redet_testing.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "redet.ipynb",
      "provenance": [],
      "mount_file_id": "1iIWZxFvm3QWMhm1tKwS3p5UuSh212zV-",
      "authorship_tag": "ABX9TyONjpTwHDpKoIGN6wx79NQj",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/mmoghadam11/ReDet/blob/master/redet_testing.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "my_dkIJk2Zxp",
        "outputId": "1dd58abb-c97f-4862-f926-8389929fd3ca"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k_0jJz2z2vSD",
        "outputId": "48149140-641c-4933-f240-236629848dbf"
      },
      "source": [
        "#باشد tesla t4 باید\n",
        "#اگر نبود در بخش ادیت - منیج سشن - ترمینت شود و از اول کار شروع شود\n",
        "!nvidia-smi"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Thu Aug 12 22:21:55 2021       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 470.42.01    Driver Version: 460.32.03    CUDA Version: 11.2     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  Tesla T4            Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   46C    P8     9W /  70W |      0MiB / 15109MiB |      0%      Default |\n",
            "|                               |                      |                  N/A |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "|  No running processes found                                                 |\n",
            "+-----------------------------------------------------------------------------+\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Yw669oToe48J"
      },
      "source": [
        "# pytorch نصب"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wP7Oo2gzpf3s",
        "outputId": "300295c8-46e0-4cc1-dfc8-63fa27375be3"
      },
      "source": [
        "# !pip install torch=1.3.1 torchvision cudatoolkit=10.0 \n",
        "!pip install torch==1.1.0 torchvision==0.3.0"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting torch==1.1.0\n",
            "  Downloading torch-1.1.0-cp37-cp37m-manylinux1_x86_64.whl (676.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 676.9 MB 3.7 kB/s \n",
            "\u001b[?25hCollecting torchvision==0.3.0\n",
            "  Downloading torchvision-0.3.0-cp37-cp37m-manylinux1_x86_64.whl (2.6 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.6 MB 58.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torch==1.1.0) (1.19.5)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from torchvision==0.3.0) (1.15.0)\n",
            "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from torchvision==0.3.0) (7.1.2)\n",
            "Installing collected packages: torch, torchvision\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 1.9.0+cu102\n",
            "    Uninstalling torch-1.9.0+cu102:\n",
            "      Successfully uninstalled torch-1.9.0+cu102\n",
            "  Attempting uninstall: torchvision\n",
            "    Found existing installation: torchvision 0.10.0+cu102\n",
            "    Uninstalling torchvision-0.10.0+cu102:\n",
            "      Successfully uninstalled torchvision-0.10.0+cu102\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchtext 0.10.0 requires torch==1.9.0, but you have torch 1.1.0 which is incompatible.\u001b[0m\n",
            "Successfully installed torch-1.1.0 torchvision-0.3.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zu855d3Fp8mg"
      },
      "source": [
        "# نصب ریپازیتوری"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xW88lC3Aqs9S",
        "outputId": "20a32c69-2f08-4ec9-a696-08052624a099"
      },
      "source": [
        "# !git clone https://github.com/dingjiansw101/AerialDetection.git\n",
        "!git clone https://github.com/csuhan/ReDet.git"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'ReDet'...\n",
            "remote: Enumerating objects: 857, done.\u001b[K\n",
            "remote: Counting objects: 100% (176/176), done.\u001b[K\n",
            "remote: Compressing objects: 100% (38/38), done.\u001b[K\n",
            "remote: Total 857 (delta 151), reused 138 (delta 138), pack-reused 681\u001b[K\n",
            "Receiving objects: 100% (857/857), 5.43 MiB | 10.64 MiB/s, done.\n",
            "Resolving deltas: 100% (327/327), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pnNs-A6grLzS",
        "outputId": "82ce8724-7ed6-4945-b917-8f451b43fd66"
      },
      "source": [
        "%cd /content/ReDet\n",
        "! chmod +rx ./compile.sh\n",
        "!./compile.sh"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/ReDet\n",
            "Building roi align op...\n",
            "running build_ext\n",
            "building 'roi_align_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/roi_align_cuda.cpp -o build/temp.linux-x86_64-3.7/src/roi_align_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=roi_align_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/roi_align_kernel.cu -o build/temp.linux-x86_64-3.7/src/roi_align_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=roi_align_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/roi_align_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/roi_align_kernel.cu:133:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/roi_align_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/roi_align_kernel.cu:276:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/roi_align_cuda.o build/temp.linux-x86_64-3.7/src/roi_align_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/roi_align_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/roi_align_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building roi pool op...\n",
            "running build_ext\n",
            "building 'roi_pool_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/roi_pool_cuda.cpp -o build/temp.linux-x86_64-3.7/src/roi_pool_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=roi_pool_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/roi_pool_kernel.cu -o build/temp.linux-x86_64-3.7/src/roi_pool_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=roi_pool_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/roi_pool_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/roi_pool_kernel.cu:88:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/roi_pool_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/roi_pool_kernel.cu:136:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/roi_pool_cuda.o build/temp.linux-x86_64-3.7/src/roi_pool_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/roi_pool_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/roi_pool_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building roi align rotated op...\n",
            "running build_ext\n",
            "building 'roi_align_rotated_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/roi_align_rotated_cuda.cpp -o build/temp.linux-x86_64-3.7/src/roi_align_rotated_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=roi_align_rotated_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/roi_align_rotated_kernel.cu -o build/temp.linux-x86_64-3.7/src/roi_align_rotated_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=roi_align_rotated_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/roi_align_rotated_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/roi_align_rotated_kernel.cu:149:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "     AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/roi_align_rotated_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/roi_align_rotated_kernel.cu:324:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "         AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/roi_align_rotated_cuda.o build/temp.linux-x86_64-3.7/src/roi_align_rotated_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/roi_align_rotated_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/roi_align_rotated_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building riroi align op...\n",
            "running build_ext\n",
            "building 'riroi_align_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/riroi_align_cuda.cpp -o build/temp.linux-x86_64-3.7/src/riroi_align_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=riroi_align_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/riroi_align_kernel.cu -o build/temp.linux-x86_64-3.7/src/riroi_align_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=riroi_align_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/riroi_align_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/riroi_align_kernel.cu:172:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "     AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/riroi_align_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/riroi_align_kernel.cu:373:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "         AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/riroi_align_cuda.o build/temp.linux-x86_64-3.7/src/riroi_align_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/riroi_align_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/riroi_align_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building ps roi align rotated op...\n",
            "running build_ext\n",
            "building 'psroi_align_rotated_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/psroi_align_rotated_cuda.cpp -o build/temp.linux-x86_64-3.7/src/psroi_align_rotated_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=psroi_align_rotated_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/psroi_align_rotated_kernel.cu -o build/temp.linux-x86_64-3.7/src/psroi_align_rotated_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=psroi_align_rotated_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/psroi_align_rotated_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/psroi_align_rotated_kernel.cu:187:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "     AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/psroi_align_rotated_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/psroi_align_rotated_kernel.cu:416:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "         AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/psroi_align_rotated_cuda.o build/temp.linux-x86_64-3.7/src/psroi_align_rotated_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/psroi_align_rotated_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/psroi_align_rotated_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building nms op...\n",
            "Compiling src/soft_nms_cpu.pyx because it changed.\n",
            "[1/1] Cythonizing src/soft_nms_cpu.pyx\n",
            "running build_ext\n",
            "building 'soft_nms_cpu' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/numpy/core/include -I/usr/include/python3.7m -c src/soft_nms_cpu.cpp -o build/temp.linux-x86_64-3.7/src/soft_nms_cpu.o -Wno-unused-function -Wno-write-strings\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1822:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/numpy/core/include/numpy/arrayobject.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Ksrc/soft_nms_cpu.cpp:657\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K#warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [\u001b[01;35m\u001b[K-Wcpp\u001b[m\u001b[K]\n",
            " #\u001b[01;35m\u001b[Kwarning\u001b[m\u001b[K \"Using deprecated NumPy API, disable it with \" \\\n",
            "  \u001b[01;35m\u001b[K^~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/soft_nms_cpu.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[KPyObject* __pyx_pf_12soft_nms_cpu_soft_nms_cpu(PyObject*, PyArrayObject*, float, unsigned int, float, float)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Ksrc/soft_nms_cpu.cpp:2474:34:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcomparison between signed and unsigned integer expressions [\u001b[01;35m\u001b[K-Wsign-compare\u001b[m\u001b[K]\n",
            "       __pyx_t_10 = ((\u001b[01;35m\u001b[K__pyx_v_pos < __pyx_v_N\u001b[m\u001b[K) != 0);\n",
            "                      \u001b[01;35m\u001b[K~~~~~~~~~~~~^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/soft_nms_cpu.cpp:2985:34:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcomparison between signed and unsigned integer expressions [\u001b[01;35m\u001b[K-Wsign-compare\u001b[m\u001b[K]\n",
            "       __pyx_t_10 = ((\u001b[01;35m\u001b[K__pyx_v_pos < __pyx_v_N\u001b[m\u001b[K) != 0);\n",
            "                      \u001b[01;35m\u001b[K~~~~~~~~~~~~^~~~~~~~~~~\u001b[m\u001b[K\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/soft_nms_cpu.o -o /content/ReDet/mmdet/ops/nms/soft_nms_cpu.cpython-37m-x86_64-linux-gnu.so\n",
            "running build_ext\n",
            "building 'nms_cuda' extension\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/nms_cuda.cpp -o build/temp.linux-x86_64-3.7/src/nms_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=nms_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/nms_kernel.cu -o build/temp.linux-x86_64-3.7/src/nms_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=nms_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/nms_cuda.o build/temp.linux-x86_64-3.7/src/nms_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/nms_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "building 'nms_cpu' extension\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/nms_cpu.cpp -o build/temp.linux-x86_64-3.7/src/nms_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=nms_cpu -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/ATen.h:9:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/types.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/data.h:3\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include/torch/all.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/torch/extension.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[Ksrc/nms_cpu.cpp:2\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[Ksrc/nms_cpu.cpp:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:71:52:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "     at::ScalarType _st = ::detail::scalar_type(TYPE\u001b[01;35m\u001b[K)\u001b[m\u001b[K;                        \\\n",
            "                                                    \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/nms_cpu.cpp:63:3:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kin expansion of macro ‘\u001b[01m\u001b[KAT_DISPATCH_FLOATING_TYPES\u001b[m\u001b[K’\n",
            "   \u001b[01;36m\u001b[KAT_DISPATCH_FLOATING_TYPES\u001b[m\u001b[K(dets.type(), \"nms\", [&] {\n",
            "   \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:23:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " inline at::ScalarType \u001b[01;36m\u001b[Kscalar_type\u001b[m\u001b[K(const at::DeprecatedTypeProperties &t) {\n",
            "                       \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/nms_cpu.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/nms_cpu.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/nms_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "copying build/lib.linux-x86_64-3.7/nms_cpu.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building dcn...\n",
            "running build_ext\n",
            "building 'deform_conv_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/deform_conv_cuda.cpp -o build/temp.linux-x86_64-3.7/src/deform_conv_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=deform_conv_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/deform_conv_cuda_kernel.cu -o build/temp.linux-x86_64-3.7/src/deform_conv_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=deform_conv_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:258:124:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                            \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:352:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:450:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:780:124:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                            \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:812:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/deform_conv_cuda_kernel.cu:845:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/deform_conv_cuda.o build/temp.linux-x86_64-3.7/src/deform_conv_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/deform_conv_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "building 'deform_pool_cuda' extension\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/deform_pool_cuda.cpp -o build/temp.linux-x86_64-3.7/src/deform_pool_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=deform_pool_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/deform_pool_cuda_kernel.cu -o build/temp.linux-x86_64-3.7/src/deform_pool_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=deform_pool_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/deform_pool_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/deform_pool_cuda_kernel.cu:291:118:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                      \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/deform_pool_cuda_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/deform_pool_cuda_kernel.cu:342:126:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                              \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/deform_pool_cuda.o build/temp.linux-x86_64-3.7/src/deform_pool_cuda_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/deform_pool_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/deform_conv_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "copying build/lib.linux-x86_64-3.7/deform_pool_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building sigmoid focal loss op...\n",
            "running build_ext\n",
            "building 'sigmoid_focal_loss_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/sigmoid_focal_loss.cpp -o build/temp.linux-x86_64-3.7/src/sigmoid_focal_loss.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=sigmoid_focal_loss_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "\u001b[01m\u001b[Ksrc/sigmoid_focal_loss.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kat::Tensor SigmoidFocalLoss_forward(const at::Tensor&, const at::Tensor&, int, float, float)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Ksrc/sigmoid_focal_loss.cpp:25:1:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcontrol reaches end of non-void function [\u001b[01;35m\u001b[K-Wreturn-type\u001b[m\u001b[K]\n",
            " \u001b[01;35m\u001b[K}\u001b[m\u001b[K\n",
            " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/sigmoid_focal_loss.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kat::Tensor SigmoidFocalLoss_backward(const at::Tensor&, const at::Tensor&, const at::Tensor&, int, float, float)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Ksrc/sigmoid_focal_loss.cpp:36:1:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kcontrol reaches end of non-void function [\u001b[01;35m\u001b[K-Wreturn-type\u001b[m\u001b[K]\n",
            " \u001b[01;35m\u001b[K}\u001b[m\u001b[K\n",
            " \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/sigmoid_focal_loss_cuda.cu -o build/temp.linux-x86_64-3.7/src/sigmoid_focal_loss_cuda.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=sigmoid_focal_loss_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/sigmoid_focal_loss_cuda.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/sigmoid_focal_loss_cuda.cu:120:122:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                          \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/sigmoid_focal_loss_cuda.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/sigmoid_focal_loss_cuda.cu:158:122:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                          \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/sigmoid_focal_loss.o build/temp.linux-x86_64-3.7/src/sigmoid_focal_loss_cuda.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/sigmoid_focal_loss_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/sigmoid_focal_loss_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building masked conv op...\n",
            "running build_ext\n",
            "building 'masked_conv2d_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/masked_conv2d_cuda.cpp -o build/temp.linux-x86_64-3.7/src/masked_conv2d_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=masked_conv2d_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/masked_conv2d_kernel.cu -o build/temp.linux-x86_64-3.7/src/masked_conv2d_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=masked_conv2d_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(83): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lowest\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(84): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"max\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(85): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"lower_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "/usr/local/lib/python3.7/dist-packages/torch/include/ATen/cuda/NumericLimits.cuh(86): warning: calling a constexpr __host__ function(\"from_bits\") from a __host__ __device__ function(\"upper_bound\") is not allowed. The experimental flag '--expt-relaxed-constexpr' can be used to allow this.\n",
            "\n",
            "\u001b[01m\u001b[Ksrc/masked_conv2d_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/masked_conv2d_kernel.cu:59:132:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                                    \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Ksrc/masked_conv2d_kernel.cu:\u001b[m\u001b[K In lambda function:\n",
            "\u001b[01m\u001b[Ksrc/masked_conv2d_kernel.cu:99:132:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[Kc10::ScalarType detail::scalar_type(const at::DeprecatedTypeProperties&)\u001b[m\u001b[K’ is deprecated [\u001b[01;35m\u001b[K-Wdeprecated-declarations\u001b[m\u001b[K]\n",
            "   AT_DISPATCH_FLOATING_TYPES_AND_HALF(\n",
            "                                                                                                                                    \u001b[01;35m\u001b[K^\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/torch/include/ATen/Dispatch.h:47:1:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdeclared here\n",
            " \u001b[01;36m\u001b[Kinline at::\u001b[m\u001b[KScalarType scalar_type(const at::DeprecatedTypeProperties &t) {\n",
            " \u001b[01;36m\u001b[K^~~~~~~~~~~\u001b[m\u001b[K\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/masked_conv2d_cuda.o build/temp.linux-x86_64-3.7/src/masked_conv2d_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/masked_conv2d_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/masked_conv2d_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building poly_nms op...\n",
            "running build_ext\n",
            "building 'poly_nms_cuda' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "creating build/temp.linux-x86_64-3.7/src\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/poly_nms_cuda.cpp -o build/temp.linux-x86_64-3.7/src/poly_nms_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=poly_nms_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "/usr/local/cuda/bin/nvcc -I/usr/local/lib/python3.7/dist-packages/torch/include -I/usr/local/lib/python3.7/dist-packages/torch/include/torch/csrc/api/include -I/usr/local/lib/python3.7/dist-packages/torch/include/TH -I/usr/local/lib/python3.7/dist-packages/torch/include/THC -I/usr/local/cuda/include -I/usr/include/python3.7m -c src/poly_nms_kernel.cu -o build/temp.linux-x86_64-3.7/src/poly_nms_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=poly_nms_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11\n",
            "creating build/lib.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/src/poly_nms_cuda.o build/temp.linux-x86_64-3.7/src/poly_nms_kernel.o -L/usr/local/cuda/lib64 -lcudart -o build/lib.linux-x86_64-3.7/poly_nms_cuda.cpython-37m-x86_64-linux-gnu.so\n",
            "copying build/lib.linux-x86_64-3.7/poly_nms_cuda.cpython-37m-x86_64-linux-gnu.so -> \n",
            "Building cpu_nms...\n",
            "running build_ext\n",
            "skipping 'bbox.c' Cython extension (up-to-date)\n",
            "building 'bbox' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.7/dist-packages/numpy/core/include -I/usr/include/python3.7m -c bbox.c -o build/temp.linux-x86_64-3.7/bbox.o -Wno-cpp -Wno-unused-function\n",
            "x86_64-linux-gnu-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/bbox.o -o /content/ReDet/mmdet/core/bbox/bbox.cpython-37m-x86_64-linux-gnu.so\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ULAHXBESugF4",
        "outputId": "60f525bf-49a8-4557-d36a-fcb397f93ef3"
      },
      "source": [
        "!python setup.py develop\n",
        "# !pip install -e ."
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "running develop\n",
            "running egg_info\n",
            "creating mmdet.egg-info\n",
            "writing mmdet.egg-info/PKG-INFO\n",
            "writing dependency_links to mmdet.egg-info/dependency_links.txt\n",
            "writing requirements to mmdet.egg-info/requires.txt\n",
            "writing top-level names to mmdet.egg-info/top_level.txt\n",
            "writing manifest file 'mmdet.egg-info/SOURCES.txt'\n",
            "adding license file 'LICENSE'\n",
            "writing manifest file 'mmdet.egg-info/SOURCES.txt'\n",
            "running build_ext\n",
            "Creating /usr/local/lib/python3.7/dist-packages/mmdet.egg-link (link to .)\n",
            "Adding mmdet 0.6.0+0b9addf to easy-install.pth file\n",
            "\n",
            "Installed /content/ReDet\n",
            "Processing dependencies for mmdet==0.6.0+0b9addf\n",
            "Searching for e2cnn\n",
            "Reading https://pypi.org/simple/e2cnn/\n",
            "Downloading https://files.pythonhosted.org/packages/c7/8d/722bc9fdecf8474da375d8e98a11e18f3cc6c843a0abcc171a8a3fb4db47/e2cnn-0.1.9-py3-none-any.whl#sha256=56aadd0dcc4799d748f5ac6ccedb08dbe76d8e68d06444453139024b9a725549\n",
            "Best match: e2cnn 0.1.9\n",
            "Processing e2cnn-0.1.9-py3-none-any.whl\n",
            "Installing e2cnn-0.1.9-py3-none-any.whl to /usr/local/lib/python3.7/dist-packages\n",
            "Adding e2cnn 0.1.9 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/e2cnn-0.1.9-py3.7.egg\n",
            "Searching for terminaltables\n",
            "Reading https://pypi.org/simple/terminaltables/\n",
            "Downloading https://files.pythonhosted.org/packages/9b/c4/4a21174f32f8a7e1104798c445dacdc1d4df86f2f26722767034e4de4bff/terminaltables-3.1.0.tar.gz#sha256=f3eb0eb92e3833972ac36796293ca0906e998dc3be91fbe1f8615b331b853b81\n",
            "Best match: terminaltables 3.1.0\n",
            "Processing terminaltables-3.1.0.tar.gz\n",
            "Writing /tmp/easy_install-t6zsy238/terminaltables-3.1.0/setup.cfg\n",
            "Running terminaltables-3.1.0/setup.py -q bdist_egg --dist-dir /tmp/easy_install-t6zsy238/terminaltables-3.1.0/egg-dist-tmp-qn_oqu7j\n",
            "Moving terminaltables-3.1.0-py3.7.egg to /usr/local/lib/python3.7/dist-packages\n",
            "Adding terminaltables 3.1.0 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/terminaltables-3.1.0-py3.7.egg\n",
            "Searching for pillow==6.2.2\n",
            "Reading https://pypi.org/simple/pillow/\n",
            "Downloading https://files.pythonhosted.org/packages/c3/3f/03375124676ab49ca6e6917c0f1f663afb8354d5d24e12f4fe4587a39ae2/Pillow-6.2.2-cp37-cp37m-manylinux1_x86_64.whl#sha256=c424d35a5259be559b64490d0fd9e03fba81f1ce8e5b66e0a59de97547351d80\n",
            "Best match: Pillow 6.2.2\n",
            "Processing Pillow-6.2.2-cp37-cp37m-manylinux1_x86_64.whl\n",
            "Installing Pillow-6.2.2-cp37-cp37m-manylinux1_x86_64.whl to /usr/local/lib/python3.7/dist-packages\n",
            "Adding Pillow 6.2.2 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/Pillow-6.2.2-py3.7-linux-x86_64.egg\n",
            "Searching for mmcv==0.2.13\n",
            "Reading https://pypi.org/simple/mmcv/\n",
            "Downloading https://files.pythonhosted.org/packages/86/98/2db09740465707361f363f8644c71c98d0d9fe28c1f2e5821f8c5a4ee5ba/mmcv-0.2.13.tar.gz#sha256=edd7b221641333e01c2ad4301a1b80ee0f69166e0666fd2aca6b9898c995a197\n",
            "Best match: mmcv 0.2.13\n",
            "Processing mmcv-0.2.13.tar.gz\n",
            "Writing /tmp/easy_install-w0h6e9lc/mmcv-0.2.13/setup.cfg\n",
            "Running mmcv-0.2.13/setup.py -q bdist_egg --dist-dir /tmp/easy_install-w0h6e9lc/mmcv-0.2.13/egg-dist-tmp-tee9cw2v\n",
            "/usr/local/lib/python3.7/dist-packages/Cython/Compiler/Main.py:369: FutureWarning: Cython directive 'language_level' not set, using 2 for now (Py2). This will change in a later release! File: /tmp/easy_install-w0h6e9lc/mmcv-0.2.13/mmcv/video/optflow_warp/flow_warp_module.pyx\n",
            "  tree = Parsing.p_module(s, pxd, full_module_name)\n",
            "In file included from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/numpy/core/include/numpy/ndarraytypes.h:1822:0\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/numpy/core/include/numpy/ndarrayobject.h:12\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/numpy/core/include/numpy/arrayobject.h:4\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K./mmcv/video/optflow_warp/flow_warp_module.cpp:626\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/local/lib/python3.7/dist-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K#warning \"Using deprecated NumPy API, disable it with \" \"#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION\" [\u001b[01;35m\u001b[K-Wcpp\u001b[m\u001b[K]\n",
            " #\u001b[01;35m\u001b[Kwarning\u001b[m\u001b[K \"Using deprecated NumPy API, disable it with \" \\\n",
            "  \u001b[01;35m\u001b[K^~~~~~~\u001b[m\u001b[K\n",
            "creating /usr/local/lib/python3.7/dist-packages/mmcv-0.2.13-py3.7-linux-x86_64.egg\n",
            "Extracting mmcv-0.2.13-py3.7-linux-x86_64.egg to /usr/local/lib/python3.7/dist-packages\n",
            "Adding mmcv 0.2.13 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/mmcv-0.2.13-py3.7-linux-x86_64.egg\n",
            "Searching for addict\n",
            "Reading https://pypi.org/simple/addict/\n",
            "Downloading https://files.pythonhosted.org/packages/6a/00/b08f23b7d7e1e14ce01419a467b583edbb93c6cdb8654e54a9cc579cd61f/addict-2.4.0-py3-none-any.whl#sha256=249bb56bbfd3cdc2a004ea0ff4c2b6ddc84d53bc2194761636eb314d5cfa5dfc\n",
            "Best match: addict 2.4.0\n",
            "Processing addict-2.4.0-py3-none-any.whl\n",
            "Installing addict-2.4.0-py3-none-any.whl to /usr/local/lib/python3.7/dist-packages\n",
            "Adding addict 2.4.0 to easy-install.pth file\n",
            "\n",
            "Installed /usr/local/lib/python3.7/dist-packages/addict-2.4.0-py3.7.egg\n",
            "Searching for pycocotools==2.0.2\n",
            "Best match: pycocotools 2.0.2\n",
            "Adding pycocotools 2.0.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for six==1.15.0\n",
            "Best match: six 1.15.0\n",
            "Adding six 1.15.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for matplotlib==3.2.2\n",
            "Best match: matplotlib 3.2.2\n",
            "Adding matplotlib 3.2.2 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for tqdm==4.41.1\n",
            "Best match: tqdm 4.41.1\n",
            "Adding tqdm 4.41.1 to easy-install.pth file\n",
            "Installing tqdm script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for Shapely==1.7.1\n",
            "Best match: Shapely 1.7.1\n",
            "Adding Shapely 1.7.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for numpy==1.19.5\n",
            "Best match: numpy 1.19.5\n",
            "Adding numpy 1.19.5 to easy-install.pth file\n",
            "Installing f2py script to /usr/local/bin\n",
            "Installing f2py3 script to /usr/local/bin\n",
            "Installing f2py3.7 script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for torch==1.1.0\n",
            "Best match: torch 1.1.0\n",
            "Adding torch 1.1.0 to easy-install.pth file\n",
            "Installing convert-caffe2-to-onnx script to /usr/local/bin\n",
            "Installing convert-onnx-to-caffe2 script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for scipy==1.4.1\n",
            "Best match: scipy 1.4.1\n",
            "Adding scipy 1.4.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for Cython==0.29.23\n",
            "Best match: Cython 0.29.23\n",
            "Adding Cython 0.29.23 to easy-install.pth file\n",
            "Installing cygdb script to /usr/local/bin\n",
            "Installing cython script to /usr/local/bin\n",
            "Installing cythonize script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for setuptools==57.2.0\n",
            "Best match: setuptools 57.2.0\n",
            "Adding setuptools 57.2.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for python-dateutil==2.8.1\n",
            "Best match: python-dateutil 2.8.1\n",
            "Adding python-dateutil 2.8.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for kiwisolver==1.3.1\n",
            "Best match: kiwisolver 1.3.1\n",
            "Adding kiwisolver 1.3.1 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for pyparsing==2.4.7\n",
            "Best match: pyparsing 2.4.7\n",
            "Adding pyparsing 2.4.7 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for cycler==0.10.0\n",
            "Best match: cycler 0.10.0\n",
            "Adding cycler 0.10.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for opencv-python==4.1.2.30\n",
            "Best match: opencv-python 4.1.2.30\n",
            "Adding opencv-python 4.1.2.30 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for requests==2.23.0\n",
            "Best match: requests 2.23.0\n",
            "Adding requests 2.23.0 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for PyYAML==3.13\n",
            "Best match: PyYAML 3.13\n",
            "Adding PyYAML 3.13 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for idna==2.10\n",
            "Best match: idna 2.10\n",
            "Adding idna 2.10 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for chardet==3.0.4\n",
            "Best match: chardet 3.0.4\n",
            "Adding chardet 3.0.4 to easy-install.pth file\n",
            "Installing chardetect script to /usr/local/bin\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for certifi==2021.5.30\n",
            "Best match: certifi 2021.5.30\n",
            "Adding certifi 2021.5.30 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Searching for urllib3==1.24.3\n",
            "Best match: urllib3 1.24.3\n",
            "Adding urllib3 1.24.3 to easy-install.pth file\n",
            "\n",
            "Using /usr/local/lib/python3.7/dist-packages\n",
            "Finished processing dependencies for mmdet==0.6.0+0b9addf\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hYurbclbqDrY"
      },
      "source": [
        "# نصب DOTA_devkit"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WmL2sGYEupcz",
        "outputId": "888729f2-5803-4d92-e1c9-2b4cf5851266"
      },
      "source": [
        "! apt-get install swig\n",
        "%cd /content/ReDet/DOTA_devkit\n",
        "!swig -c++ -python polyiou.i\n",
        "!python setup.py build_ext --inplace"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "The following additional packages will be installed:\n",
            "  swig3.0\n",
            "Suggested packages:\n",
            "  swig-doc swig-examples swig3.0-examples swig3.0-doc\n",
            "The following NEW packages will be installed:\n",
            "  swig swig3.0\n",
            "0 upgraded, 2 newly installed, 0 to remove and 40 not upgraded.\n",
            "Need to get 1,100 kB of archives.\n",
            "After this operation, 5,822 kB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 swig3.0 amd64 3.0.12-1 [1,094 kB]\n",
            "Get:2 http://archive.ubuntu.com/ubuntu bionic/universe amd64 swig amd64 3.0.12-1 [6,460 B]\n",
            "Fetched 1,100 kB in 1s (866 kB/s)\n",
            "Selecting previously unselected package swig3.0.\n",
            "(Reading database ... 160837 files and directories currently installed.)\n",
            "Preparing to unpack .../swig3.0_3.0.12-1_amd64.deb ...\n",
            "Unpacking swig3.0 (3.0.12-1) ...\n",
            "Selecting previously unselected package swig.\n",
            "Preparing to unpack .../swig_3.0.12-1_amd64.deb ...\n",
            "Unpacking swig (3.0.12-1) ...\n",
            "Setting up swig3.0 (3.0.12-1) ...\n",
            "Setting up swig (3.0.12-1) ...\n",
            "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n",
            "/content/ReDet/DOTA_devkit\n",
            "running build_ext\n",
            "building '_polyiou' extension\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.7\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/python3.7m -c polyiou_wrap.cxx -o build/temp.linux-x86_64-3.7/polyiou_wrap.o\n",
            "x86_64-linux-gnu-gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/python3.7m -c polyiou.cpp -o build/temp.linux-x86_64-3.7/polyiou.o\n",
            "\u001b[01m\u001b[Kpolyiou.cpp:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[Kdouble intersectArea(Point, Point, Point, Point)\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Kpolyiou.cpp:88:5:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kthis ‘\u001b[01m\u001b[Kif\u001b[m\u001b[K’ clause does not guard... [\u001b[01;35m\u001b[K-Wmisleading-indentation\u001b[m\u001b[K]\n",
            "     \u001b[01;35m\u001b[Kif\u001b[m\u001b[K(s1*s2==-1) res=-res;return res;\n",
            "     \u001b[01;35m\u001b[K^~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[Kpolyiou.cpp:88:28:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[K...this statement, but the latter is misleadingly indented as if it were guarded by the ‘\u001b[01m\u001b[Kif\u001b[m\u001b[K’\n",
            "     if(s1*s2==-1) res=-res;\u001b[01;36m\u001b[Kreturn\u001b[m\u001b[K res;\n",
            "                            \u001b[01;36m\u001b[K^~~~~~\u001b[m\u001b[K\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fdebug-prefix-map=/build/python3.7-LSlbJj/python3.7-3.7.11=. -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.7/polyiou_wrap.o build/temp.linux-x86_64-3.7/polyiou.o -o /content/ReDet/DOTA_devkit/_polyiou.cpython-37m-x86_64-linux-gnu.so\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wklxzgvdv4f7"
      },
      "source": [
        "# حال وقت آن است که تصاویری با اندازه ۱۰۲۴*۱۰۲۴ بسازیم و حجم نهیی آن بیش از ۳۵ گیگ خواهد بود"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kgbfn9Dkmr-X",
        "outputId": "ce49929f-64fa-4e01-fd25-d6ee45f0f2f9"
      },
      "source": [
        "#unzip .pth file فایل چکپوینت\n",
        "# !unzip '/content/drive/MyDrive/aerial detection pth/weight_file_r101_baseline.zip' -d '/content/drive/MyDrive/4++/work_dirs/pth/'"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Archive:  /content/drive/MyDrive/aerial detection pth/weight_file_r101_baseline.zip\n",
            "   creating: /content/drive/MyDrive/4++/work_dirs/pth/weight_file_r101_baseline/\n",
            "   creating: /content/drive/MyDrive/4++/work_dirs/pth/weight_file_r101_baseline/work_dirs/\n",
            "   creating: /content/drive/MyDrive/4++/work_dirs/pth/weight_file_r101_baseline/work_dirs/faster_rcnn_RoITrans_r101_fpn_baseline/\n",
            "  inflating: /content/drive/MyDrive/4++/work_dirs/pth/weight_file_r101_baseline/work_dirs/faster_rcnn_RoITrans_r101_fpn_baseline/epoch_12.pth  \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2k2kF835wffg"
      },
      "source": [
        "#برای مدیریت حافظ از سیمبلیک لینک کمک گرفتم\n",
        "!mkdir '/content/ReDet/data'\n",
        "# !mkdir '/content/AerialDetection/data/dota1_1024'\n",
        "!ln -s  /content/drive/Shareddrives/mahdiyar_SBU/data/dota1_1024 /content/ReDet/data\n",
        "\n",
        "# !ln -s /content/drive/MyDrive/++ /content/AerialDetection/data/dota1_1024/test1024\n",
        "# !ln -s /content/drive/MyDrive/4++/trainval1024 /content/AerialDetection/data/dota1_1024/trainval1024\n",
        "\n",
        "# !unlink /content/AerialDetection/data/dota1_1024/trainval1024\n",
        "!ln -s /content/drive/MyDrive/4++/work_dirs /content/ReDet"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7oG5TnqTplI_"
      },
      "source": [
        "# بررسی حافظه"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LEbzqqOJY7Qk",
        "outputId": "2bd2067d-5dfc-473f-b68b-423bfb0a7d9c"
      },
      "source": [
        "#ممکن است بار اول بعد ۲ دقیقه خطا دهد. اگر خطا داد دوباره همین دستور اجرا شود (بار دوم خطا نمیدهد)\n",
        "import os\n",
        "\n",
        "print(len(os.listdir(os.path.join('/content/ReDet/data/dota1_1024/test1024/images'))))"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4750\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "49gzH6svQfIr",
        "outputId": "3beda6f7-1c72-4130-dd08-fb6dd4d4fbf8"
      },
      "source": [
        "#میتوان فولدر را چک کرد(اختیاری)\n",
        "!du -c /content/AerialDetection/data/dota1_1024"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4\t/content/AerialDetection/data/dota1_1024\n",
            "4\ttotal\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X_EkOnCPppQW"
      },
      "source": [
        "# نصب mmcv"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YOeH-8AKAPeZ",
        "outputId": "f11a3a15-b75f-4f4e-c165-647c6421e999"
      },
      "source": [
        "%cd /content/ReDet\n",
        "!pip install mmcv==0.2.13 #<=0.2.14\n",
        "# !pip install mmcv==0.4.3\n",
        "# !pip install mmcv==1.3.9"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/ReDet\n",
            "Requirement already satisfied: mmcv==0.2.13 in /usr/local/lib/python3.7/dist-packages/mmcv-0.2.13-py3.7-linux-x86_64.egg (0.2.13)\n",
            "Requirement already satisfied: numpy>=1.11.1 in /usr/local/lib/python3.7/dist-packages (from mmcv==0.2.13) (1.19.5)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.7/dist-packages (from mmcv==0.2.13) (3.13)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from mmcv==0.2.13) (1.15.0)\n",
            "Requirement already satisfied: addict in /usr/local/lib/python3.7/dist-packages/addict-2.4.0-py3.7.egg (from mmcv==0.2.13) (2.4.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from mmcv==0.2.13) (2.23.0)\n",
            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (from mmcv==0.2.13) (4.1.2.30)\n",
            "Requirement already satisfied: Cython in /usr/local/lib/python3.7/dist-packages (from mmcv==0.2.13) (0.29.23)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->mmcv==0.2.13) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->mmcv==0.2.13) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->mmcv==0.2.13) (2021.5.30)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->mmcv==0.2.13) (2.10)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JeFqZPhZ_s46"
      },
      "source": [
        "# نکته ی بسیار مهم در کانفیگ مدل ها تایین زمان ثبت چکپوینت هنگام آموزش، مکان دیتاست می‌باشد"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gyqMbxerkgVg"
      },
      "source": [
        "redet config"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4VPI6CdQ_emr",
        "outputId": "79971fab-b6e5-496d-c947-eca54764c220"
      },
      "source": [
        "# %pycat /content/CG-Net/configs/DOTA/faster_rcnn_RoITrans_r101_fpn_baseline.py\n",
        "%%writefile /content/ReDet/configs/ReDet/ReDet_re50_refpn_1x_dota1.py \n",
        "############باید مکان دیتاست و اسم آن در فایل کانفیگ به روز شود در بالای خط دستور تغیر یک خط علامت # گزاشته ام\n",
        "\n",
        "# model settings\n",
        "model = dict(\n",
        "    type='ReDet',\n",
        "    ############################################################################################################\n",
        "    # pretrained='work_dirs/ReResNet_pretrain/re_resnet50_c8_batch256-12933bc2.pth',\n",
        "    pretrained='/content/ReDet/work_dirs/ReResNet_pretrain/re_resnet50_c8_batch256-25b16846.pth',\n",
        "    ############################################################################################################\n",
        "    backbone=dict(\n",
        "        type='ReResNet',\n",
        "        depth=50,\n",
        "        num_stages=4,\n",
        "        out_indices=(0, 1, 2, 3),\n",
        "        frozen_stages=1,\n",
        "        style='pytorch'),\n",
        "    neck=dict(\n",
        "        type='ReFPN',\n",
        "        in_channels=[256, 512, 1024, 2048],\n",
        "        out_channels=256,\n",
        "        num_outs=5),\n",
        "    rpn_head=dict(\n",
        "        type='RPNHead',\n",
        "        in_channels=256,\n",
        "        feat_channels=256,\n",
        "        anchor_scales=[8],\n",
        "        anchor_ratios=[0.5, 1.0, 2.0],\n",
        "        anchor_strides=[4, 8, 16, 32, 64],\n",
        "        target_means=[.0, .0, .0, .0],\n",
        "        target_stds=[1.0, 1.0, 1.0, 1.0],\n",
        "        loss_cls=dict(\n",
        "            type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),\n",
        "        loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0)),\n",
        "    bbox_roi_extractor=dict(\n",
        "        type='SingleRoIExtractor',\n",
        "        roi_layer=dict(type='RoIAlign', out_size=7, sample_num=2),\n",
        "        out_channels=256,\n",
        "        featmap_strides=[4, 8, 16, 32]),\n",
        "    bbox_head=dict(\n",
        "        type='SharedFCBBoxHeadRbbox',\n",
        "        num_fcs=2,\n",
        "        in_channels=256,\n",
        "        fc_out_channels=1024,\n",
        "        roi_feat_size=7,\n",
        "        num_classes=16,\n",
        "        target_means=[0., 0., 0., 0., 0.],\n",
        "        target_stds=[0.1, 0.1, 0.2, 0.2, 0.1],\n",
        "        reg_class_agnostic=True,\n",
        "        with_module=False,\n",
        "        loss_cls=dict(\n",
        "            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),\n",
        "        loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0)),\n",
        "    rbbox_roi_extractor=dict(\n",
        "        type='RboxSingleRoIExtractor',\n",
        "        roi_layer=dict(type='RiRoIAlign', out_size=7, sample_num=2),\n",
        "        out_channels=256,\n",
        "        featmap_strides=[4, 8, 16, 32]),\n",
        "    rbbox_head = dict(\n",
        "        type='SharedFCBBoxHeadRbbox',\n",
        "        num_fcs=2,\n",
        "        in_channels=256,\n",
        "        fc_out_channels=1024,\n",
        "        roi_feat_size=7,\n",
        "        num_classes=16,\n",
        "        target_means=[0., 0., 0., 0., 0.],\n",
        "        target_stds=[0.05, 0.05, 0.1, 0.1, 0.05],\n",
        "        reg_class_agnostic=False,\n",
        "        loss_cls=dict(\n",
        "            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),\n",
        "        loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))\n",
        "    )\n",
        "# model training and testing settings\n",
        "train_cfg = dict(\n",
        "    rpn=dict(\n",
        "        assigner=dict(\n",
        "            type='MaxIoUAssignerCy',\n",
        "            pos_iou_thr=0.7,\n",
        "            neg_iou_thr=0.3,\n",
        "            min_pos_iou=0.3,\n",
        "            ignore_iof_thr=-1),\n",
        "        sampler=dict(\n",
        "            type='RandomSampler',\n",
        "            num=256,\n",
        "            pos_fraction=0.5,\n",
        "            neg_pos_ub=-1,\n",
        "            add_gt_as_proposals=False),\n",
        "        allowed_border=0,\n",
        "        pos_weight=-1,\n",
        "        debug=False),\n",
        "    rpn_proposal=dict(\n",
        "        nms_across_levels=False,\n",
        "        nms_pre=2000,\n",
        "        nms_post=2000,\n",
        "        max_num=2000,\n",
        "        nms_thr=0.7,\n",
        "        min_bbox_size=0),\n",
        "    rcnn=[\n",
        "        dict(\n",
        "            assigner=dict(\n",
        "                type='MaxIoUAssignerCy',\n",
        "                pos_iou_thr=0.5,\n",
        "                neg_iou_thr=0.5,\n",
        "                min_pos_iou=0.5,\n",
        "                ignore_iof_thr=-1),\n",
        "            sampler=dict(\n",
        "                type='RandomSampler',\n",
        "                num=512,\n",
        "                pos_fraction=0.25,\n",
        "                neg_pos_ub=-1,\n",
        "                add_gt_as_proposals=True),\n",
        "            pos_weight=-1,\n",
        "            debug=False),\n",
        "        dict(\n",
        "            assigner=dict(\n",
        "                type='MaxIoUAssignerRbbox',\n",
        "                pos_iou_thr=0.5,\n",
        "                neg_iou_thr=0.5,\n",
        "                min_pos_iou=0.5,\n",
        "                ignore_iof_thr=-1),\n",
        "            sampler=dict(\n",
        "                type='RandomRbboxSampler',\n",
        "                num=512,\n",
        "                pos_fraction=0.25,\n",
        "                neg_pos_ub=-1,\n",
        "                add_gt_as_proposals=True),\n",
        "            pos_weight=-1,\n",
        "            debug=False)\n",
        "    ])\n",
        "test_cfg = dict(\n",
        "    rpn=dict(\n",
        "        # TODO: test nms 2000\n",
        "        nms_across_levels=False,\n",
        "        nms_pre=2000,\n",
        "        nms_post=2000,\n",
        "        max_num=2000,\n",
        "        nms_thr=0.7,\n",
        "        min_bbox_size=0),\n",
        "    rcnn=dict(\n",
        "        score_thr = 0.05, nms = dict(type='py_cpu_nms_poly_fast', iou_thr=0.1), max_per_img = 2000)\n",
        ")\n",
        "# dataset settings\n",
        "dataset_type = 'DOTADataset'\n",
        "########################################################################################################################\n",
        "data_root = '/content/ReDet/data/dota1_1024/'\n",
        "########################################################################################################################\n",
        "img_norm_cfg = dict(\n",
        "    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)\n",
        "data = dict(\n",
        "    imgs_per_gpu=2,\n",
        "    workers_per_gpu=2,\n",
        "    train=dict(\n",
        "        type=dataset_type,\n",
        "        ####################################################################################\n",
        "        ann_file=data_root + 'trainval1024/DOTA_trainval1024.json',\n",
        "        img_prefix=data_root + 'trainval1024/images',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0.5,\n",
        "        with_mask=True,\n",
        "        with_crowd=True,\n",
        "        with_label=True),\n",
        "    val=dict(\n",
        "        type=dataset_type,\n",
        "        ann_file=data_root + 'trainval1024/DOTA_trainval1024.json',\n",
        "        img_prefix=data_root + 'trainval1024/images',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0,\n",
        "        with_mask=True,\n",
        "        with_crowd=True,\n",
        "        with_label=True),\n",
        "    test=dict(\n",
        "        type=dataset_type,\n",
        "        ann_file=data_root + 'test1024/DOTA_test1024.json',\n",
        "        img_prefix=data_root + 'test1024/images',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0,\n",
        "        with_mask=False,\n",
        "        with_label=False,\n",
        "        test_mode=True))\n",
        "        ####################################################################################\n",
        "# optimizer\n",
        "optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)\n",
        "optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))\n",
        "# learning policy\n",
        "lr_config = dict(\n",
        "    policy='step',\n",
        "    warmup='linear',\n",
        "    warmup_iters=500,\n",
        "    warmup_ratio=1.0 / 3,\n",
        "    step=[8, 11])\n",
        "checkpoint_config = dict(interval=12)\n",
        "# yapf:disable\n",
        "log_config = dict(\n",
        "    interval=50,\n",
        "    hooks=[\n",
        "        dict(type='TextLoggerHook'),\n",
        "        ####################################################################################\n",
        "        dict(type='TensorboardLoggerHook')\n",
        "    ])\n",
        "# yapf:enable\n",
        "# runtime settings\n",
        "total_epochs = 12\n",
        "dist_params = dict(backend='nccl')\n",
        "log_level = 'INFO'\n",
        "work_dir = './work_dirs/ReDet_re50_refpn_1x_dota1'\n",
        "load_from = None\n",
        "resume_from = None\n",
        "workflow = [('train', 1)]\n",
        "\n",
        "############################################################################################\n",
        "# map: 0.7625466854468368\n",
        "# classaps:  [88.78856374 82.64427543 53.97022743 73.99912889 78.12618094 84.05574561\n",
        "# 88.03844621 90.88860051 87.78155929 85.75268025 61.76308434 60.39378975\n",
        "# 75.9600904  68.06737265 63.59028274]"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Overwriting /content/ReDet/configs/ReDet/ReDet_re50_refpn_1x_dota1.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JR_FFp_-kmqJ"
      },
      "source": [
        "faster_rcnn_RoITrans_r50_fpn_1x_dota config"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yxmi-iv7ksJx",
        "outputId": "2560f855-771c-4cab-fb4b-2519a4043fd2"
      },
      "source": [
        "# %pycat /content/ReDet/configs/DOTA/faster_rcnn_RoITrans_r50_fpn_1x_dota.py\n",
        "%%writefile /content/ReDet/configs/DOTA/faster_rcnn_RoITrans_r50_fpn_1x_dota.py\n",
        "##########این کانفیگ از ریپازیتوری اصلی کپی شده\n",
        "\n",
        "# model settings\n",
        "model = dict(\n",
        "    type='RoITransformer',\n",
        "    pretrained='modelzoo://resnet50',\n",
        "    backbone=dict(\n",
        "        type='ResNet',\n",
        "        depth=50,\n",
        "        num_stages=4,\n",
        "        out_indices=(0, 1, 2, 3),\n",
        "        frozen_stages=1,\n",
        "        style='pytorch'),\n",
        "    neck=dict(\n",
        "        type='FPN',\n",
        "        in_channels=[256, 512, 1024, 2048],\n",
        "        out_channels=256,\n",
        "        num_outs=5),\n",
        "    rpn_head=dict(\n",
        "        type='RPNHead',\n",
        "        in_channels=256,\n",
        "        feat_channels=256,\n",
        "        anchor_scales=[8],\n",
        "        anchor_ratios=[0.5, 1.0, 2.0],\n",
        "        anchor_strides=[4, 8, 16, 32, 64],\n",
        "        target_means=[.0, .0, .0, .0],\n",
        "        target_stds=[1.0, 1.0, 1.0, 1.0],\n",
        "        loss_cls=dict(\n",
        "            type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),\n",
        "        loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0)),\n",
        "    bbox_roi_extractor=dict(\n",
        "        type='SingleRoIExtractor',\n",
        "        roi_layer=dict(type='RoIAlign', out_size=7, sample_num=2),\n",
        "        out_channels=256,\n",
        "        featmap_strides=[4, 8, 16, 32]),\n",
        "    bbox_head=dict(\n",
        "        type='SharedFCBBoxHeadRbbox',\n",
        "        num_fcs=2,\n",
        "        in_channels=256,\n",
        "        fc_out_channels=1024,\n",
        "        roi_feat_size=7,\n",
        "        num_classes=16,\n",
        "        target_means=[0., 0., 0., 0., 0.],\n",
        "        target_stds=[0.1, 0.1, 0.2, 0.2, 0.1],\n",
        "        reg_class_agnostic=True,\n",
        "        with_module=False,\n",
        "        loss_cls=dict(\n",
        "            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),\n",
        "        loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0)),\n",
        "    rbbox_roi_extractor=dict(\n",
        "        type='RboxSingleRoIExtractor',\n",
        "        roi_layer=dict(type='RoIAlignRotated', out_size=7, sample_num=2),\n",
        "        out_channels=256,\n",
        "        featmap_strides=[4, 8, 16, 32]),\n",
        "    rbbox_head = dict(\n",
        "        type='SharedFCBBoxHeadRbbox',\n",
        "        num_fcs=2,\n",
        "        in_channels=256,\n",
        "        fc_out_channels=1024,\n",
        "        roi_feat_size=7,\n",
        "        num_classes=16,\n",
        "        target_means=[0., 0., 0., 0., 0.],\n",
        "        target_stds=[0.05, 0.05, 0.1, 0.1, 0.05],\n",
        "        reg_class_agnostic=False,\n",
        "        loss_cls=dict(\n",
        "            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),\n",
        "        loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0))\n",
        "    )\n",
        "# model training and testing settings\n",
        "train_cfg = dict(\n",
        "    rpn=dict(\n",
        "        assigner=dict(\n",
        "            type='MaxIoUAssignerCy',\n",
        "            pos_iou_thr=0.7,\n",
        "            neg_iou_thr=0.3,\n",
        "            min_pos_iou=0.3,\n",
        "            ignore_iof_thr=-1),\n",
        "        sampler=dict(\n",
        "            type='RandomSampler',\n",
        "            num=256,\n",
        "            pos_fraction=0.5,\n",
        "            neg_pos_ub=-1,\n",
        "            add_gt_as_proposals=False),\n",
        "        allowed_border=0,\n",
        "        pos_weight=-1,\n",
        "        debug=False),\n",
        "    rpn_proposal=dict(\n",
        "        nms_across_levels=False,\n",
        "        nms_pre=2000,\n",
        "        nms_post=2000,\n",
        "        max_num=2000,\n",
        "        nms_thr=0.7,\n",
        "        min_bbox_size=0),\n",
        "    rcnn=[\n",
        "        dict(\n",
        "            assigner=dict(\n",
        "                type='MaxIoUAssignerCy',\n",
        "                pos_iou_thr=0.5,\n",
        "                neg_iou_thr=0.5,\n",
        "                min_pos_iou=0.5,\n",
        "                ignore_iof_thr=-1),\n",
        "            sampler=dict(\n",
        "                type='RandomSampler',\n",
        "                num=512,\n",
        "                pos_fraction=0.25,\n",
        "                neg_pos_ub=-1,\n",
        "                add_gt_as_proposals=True),\n",
        "            pos_weight=-1,\n",
        "            debug=False),\n",
        "        dict(\n",
        "            assigner=dict(\n",
        "                type='MaxIoUAssignerRbbox',\n",
        "                pos_iou_thr=0.5,\n",
        "                neg_iou_thr=0.5,\n",
        "                min_pos_iou=0.5,\n",
        "                ignore_iof_thr=-1),\n",
        "            sampler=dict(\n",
        "                type='RandomRbboxSampler',\n",
        "                num=512,\n",
        "                pos_fraction=0.25,\n",
        "                neg_pos_ub=-1,\n",
        "                add_gt_as_proposals=True),\n",
        "            pos_weight=-1,\n",
        "            debug=False)\n",
        "    ])\n",
        "test_cfg = dict(\n",
        "    rpn=dict(\n",
        "        # TODO: test nms 2000\n",
        "        nms_across_levels=False,\n",
        "        nms_pre=2000,\n",
        "        nms_post=2000,\n",
        "        max_num=2000,\n",
        "        nms_thr=0.7,\n",
        "        min_bbox_size=0),\n",
        "    rcnn=dict(\n",
        "        # score_thr=0.05, nms=dict(type='py_cpu_nms_poly_fast', iou_thr=0.1), max_per_img=1000)\n",
        "        score_thr = 0.05, nms = dict(type='py_cpu_nms_poly_fast', iou_thr=0.1), max_per_img = 2000)\n",
        "        # score_thr = 0.001, nms = dict(type='pesudo_nms_poly', iou_thr=0.9), max_per_img = 2000)\n",
        "        # score_thr = 0.001, nms = dict(type='py_cpu_nms_poly_fast', iou_thr=0.1), max_per_img = 2000)\n",
        "\n",
        "# soft-nms is also supported for rcnn testing\n",
        "    # e.g., nms=dict(type='soft_nms', iou_thr=0.5, min_score=0.05)\n",
        ")\n",
        "# dataset settings\n",
        "dataset_type = 'DOTADataset'\n",
        "data_root = 'data/dota1_1024/'\n",
        "img_norm_cfg = dict(\n",
        "    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)\n",
        "data = dict(\n",
        "    imgs_per_gpu=2,\n",
        "    workers_per_gpu=2,\n",
        "    train=dict(\n",
        "        type=dataset_type,\n",
        "        ann_file=data_root + 'trainval1024/DOTA_trainval1024.json',\n",
        "        img_prefix=data_root + 'trainval1024/images/',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0.5,\n",
        "        with_mask=True,\n",
        "        with_crowd=True,\n",
        "        with_label=True),\n",
        "    val=dict(\n",
        "        type=dataset_type,\n",
        "        ann_file=data_root + 'trainval1024/DOTA_trainval1024.json',\n",
        "        img_prefix=data_root + 'trainval1024/images',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0,\n",
        "        with_mask=True,\n",
        "        with_crowd=True,\n",
        "        with_label=True),\n",
        "    test=dict(\n",
        "        type=dataset_type,\n",
        "        ann_file=data_root + 'test1024/DOTA_test1024.json',\n",
        "        img_prefix=data_root + 'test1024/images',\n",
        "        # ann_file=data_root + 'test1024_ms/DOTA_test1024_ms.json',\n",
        "        # img_prefix=data_root + 'test1024_ms/images',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0,\n",
        "        with_mask=False,\n",
        "        with_label=False,\n",
        "        test_mode=True))\n",
        "# optimizer\n",
        "optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)\n",
        "optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))\n",
        "# learning policy\n",
        "lr_config = dict(\n",
        "    policy='step',\n",
        "    warmup='linear',\n",
        "    warmup_iters=500,\n",
        "    warmup_ratio=1.0 / 3,\n",
        "    step=[8, 11])\n",
        "checkpoint_config = dict(interval=12)\n",
        "# yapf:disable\n",
        "log_config = dict(\n",
        "    interval=50,\n",
        "    hooks=[\n",
        "        dict(type='TextLoggerHook'),\n",
        "        # dict(type='TensorboardLoggerHook')\n",
        "    ])\n",
        "# yapf:enable\n",
        "# runtime settings\n",
        "total_epochs = 12\n",
        "dist_params = dict(backend='nccl')\n",
        "log_level = 'INFO'\n",
        "work_dir = './work_dirs/faster_rcnn_RoITrans_r50_fpn_1x_dota'\n",
        "load_from = None\n",
        "resume_from = None\n",
        "workflow = [('train', 1)]"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Overwriting /content/ReDet/configs/DOTA/faster_rcnn_RoITrans_r50_fpn_1x_dota.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IvXb_kMfnSau"
      },
      "source": [
        "faster_rcnn_obb_r50_fpn_1x_dota config"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_HIXmti_nBtI"
      },
      "source": [
        "# %pycat /content/ReDet/configs/DOTA/faster_rcnn_obb_r50_fpn_1x_dota.py\n",
        "%%writefile /content/ReDet/configs/DOTA/faster_rcnn_obb_r50_fpn_1x_dota.py\n",
        "##########این کانفیگ از ریپازیتوری اصلی کپی شده\n",
        "\n",
        "\n",
        "\n",
        "# model settings\n",
        "model = dict(\n",
        "    type='FasterRCNNOBB',\n",
        "    pretrained='modelzoo://resnet50',\n",
        "    backbone=dict(\n",
        "        type='ResNet',\n",
        "        depth=50,\n",
        "        num_stages=4,\n",
        "        out_indices=(0, 1, 2, 3),\n",
        "        frozen_stages=1,\n",
        "        style='pytorch'),\n",
        "    neck=dict(\n",
        "        type='FPN',\n",
        "        in_channels=[256, 512, 1024, 2048],\n",
        "        out_channels=256,\n",
        "        num_outs=5),\n",
        "    rpn_head=dict(\n",
        "        type='RPNHead',\n",
        "        in_channels=256,\n",
        "        feat_channels=256,\n",
        "        anchor_scales=[8],\n",
        "        anchor_ratios=[0.5, 1.0, 2.0],\n",
        "        anchor_strides=[4, 8, 16, 32, 64],\n",
        "        target_means=[.0, .0, .0, .0],\n",
        "        target_stds=[1.0, 1.0, 1.0, 1.0],\n",
        "        loss_cls=dict(\n",
        "            type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0),\n",
        "        loss_bbox=dict(type='SmoothL1Loss', beta=1.0 / 9.0, loss_weight=1.0)),\n",
        "    bbox_roi_extractor=dict(\n",
        "        type='SingleRoIExtractor',\n",
        "        roi_layer=dict(type='RoIAlign', out_size=7, sample_num=2),\n",
        "        out_channels=256,\n",
        "        featmap_strides=[4, 8, 16, 32]),\n",
        "    bbox_head=dict(\n",
        "        type='SharedFCBBoxHeadRbbox',\n",
        "        num_fcs=2,\n",
        "        in_channels=256,\n",
        "        fc_out_channels=1024,\n",
        "        roi_feat_size=7,\n",
        "        num_classes=16,\n",
        "        target_means=[0., 0., 0., 0., 0.],\n",
        "        target_stds=[0.1, 0.1, 0.2, 0.2, 0.1],\n",
        "        reg_class_agnostic=False,\n",
        "        with_module=False,\n",
        "        hbb_trans='hbbpolyobb',\n",
        "        loss_cls=dict(\n",
        "            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),\n",
        "        loss_bbox=dict(type='SmoothL1Loss', beta=1.0, loss_weight=1.0)))\n",
        "# model training and testing settings\n",
        "train_cfg = dict(\n",
        "    rpn=dict(\n",
        "        assigner=dict(\n",
        "            type='MaxIoUAssignerCy',\n",
        "            pos_iou_thr=0.7,\n",
        "            neg_iou_thr=0.3,\n",
        "            min_pos_iou=0.3,\n",
        "            ignore_iof_thr=-1),\n",
        "        sampler=dict(\n",
        "            type='RandomSampler',\n",
        "            num=256,\n",
        "            pos_fraction=0.5,\n",
        "            neg_pos_ub=-1,\n",
        "            add_gt_as_proposals=False),\n",
        "        allowed_border=0,\n",
        "        pos_weight=-1,\n",
        "        debug=False),\n",
        "    rpn_proposal=dict(\n",
        "        nms_across_levels=False,\n",
        "        nms_pre=2000,\n",
        "        nms_post=2000,\n",
        "        max_num=2000,\n",
        "        nms_thr=0.7,\n",
        "        min_bbox_size=0),\n",
        "    rcnn=dict(\n",
        "        assigner=dict(\n",
        "            type='MaxIoUAssignerCy',\n",
        "            pos_iou_thr=0.5,\n",
        "            neg_iou_thr=0.5,\n",
        "            min_pos_iou=0.5,\n",
        "            ignore_iof_thr=-1),\n",
        "        sampler=dict(\n",
        "            type='RandomSampler',\n",
        "            num=512,\n",
        "            pos_fraction=0.25,\n",
        "            neg_pos_ub=-1,\n",
        "            add_gt_as_proposals=True),\n",
        "        pos_weight=-1,\n",
        "        debug=False))\n",
        "test_cfg = dict(\n",
        "    rpn=dict(\n",
        "        nms_across_levels=False,\n",
        "        nms_pre=2000,\n",
        "        nms_post=2000,\n",
        "        max_num=2000,\n",
        "        nms_thr=0.7,\n",
        "        min_bbox_size=0),\n",
        "    rcnn=dict(\n",
        "        # score_thr=0.05, nms=dict(type='py_cpu_nms_poly_fast', iou_thr=0.1), max_per_img=1000)\n",
        "    score_thr = 0.05, nms = dict(type='py_cpu_nms_poly_fast', iou_thr=0.1), max_per_img = 2000)\n",
        "# soft-nms is also supported for rcnn testing\n",
        "    # e.g., nms=dict(type='soft_nms', iou_thr=0.5, min_score=0.05)\n",
        ")\n",
        "# dataset settings\n",
        "dataset_type = 'DOTADataset'\n",
        "data_root = 'data/dota1_1024/'\n",
        "img_norm_cfg = dict(\n",
        "    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)\n",
        "data = dict(\n",
        "    imgs_per_gpu=2,\n",
        "    workers_per_gpu=2,\n",
        "    train=dict(\n",
        "        type=dataset_type,\n",
        "        ann_file=data_root + 'trainval1024/DOTA_trainval1024.json',\n",
        "        img_prefix=data_root + 'trainval1024/images/',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0.5,\n",
        "        with_mask=True,\n",
        "        with_crowd=True,\n",
        "        with_label=True),\n",
        "    val=dict(\n",
        "        type=dataset_type,\n",
        "        ann_file=data_root + 'trainval1024/DOTA_trainval1024.json',\n",
        "        img_prefix=data_root + 'trainval1024/images',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0,\n",
        "        with_mask=True,\n",
        "        with_crowd=True,\n",
        "        with_label=True),\n",
        "    test=dict(\n",
        "        type=dataset_type,\n",
        "        ann_file=data_root + 'test1024/DOTA_test1024.json',\n",
        "        img_prefix=data_root + 'test1024/images',\n",
        "        img_scale=(1024, 1024),\n",
        "        img_norm_cfg=img_norm_cfg,\n",
        "        size_divisor=32,\n",
        "        flip_ratio=0,\n",
        "        with_mask=False,\n",
        "        with_label=False,\n",
        "        test_mode=True))\n",
        "# optimizer\n",
        "optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)\n",
        "optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))\n",
        "# learning policy\n",
        "lr_config = dict(\n",
        "    policy='step',\n",
        "    warmup='linear',\n",
        "    warmup_iters=500,\n",
        "    warmup_ratio=1.0 / 3,\n",
        "    step=[8, 11])\n",
        "checkpoint_config = dict(interval=12)\n",
        "# yapf:disable\n",
        "log_config = dict(\n",
        "    interval=50,\n",
        "    hooks=[\n",
        "        dict(type='TextLoggerHook'),\n",
        "        # dict(type='TensorboardLoggerHook')\n",
        "    ])\n",
        "# yapf:enable\n",
        "# runtime settings\n",
        "total_epochs = 12\n",
        "dist_params = dict(backend='nccl')\n",
        "log_level = 'INFO'\n",
        "work_dir = './work_dirs/faster_rcnn_obb_r50_fpn_1x_dota'\n",
        "load_from = None\n",
        "resume_from = None\n",
        "workflow = [('train', 1)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pT6DVa5zptwp"
      },
      "source": [
        "# آموزش شبکه"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qc9KlcGVRbSA",
        "outputId": "fe2c1580-bbfc-4530-d490-b9fe7f44f15c"
      },
      "source": [
        "!python tools/train.py /content/AerialDetection/configs/DOTA/faster_rcnn_obb_r50_fpn_1x_dota.py --resume_from /content/AerialDetection/work_dirs/faster_rcnn_obb_r50_fpn_1x_dota/epoch_11.pth"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2021-07-26 16:52:03,055 - INFO - Distributed training: False\n",
            "2021-07-26 16:52:03,475 - INFO - load model from: modelzoo://resnet50\n",
            "/usr/local/lib/python3.7/dist-packages/mmcv/runner/checkpoint.py:145: UserWarning: The URL scheme of \"modelzoo://\" is deprecated, please use \"torchvision://\" instead\n",
            "  warnings.warn('The URL scheme of \"modelzoo://\" is deprecated, please '\n",
            "Downloading: \"https://download.pytorch.org/models/resnet50-19c8e357.pth\" to /root/.cache/torch/checkpoints/resnet50-19c8e357.pth\n",
            "100% 102502400/102502400 [00:00<00:00, 124710824.68it/s]\n",
            "2021-07-26 16:52:04,672 - WARNING - The model and loaded state dict do not match exactly\n",
            "\n",
            "unexpected key in source state_dict: fc.weight, fc.bias\n",
            "\n",
            "loading annotations into memory...\n",
            "Done (t=2.99s)\n",
            "creating index...\n",
            "index created!\n",
            "2021-07-26 16:52:13,376 - INFO - load checkpoint from /content/AerialDetection/work_dirs/faster_rcnn_obb_r50_fpn_1x_dota/epoch_11.pth\n",
            "2021-07-26 16:52:18,657 - INFO - resumed epoch 11, iter 74569\n",
            "2021-07-26 16:52:18,660 - INFO - Start running, host: root@7b63d77060d2, work_dir: /content/AerialDetection/work_dirs/faster_rcnn_obb_r50_fpn_1x_dota\n",
            "2021-07-26 16:52:18,661 - INFO - workflow: [('train', 1)], max: 12 epochs\n",
            "THCudaCheck FAIL file=/pytorch/aten/src/THC/THCGeneral.cpp line=383 error=11 : invalid argument\n",
            "2021-07-26 16:53:18,087 - INFO - Epoch [12][50/6779]\tlr: 0.00010, eta: 2:13:16, time: 1.188, data_time: 0.195, memory: 3701, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0154, rbbox_loss_cls: 0.0943, rbbox_acc: 96.3125, rbbox_loss_bbox: 0.1548, loss: 0.2756\n",
            "2021-07-26 16:54:05,772 - INFO - Epoch [12][100/6779]\tlr: 0.00010, eta: 1:59:13, time: 0.954, data_time: 0.078, memory: 3701, loss_rpn_cls: 0.0076, loss_rpn_bbox: 0.0118, rbbox_loss_cls: 0.0816, rbbox_acc: 96.9141, rbbox_loss_bbox: 0.1007, loss: 0.2018\n",
            "2021-07-26 16:54:54,656 - INFO - Epoch [12][150/6779]\tlr: 0.00010, eta: 1:54:53, time: 0.978, data_time: 0.068, memory: 3701, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0171, rbbox_loss_cls: 0.1139, rbbox_acc: 95.6582, rbbox_loss_bbox: 0.1421, loss: 0.2845\n",
            "2021-07-26 16:55:43,358 - INFO - Epoch [12][200/6779]\tlr: 0.00010, eta: 1:52:13, time: 0.974, data_time: 0.072, memory: 3701, loss_rpn_cls: 0.0075, loss_rpn_bbox: 0.0132, rbbox_loss_cls: 0.0820, rbbox_acc: 96.7188, rbbox_loss_bbox: 0.1265, loss: 0.2292\n",
            "2021-07-26 16:56:31,767 - INFO - Epoch [12][250/6779]\tlr: 0.00010, eta: 1:50:09, time: 0.968, data_time: 0.070, memory: 3701, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0161, rbbox_loss_cls: 0.0939, rbbox_acc: 96.4590, rbbox_loss_bbox: 0.1369, loss: 0.2587\n",
            "2021-07-26 16:57:24,467 - INFO - Epoch [12][300/6779]\tlr: 0.00010, eta: 1:50:04, time: 1.054, data_time: 0.089, memory: 3701, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0215, rbbox_loss_cls: 0.1079, rbbox_acc: 95.8398, rbbox_loss_bbox: 0.1534, loss: 0.2944\n",
            "2021-07-26 16:58:16,904 - INFO - Epoch [12][350/6779]\tlr: 0.00010, eta: 1:49:40, time: 1.049, data_time: 0.123, memory: 3701, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0182, rbbox_loss_cls: 0.0927, rbbox_acc: 96.5332, rbbox_loss_bbox: 0.1316, loss: 0.2532\n",
            "2021-07-26 16:59:07,581 - INFO - Epoch [12][400/6779]\tlr: 0.00010, eta: 1:48:41, time: 1.014, data_time: 0.087, memory: 3701, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0176, rbbox_loss_cls: 0.0971, rbbox_acc: 96.1953, rbbox_loss_bbox: 0.1277, loss: 0.2515\n",
            "2021-07-26 17:00:04,691 - INFO - Epoch [12][450/6779]\tlr: 0.00010, eta: 1:49:14, time: 1.142, data_time: 0.179, memory: 3851, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0174, rbbox_loss_cls: 0.0917, rbbox_acc: 96.3984, rbbox_loss_bbox: 0.1555, loss: 0.2737\n",
            "2021-07-26 17:00:54,558 - INFO - Epoch [12][500/6779]\tlr: 0.00010, eta: 1:47:58, time: 0.997, data_time: 0.087, memory: 3851, loss_rpn_cls: 0.0081, loss_rpn_bbox: 0.0137, rbbox_loss_cls: 0.0876, rbbox_acc: 96.7441, rbbox_loss_bbox: 0.1240, loss: 0.2334\n",
            "2021-07-26 17:01:54,477 - INFO - Epoch [12][550/6779]\tlr: 0.00010, eta: 1:48:41, time: 1.198, data_time: 0.201, memory: 3851, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0155, rbbox_loss_cls: 0.0925, rbbox_acc: 96.4727, rbbox_loss_bbox: 0.1444, loss: 0.2635\n",
            "2021-07-26 17:02:45,037 - INFO - Epoch [12][600/6779]\tlr: 0.00010, eta: 1:47:30, time: 1.011, data_time: 0.092, memory: 3851, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0172, rbbox_loss_cls: 0.0996, rbbox_acc: 96.0527, rbbox_loss_bbox: 0.1410, loss: 0.2693\n",
            "2021-07-26 17:03:38,023 - INFO - Epoch [12][650/6779]\tlr: 0.00010, eta: 1:46:45, time: 1.060, data_time: 0.127, memory: 3851, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0176, rbbox_loss_cls: 0.0857, rbbox_acc: 96.5938, rbbox_loss_bbox: 0.1486, loss: 0.2622\n",
            "2021-07-26 17:04:34,395 - INFO - Epoch [12][700/6779]\tlr: 0.00010, eta: 1:46:29, time: 1.128, data_time: 0.144, memory: 3851, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0170, rbbox_loss_cls: 0.0926, rbbox_acc: 96.2383, rbbox_loss_bbox: 0.1282, loss: 0.2493\n",
            "2021-07-26 17:05:24,169 - INFO - Epoch [12][750/6779]\tlr: 0.00010, eta: 1:45:14, time: 0.995, data_time: 0.086, memory: 3851, loss_rpn_cls: 0.0103, loss_rpn_bbox: 0.0167, rbbox_loss_cls: 0.0970, rbbox_acc: 96.1895, rbbox_loss_bbox: 0.1563, loss: 0.2803\n",
            "2021-07-26 17:06:16,066 - INFO - Epoch [12][800/6779]\tlr: 0.00010, eta: 1:44:18, time: 1.038, data_time: 0.102, memory: 3851, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0159, rbbox_loss_cls: 0.0934, rbbox_acc: 96.2773, rbbox_loss_bbox: 0.1372, loss: 0.2581\n",
            "2021-07-26 17:07:11,751 - INFO - Epoch [12][850/6779]\tlr: 0.00010, eta: 1:43:49, time: 1.114, data_time: 0.152, memory: 3851, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0162, rbbox_loss_cls: 0.0865, rbbox_acc: 96.5645, rbbox_loss_bbox: 0.1238, loss: 0.2364\n",
            "2021-07-26 17:08:08,708 - INFO - Epoch [12][900/6779]\tlr: 0.00010, eta: 1:43:25, time: 1.139, data_time: 0.165, memory: 3851, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0163, rbbox_loss_cls: 0.0932, rbbox_acc: 96.3379, rbbox_loss_bbox: 0.1316, loss: 0.2515\n",
            "2021-07-26 17:09:04,779 - INFO - Epoch [12][950/6779]\tlr: 0.00010, eta: 1:42:53, time: 1.121, data_time: 0.130, memory: 3851, loss_rpn_cls: 0.0158, loss_rpn_bbox: 0.0170, rbbox_loss_cls: 0.1148, rbbox_acc: 95.7559, rbbox_loss_bbox: 0.1252, loss: 0.2729\n",
            "2021-07-26 17:09:53,638 - INFO - Epoch [12][1000/6779]\tlr: 0.00010, eta: 1:41:36, time: 0.977, data_time: 0.080, memory: 3851, loss_rpn_cls: 0.0080, loss_rpn_bbox: 0.0160, rbbox_loss_cls: 0.0918, rbbox_acc: 96.4023, rbbox_loss_bbox: 0.1071, loss: 0.2229\n",
            "2021-07-26 17:10:49,303 - INFO - Epoch [12][1050/6779]\tlr: 0.00010, eta: 1:40:59, time: 1.113, data_time: 0.159, memory: 3851, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0156, rbbox_loss_cls: 0.0928, rbbox_acc: 96.3691, rbbox_loss_bbox: 0.1137, loss: 0.2325\n",
            "2021-07-26 17:11:50,082 - INFO - Epoch [12][1100/6779]\tlr: 0.00010, eta: 1:40:47, time: 1.216, data_time: 0.212, memory: 3851, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0203, rbbox_loss_cls: 0.1111, rbbox_acc: 95.6016, rbbox_loss_bbox: 0.1449, loss: 0.2894\n",
            "2021-07-26 17:12:46,825 - INFO - Epoch [12][1150/6779]\tlr: 0.00010, eta: 1:40:11, time: 1.135, data_time: 0.175, memory: 3851, loss_rpn_cls: 0.0131, loss_rpn_bbox: 0.0168, rbbox_loss_cls: 0.1006, rbbox_acc: 96.1191, rbbox_loss_bbox: 0.1204, loss: 0.2509\n",
            "2021-07-26 17:13:42,049 - INFO - Epoch [12][1200/6779]\tlr: 0.00010, eta: 1:39:26, time: 1.105, data_time: 0.154, memory: 3851, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0156, rbbox_loss_cls: 0.1035, rbbox_acc: 95.9316, rbbox_loss_bbox: 0.1447, loss: 0.2756\n",
            "2021-07-26 17:14:38,956 - INFO - Epoch [12][1250/6779]\tlr: 0.00010, eta: 1:38:48, time: 1.138, data_time: 0.210, memory: 3867, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0173, rbbox_loss_cls: 0.0887, rbbox_acc: 96.5645, rbbox_loss_bbox: 0.1268, loss: 0.2453\n",
            "2021-07-26 17:15:30,588 - INFO - Epoch [12][1300/6779]\tlr: 0.00010, eta: 1:37:46, time: 1.033, data_time: 0.097, memory: 3867, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0199, rbbox_loss_cls: 0.1077, rbbox_acc: 95.7090, rbbox_loss_bbox: 0.1527, loss: 0.2930\n",
            "2021-07-26 17:16:24,227 - INFO - Epoch [12][1350/6779]\tlr: 0.00010, eta: 1:36:53, time: 1.073, data_time: 0.116, memory: 3867, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0171, rbbox_loss_cls: 0.0973, rbbox_acc: 96.1602, rbbox_loss_bbox: 0.1438, loss: 0.2671\n",
            "2021-07-26 17:17:18,218 - INFO - Epoch [12][1400/6779]\tlr: 0.00010, eta: 1:36:01, time: 1.080, data_time: 0.142, memory: 3867, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0151, rbbox_loss_cls: 0.0944, rbbox_acc: 96.2266, rbbox_loss_bbox: 0.1491, loss: 0.2691\n",
            "2021-07-26 17:18:08,125 - INFO - Epoch [12][1450/6779]\tlr: 0.00010, eta: 1:34:54, time: 0.998, data_time: 0.099, memory: 3867, loss_rpn_cls: 0.0067, loss_rpn_bbox: 0.0149, rbbox_loss_cls: 0.0859, rbbox_acc: 96.6230, rbbox_loss_bbox: 0.1216, loss: 0.2291\n",
            "2021-07-26 17:19:01,904 - INFO - Epoch [12][1500/6779]\tlr: 0.00010, eta: 1:34:02, time: 1.076, data_time: 0.127, memory: 3867, loss_rpn_cls: 0.0134, loss_rpn_bbox: 0.0187, rbbox_loss_cls: 0.1063, rbbox_acc: 95.6738, rbbox_loss_bbox: 0.1385, loss: 0.2768\n",
            "2021-07-26 17:19:58,218 - INFO - Epoch [12][1550/6779]\tlr: 0.00010, eta: 1:33:18, time: 1.126, data_time: 0.143, memory: 3867, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0174, rbbox_loss_cls: 0.1057, rbbox_acc: 95.8730, rbbox_loss_bbox: 0.1740, loss: 0.3071\n",
            "2021-07-26 17:20:54,207 - INFO - Epoch [12][1600/6779]\tlr: 0.00010, eta: 1:32:32, time: 1.120, data_time: 0.173, memory: 3867, loss_rpn_cls: 0.0083, loss_rpn_bbox: 0.0145, rbbox_loss_cls: 0.0852, rbbox_acc: 96.6680, rbbox_loss_bbox: 0.1104, loss: 0.2183\n",
            "2021-07-26 17:21:54,043 - INFO - Epoch [12][1650/6779]\tlr: 0.00010, eta: 1:31:58, time: 1.197, data_time: 0.235, memory: 3867, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0164, rbbox_loss_cls: 0.0819, rbbox_acc: 96.7129, rbbox_loss_bbox: 0.1430, loss: 0.2503\n",
            "2021-07-26 17:22:50,219 - INFO - Epoch [12][1700/6779]\tlr: 0.00010, eta: 1:31:11, time: 1.124, data_time: 0.129, memory: 3867, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0208, rbbox_loss_cls: 0.1017, rbbox_acc: 95.9297, rbbox_loss_bbox: 0.1399, loss: 0.2732\n",
            "2021-07-26 17:23:45,352 - INFO - Epoch [12][1750/6779]\tlr: 0.00010, eta: 1:30:21, time: 1.102, data_time: 0.133, memory: 3867, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0180, rbbox_loss_cls: 0.1026, rbbox_acc: 96.1562, rbbox_loss_bbox: 0.1414, loss: 0.2757\n",
            "2021-07-26 17:24:36,130 - INFO - Epoch [12][1800/6779]\tlr: 0.00010, eta: 1:29:19, time: 1.016, data_time: 0.079, memory: 3867, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0195, rbbox_loss_cls: 0.1029, rbbox_acc: 95.8008, rbbox_loss_bbox: 0.1509, loss: 0.2854\n",
            "2021-07-26 17:25:29,176 - INFO - Epoch [12][1850/6779]\tlr: 0.00010, eta: 1:28:23, time: 1.061, data_time: 0.138, memory: 3867, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0176, rbbox_loss_cls: 0.0931, rbbox_acc: 96.3184, rbbox_loss_bbox: 0.1108, loss: 0.2327\n",
            "2021-07-26 17:26:25,152 - INFO - Epoch [12][1900/6779]\tlr: 0.00010, eta: 1:27:35, time: 1.119, data_time: 0.163, memory: 3867, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0155, rbbox_loss_cls: 0.0903, rbbox_acc: 96.4199, rbbox_loss_bbox: 0.1372, loss: 0.2529\n",
            "2021-07-26 17:27:22,865 - INFO - Epoch [12][1950/6779]\tlr: 0.00010, eta: 1:26:50, time: 1.154, data_time: 0.128, memory: 3867, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0227, rbbox_loss_cls: 0.0982, rbbox_acc: 96.1406, rbbox_loss_bbox: 0.1685, loss: 0.3006\n",
            "2021-07-26 17:28:15,155 - INFO - Epoch [12][2000/6779]\tlr: 0.00010, eta: 1:25:52, time: 1.046, data_time: 0.099, memory: 3867, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0193, rbbox_loss_cls: 0.1013, rbbox_acc: 95.9102, rbbox_loss_bbox: 0.1602, loss: 0.2905\n",
            "tcmalloc: large alloc 1172406272 bytes == 0x563e2a1b4000 @  0x7fd40a441001 0x7fd407fbf54f 0x7fd40800fb58 0x7fd408013b17 0x7fd4080b2203 0x563d7d90b338 0x7fd3a6810b3e 0x7fd3a6811752 0x563d7d9ca010 0x563d7d9c9da0 0x563d7da3dbb3 0x563d7d9cb65a 0x563d7da39b0e 0x563d7da38c35 0x563d7d9cb73a 0x563d7da39d67 0x563d7d9cb65a 0x563d7da39b0e 0x563d7da38c35 0x563d7d9ca51e 0x563d7db3b539 0x563d7d9ca2bf 0x563d7da374c1 0x563d7dab198c 0x563d7da3f40c 0x563d7da38c35 0x563d7d9cb73a 0x563d7da3a93b 0x563d7da38c35 0x563d7d9cb73a 0x563d7da3a93b\n",
            "2021-07-26 17:29:18,704 - INFO - Epoch [12][2050/6779]\tlr: 0.00010, eta: 1:25:21, time: 1.271, data_time: 0.300, memory: 4067, loss_rpn_cls: 0.0121, loss_rpn_bbox: 0.0195, rbbox_loss_cls: 0.0987, rbbox_acc: 96.1055, rbbox_loss_bbox: 0.1488, loss: 0.2790\n",
            "2021-07-26 17:30:15,026 - INFO - Epoch [12][2100/6779]\tlr: 0.00010, eta: 1:24:31, time: 1.126, data_time: 0.181, memory: 4067, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0171, rbbox_loss_cls: 0.0846, rbbox_acc: 96.6699, rbbox_loss_bbox: 0.1246, loss: 0.2356\n",
            "2021-07-26 17:31:08,794 - INFO - Epoch [12][2150/6779]\tlr: 0.00010, eta: 1:23:36, time: 1.075, data_time: 0.101, memory: 4067, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0175, rbbox_loss_cls: 0.0978, rbbox_acc: 96.0273, rbbox_loss_bbox: 0.1211, loss: 0.2469\n",
            "2021-07-26 17:32:03,184 - INFO - Epoch [12][2200/6779]\tlr: 0.00010, eta: 1:22:42, time: 1.088, data_time: 0.123, memory: 4067, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0151, rbbox_loss_cls: 0.0939, rbbox_acc: 96.2715, rbbox_loss_bbox: 0.1505, loss: 0.2691\n",
            "2021-07-26 17:33:01,066 - INFO - Epoch [12][2250/6779]\tlr: 0.00010, eta: 1:21:56, time: 1.158, data_time: 0.177, memory: 4067, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0157, rbbox_loss_cls: 0.0915, rbbox_acc: 96.3945, rbbox_loss_bbox: 0.1402, loss: 0.2590\n",
            "2021-07-26 17:34:06,289 - INFO - Epoch [12][2300/6779]\tlr: 0.00010, eta: 1:21:23, time: 1.304, data_time: 0.325, memory: 4082, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0145, rbbox_loss_cls: 0.0875, rbbox_acc: 96.7188, rbbox_loss_bbox: 0.1315, loss: 0.2442\n",
            "2021-07-26 17:35:01,929 - INFO - Epoch [12][2350/6779]\tlr: 0.00010, eta: 1:20:30, time: 1.113, data_time: 0.120, memory: 4082, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0171, rbbox_loss_cls: 0.0947, rbbox_acc: 96.2207, rbbox_loss_bbox: 0.1248, loss: 0.2491\n",
            "2021-07-26 17:35:58,726 - INFO - Epoch [12][2400/6779]\tlr: 0.00010, eta: 1:19:40, time: 1.136, data_time: 0.175, memory: 4082, loss_rpn_cls: 0.0079, loss_rpn_bbox: 0.0150, rbbox_loss_cls: 0.0858, rbbox_acc: 96.5703, rbbox_loss_bbox: 0.1341, loss: 0.2428\n",
            "2021-07-26 17:36:57,143 - INFO - Epoch [12][2450/6779]\tlr: 0.00010, eta: 1:18:52, time: 1.168, data_time: 0.205, memory: 4082, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0187, rbbox_loss_cls: 0.0992, rbbox_acc: 96.0781, rbbox_loss_bbox: 0.1517, loss: 0.2812\n",
            "2021-07-26 17:37:47,976 - INFO - Epoch [12][2500/6779]\tlr: 0.00010, eta: 1:17:51, time: 1.017, data_time: 0.113, memory: 4082, loss_rpn_cls: 0.0125, loss_rpn_bbox: 0.0171, rbbox_loss_cls: 0.0912, rbbox_acc: 96.4980, rbbox_loss_bbox: 0.1150, loss: 0.2357\n",
            "2021-07-26 17:38:43,914 - INFO - Epoch [12][2550/6779]\tlr: 0.00010, eta: 1:16:59, time: 1.119, data_time: 0.144, memory: 4082, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0168, rbbox_loss_cls: 0.0909, rbbox_acc: 96.3320, rbbox_loss_bbox: 0.1190, loss: 0.2371\n",
            "2021-07-26 17:39:35,358 - INFO - Epoch [12][2600/6779]\tlr: 0.00010, eta: 1:15:59, time: 1.029, data_time: 0.116, memory: 4082, loss_rpn_cls: 0.0079, loss_rpn_bbox: 0.0128, rbbox_loss_cls: 0.0797, rbbox_acc: 96.8691, rbbox_loss_bbox: 0.1019, loss: 0.2023\n",
            "2021-07-26 17:40:30,055 - INFO - Epoch [12][2650/6779]\tlr: 0.00010, eta: 1:15:05, time: 1.094, data_time: 0.117, memory: 4082, loss_rpn_cls: 0.0084, loss_rpn_bbox: 0.0177, rbbox_loss_cls: 0.0967, rbbox_acc: 96.1680, rbbox_loss_bbox: 0.1362, loss: 0.2590\n",
            "2021-07-26 17:41:20,960 - INFO - Epoch [12][2700/6779]\tlr: 0.00010, eta: 1:14:04, time: 1.018, data_time: 0.084, memory: 4082, loss_rpn_cls: 0.0076, loss_rpn_bbox: 0.0127, rbbox_loss_cls: 0.0966, rbbox_acc: 96.3398, rbbox_loss_bbox: 0.1261, loss: 0.2430\n",
            "2021-07-26 17:42:16,044 - INFO - Epoch [12][2750/6779]\tlr: 0.00010, eta: 1:13:11, time: 1.102, data_time: 0.128, memory: 4082, loss_rpn_cls: 0.0112, loss_rpn_bbox: 0.0177, rbbox_loss_cls: 0.1029, rbbox_acc: 96.0195, rbbox_loss_bbox: 0.1285, loss: 0.2603\n",
            "2021-07-26 17:43:12,249 - INFO - Epoch [12][2800/6779]\tlr: 0.00010, eta: 1:12:19, time: 1.124, data_time: 0.115, memory: 4082, loss_rpn_cls: 0.0147, loss_rpn_bbox: 0.0197, rbbox_loss_cls: 0.1129, rbbox_acc: 95.5156, rbbox_loss_bbox: 0.1363, loss: 0.2835\n",
            "2021-07-26 17:44:13,329 - INFO - Epoch [12][2850/6779]\tlr: 0.00010, eta: 1:11:33, time: 1.222, data_time: 0.242, memory: 4082, loss_rpn_cls: 0.0107, loss_rpn_bbox: 0.0177, rbbox_loss_cls: 0.0939, rbbox_acc: 96.4570, rbbox_loss_bbox: 0.1241, loss: 0.2465\n",
            "2021-07-26 17:45:05,642 - INFO - Epoch [12][2900/6779]\tlr: 0.00010, eta: 1:10:36, time: 1.046, data_time: 0.100, memory: 4082, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0185, rbbox_loss_cls: 0.0958, rbbox_acc: 96.2461, rbbox_loss_bbox: 0.1681, loss: 0.2920\n",
            "2021-07-26 17:46:06,235 - INFO - Epoch [12][2950/6779]\tlr: 0.00010, eta: 1:09:49, time: 1.212, data_time: 0.205, memory: 4082, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0190, rbbox_loss_cls: 0.0960, rbbox_acc: 96.2305, rbbox_loss_bbox: 0.1351, loss: 0.2618\n",
            "2021-07-26 17:47:00,317 - INFO - Epoch [12][3000/6779]\tlr: 0.00010, eta: 1:08:53, time: 1.082, data_time: 0.121, memory: 4082, loss_rpn_cls: 0.0118, loss_rpn_bbox: 0.0174, rbbox_loss_cls: 0.1065, rbbox_acc: 95.7793, rbbox_loss_bbox: 0.1167, loss: 0.2522\n",
            "2021-07-26 17:47:55,448 - INFO - Epoch [12][3050/6779]\tlr: 0.00010, eta: 1:07:59, time: 1.103, data_time: 0.118, memory: 4082, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0168, rbbox_loss_cls: 0.1016, rbbox_acc: 95.9219, rbbox_loss_bbox: 0.1290, loss: 0.2602\n",
            "2021-07-26 17:48:48,785 - INFO - Epoch [12][3100/6779]\tlr: 0.00010, eta: 1:07:03, time: 1.067, data_time: 0.114, memory: 4082, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0168, rbbox_loss_cls: 0.0965, rbbox_acc: 96.2812, rbbox_loss_bbox: 0.1277, loss: 0.2532\n",
            "2021-07-26 17:49:47,465 - INFO - Epoch [12][3150/6779]\tlr: 0.00010, eta: 1:06:13, time: 1.174, data_time: 0.215, memory: 4082, loss_rpn_cls: 0.0095, loss_rpn_bbox: 0.0149, rbbox_loss_cls: 0.0847, rbbox_acc: 96.7695, rbbox_loss_bbox: 0.1287, loss: 0.2378\n",
            "tcmalloc: large alloc 1280540672 bytes == 0x563e2a0b2000 @  0x7fd40a441001 0x7fd407fbf54f 0x7fd40800fb58 0x7fd408013b17 0x7fd4080b2203 0x563d7d90b338 0x7fd3a6810b3e 0x7fd3a6811752 0x563d7d9ca010 0x563d7d9c9da0 0x563d7da3dbb3 0x563d7d9cb65a 0x563d7da39b0e 0x563d7da38c35 0x563d7d9cb73a 0x563d7da39d67 0x563d7d9cb65a 0x563d7da39b0e 0x563d7da38c35 0x563d7d9ca51e 0x563d7db3b539 0x563d7d9ca2bf 0x563d7da374c1 0x563d7dab1a2a 0x563d7da3f40c 0x563d7da38c35 0x563d7d9cb73a 0x563d7da3a93b 0x563d7da38c35 0x563d7d9cb73a 0x563d7da3a93b\n",
            "2021-07-26 17:50:54,444 - INFO - Epoch [12][3200/6779]\tlr: 0.00010, eta: 1:05:32, time: 1.340, data_time: 0.337, memory: 4182, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0167, rbbox_loss_cls: 0.0903, rbbox_acc: 96.3750, rbbox_loss_bbox: 0.1409, loss: 0.2579\n",
            "2021-07-26 17:51:49,138 - INFO - Epoch [12][3250/6779]\tlr: 0.00010, eta: 1:04:36, time: 1.094, data_time: 0.110, memory: 4182, loss_rpn_cls: 0.0080, loss_rpn_bbox: 0.0197, rbbox_loss_cls: 0.0909, rbbox_acc: 96.4023, rbbox_loss_bbox: 0.1223, loss: 0.2409\n",
            "2021-07-26 17:52:46,000 - INFO - Epoch [12][3300/6779]\tlr: 0.00010, eta: 1:03:44, time: 1.137, data_time: 0.156, memory: 4182, loss_rpn_cls: 0.0088, loss_rpn_bbox: 0.0174, rbbox_loss_cls: 0.0946, rbbox_acc: 96.3340, rbbox_loss_bbox: 0.1063, loss: 0.2272\n",
            "2021-07-26 17:53:46,473 - INFO - Epoch [12][3350/6779]\tlr: 0.00010, eta: 1:02:54, time: 1.209, data_time: 0.168, memory: 4182, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0225, rbbox_loss_cls: 0.1114, rbbox_acc: 95.6816, rbbox_loss_bbox: 0.1419, loss: 0.2887\n",
            "2021-07-26 17:54:44,501 - INFO - Epoch [12][3400/6779]\tlr: 0.00010, eta: 1:02:02, time: 1.161, data_time: 0.154, memory: 4182, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0203, rbbox_loss_cls: 0.0940, rbbox_acc: 96.2910, rbbox_loss_bbox: 0.1429, loss: 0.2672\n",
            "2021-07-26 17:55:51,987 - INFO - Epoch [12][3450/6779]\tlr: 0.00010, eta: 1:01:19, time: 1.350, data_time: 0.370, memory: 4182, loss_rpn_cls: 0.0109, loss_rpn_bbox: 0.0141, rbbox_loss_cls: 0.0981, rbbox_acc: 96.2969, rbbox_loss_bbox: 0.1460, loss: 0.2691\n",
            "2021-07-26 17:56:55,732 - INFO - Epoch [12][3500/6779]\tlr: 0.00010, eta: 1:00:32, time: 1.275, data_time: 0.225, memory: 4182, loss_rpn_cls: 0.0146, loss_rpn_bbox: 0.0208, rbbox_loss_cls: 0.1090, rbbox_acc: 95.6602, rbbox_loss_bbox: 0.1430, loss: 0.2874\n",
            "2021-07-26 17:57:50,207 - INFO - Epoch [12][3550/6779]\tlr: 0.00010, eta: 0:59:35, time: 1.089, data_time: 0.099, memory: 4182, loss_rpn_cls: 0.0137, loss_rpn_bbox: 0.0180, rbbox_loss_cls: 0.1024, rbbox_acc: 95.9434, rbbox_loss_bbox: 0.1265, loss: 0.2605\n",
            "2021-07-26 17:58:47,581 - INFO - Epoch [12][3600/6779]\tlr: 0.00010, eta: 0:58:42, time: 1.147, data_time: 0.151, memory: 4182, loss_rpn_cls: 0.0143, loss_rpn_bbox: 0.0196, rbbox_loss_cls: 0.1075, rbbox_acc: 95.9414, rbbox_loss_bbox: 0.1766, loss: 0.3180\n",
            "2021-07-26 17:59:55,848 - INFO - Epoch [12][3650/6779]\tlr: 0.00010, eta: 0:57:58, time: 1.365, data_time: 0.292, memory: 4182, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0179, rbbox_loss_cls: 0.0966, rbbox_acc: 96.2500, rbbox_loss_bbox: 0.1520, loss: 0.2779\n",
            "2021-07-26 18:00:49,646 - INFO - Epoch [12][3700/6779]\tlr: 0.00010, eta: 0:57:00, time: 1.076, data_time: 0.110, memory: 4182, loss_rpn_cls: 0.0156, loss_rpn_bbox: 0.0192, rbbox_loss_cls: 0.0997, rbbox_acc: 96.0801, rbbox_loss_bbox: 0.1633, loss: 0.2979\n",
            "2021-07-26 18:01:45,130 - INFO - Epoch [12][3750/6779]\tlr: 0.00010, eta: 0:56:05, time: 1.110, data_time: 0.121, memory: 4182, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0177, rbbox_loss_cls: 0.1037, rbbox_acc: 96.0254, rbbox_loss_bbox: 0.1357, loss: 0.2671\n",
            "2021-07-26 18:02:38,729 - INFO - Epoch [12][3800/6779]\tlr: 0.00010, eta: 0:55:08, time: 1.072, data_time: 0.126, memory: 4182, loss_rpn_cls: 0.0111, loss_rpn_bbox: 0.0192, rbbox_loss_cls: 0.0977, rbbox_acc: 96.0645, rbbox_loss_bbox: 0.1788, loss: 0.3068\n",
            "2021-07-26 18:03:31,809 - INFO - Epoch [12][3850/6779]\tlr: 0.00010, eta: 0:54:10, time: 1.062, data_time: 0.115, memory: 4182, loss_rpn_cls: 0.0086, loss_rpn_bbox: 0.0146, rbbox_loss_cls: 0.0803, rbbox_acc: 96.8691, rbbox_loss_bbox: 0.1288, loss: 0.2323\n",
            "2021-07-26 18:04:25,955 - INFO - Epoch [12][3900/6779]\tlr: 0.00010, eta: 0:53:14, time: 1.083, data_time: 0.094, memory: 4182, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0174, rbbox_loss_cls: 0.1126, rbbox_acc: 95.5273, rbbox_loss_bbox: 0.1401, loss: 0.2806\n",
            "2021-07-26 18:05:15,278 - INFO - Epoch [12][3950/6779]\tlr: 0.00010, eta: 0:52:14, time: 0.986, data_time: 0.078, memory: 4182, loss_rpn_cls: 0.0144, loss_rpn_bbox: 0.0178, rbbox_loss_cls: 0.0942, rbbox_acc: 96.3184, rbbox_loss_bbox: 0.1283, loss: 0.2547\n",
            "2021-07-26 18:06:09,259 - INFO - Epoch [12][4000/6779]\tlr: 0.00010, eta: 0:51:18, time: 1.080, data_time: 0.125, memory: 4182, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0166, rbbox_loss_cls: 0.0932, rbbox_acc: 96.3418, rbbox_loss_bbox: 0.1455, loss: 0.2661\n",
            "2021-07-26 18:07:01,768 - INFO - Epoch [12][4050/6779]\tlr: 0.00010, eta: 0:50:20, time: 1.050, data_time: 0.095, memory: 4182, loss_rpn_cls: 0.0089, loss_rpn_bbox: 0.0153, rbbox_loss_cls: 0.0996, rbbox_acc: 96.1289, rbbox_loss_bbox: 0.1265, loss: 0.2504\n",
            "2021-07-26 18:08:01,925 - INFO - Epoch [12][4100/6779]\tlr: 0.00010, eta: 0:49:28, time: 1.203, data_time: 0.187, memory: 4182, loss_rpn_cls: 0.0129, loss_rpn_bbox: 0.0209, rbbox_loss_cls: 0.1027, rbbox_acc: 96.1738, rbbox_loss_bbox: 0.1497, loss: 0.2862\n",
            "2021-07-26 18:08:57,554 - INFO - Epoch [12][4150/6779]\tlr: 0.00010, eta: 0:48:33, time: 1.113, data_time: 0.123, memory: 4182, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0196, rbbox_loss_cls: 0.0946, rbbox_acc: 96.1582, rbbox_loss_bbox: 0.1321, loss: 0.2571\n",
            "2021-07-26 18:09:55,106 - INFO - Epoch [12][4200/6779]\tlr: 0.00010, eta: 0:47:39, time: 1.151, data_time: 0.175, memory: 4182, loss_rpn_cls: 0.0117, loss_rpn_bbox: 0.0192, rbbox_loss_cls: 0.0994, rbbox_acc: 96.0176, rbbox_loss_bbox: 0.1220, loss: 0.2523\n",
            "2021-07-26 18:10:48,687 - INFO - Epoch [12][4250/6779]\tlr: 0.00010, eta: 0:46:42, time: 1.072, data_time: 0.131, memory: 4182, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0197, rbbox_loss_cls: 0.0942, rbbox_acc: 96.3633, rbbox_loss_bbox: 0.1334, loss: 0.2564\n",
            "2021-07-26 18:11:40,247 - INFO - Epoch [12][4300/6779]\tlr: 0.00010, eta: 0:45:45, time: 1.031, data_time: 0.104, memory: 4182, loss_rpn_cls: 0.0076, loss_rpn_bbox: 0.0168, rbbox_loss_cls: 0.0904, rbbox_acc: 96.5352, rbbox_loss_bbox: 0.1302, loss: 0.2449\n",
            "2021-07-26 18:12:29,283 - INFO - Epoch [12][4350/6779]\tlr: 0.00010, eta: 0:44:46, time: 0.981, data_time: 0.073, memory: 4182, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0160, rbbox_loss_cls: 0.1030, rbbox_acc: 96.2051, rbbox_loss_bbox: 0.1499, loss: 0.2790\n",
            "2021-07-26 18:13:27,612 - INFO - Epoch [12][4400/6779]\tlr: 0.00010, eta: 0:43:52, time: 1.167, data_time: 0.174, memory: 4182, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0201, rbbox_loss_cls: 0.1049, rbbox_acc: 95.9902, rbbox_loss_bbox: 0.1344, loss: 0.2697\n",
            "2021-07-26 18:14:20,519 - INFO - Epoch [12][4450/6779]\tlr: 0.00010, eta: 0:42:55, time: 1.058, data_time: 0.113, memory: 4182, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0167, rbbox_loss_cls: 0.1035, rbbox_acc: 95.9590, rbbox_loss_bbox: 0.1237, loss: 0.2530\n",
            "2021-07-26 18:15:13,188 - INFO - Epoch [12][4500/6779]\tlr: 0.00010, eta: 0:41:59, time: 1.053, data_time: 0.095, memory: 4182, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0192, rbbox_loss_cls: 0.0916, rbbox_acc: 96.4824, rbbox_loss_bbox: 0.1508, loss: 0.2730\n",
            "2021-07-26 18:16:05,085 - INFO - Epoch [12][4550/6779]\tlr: 0.00010, eta: 0:41:02, time: 1.038, data_time: 0.102, memory: 4182, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0161, rbbox_loss_cls: 0.0907, rbbox_acc: 96.4180, rbbox_loss_bbox: 0.1327, loss: 0.2494\n",
            "2021-07-26 18:16:58,043 - INFO - Epoch [12][4600/6779]\tlr: 0.00010, eta: 0:40:06, time: 1.059, data_time: 0.086, memory: 4182, loss_rpn_cls: 0.0097, loss_rpn_bbox: 0.0183, rbbox_loss_cls: 0.0951, rbbox_acc: 96.3418, rbbox_loss_bbox: 0.1347, loss: 0.2578\n",
            "2021-07-26 18:18:01,757 - INFO - Epoch [12][4650/6779]\tlr: 0.00010, eta: 0:39:14, time: 1.274, data_time: 0.313, memory: 4182, loss_rpn_cls: 0.0108, loss_rpn_bbox: 0.0172, rbbox_loss_cls: 0.1047, rbbox_acc: 95.8750, rbbox_loss_bbox: 0.1759, loss: 0.3085\n",
            "2021-07-26 18:18:56,003 - INFO - Epoch [12][4700/6779]\tlr: 0.00010, eta: 0:38:18, time: 1.085, data_time: 0.123, memory: 4182, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0178, rbbox_loss_cls: 0.0951, rbbox_acc: 96.3164, rbbox_loss_bbox: 0.1207, loss: 0.2431\n",
            "2021-07-26 18:19:46,154 - INFO - Epoch [12][4750/6779]\tlr: 0.00010, eta: 0:37:21, time: 1.003, data_time: 0.078, memory: 4182, loss_rpn_cls: 0.0115, loss_rpn_bbox: 0.0164, rbbox_loss_cls: 0.0987, rbbox_acc: 96.1465, rbbox_loss_bbox: 0.1352, loss: 0.2619\n",
            "2021-07-26 18:20:37,221 - INFO - Epoch [12][4800/6779]\tlr: 0.00010, eta: 0:36:24, time: 1.021, data_time: 0.085, memory: 4182, loss_rpn_cls: 0.0079, loss_rpn_bbox: 0.0187, rbbox_loss_cls: 0.0925, rbbox_acc: 96.2461, rbbox_loss_bbox: 0.1263, loss: 0.2454\n",
            "2021-07-26 18:21:29,326 - INFO - Epoch [12][4850/6779]\tlr: 0.00010, eta: 0:35:28, time: 1.042, data_time: 0.122, memory: 4182, loss_rpn_cls: 0.0128, loss_rpn_bbox: 0.0164, rbbox_loss_cls: 0.0870, rbbox_acc: 96.5039, rbbox_loss_bbox: 0.1154, loss: 0.2316\n",
            "2021-07-26 18:22:24,561 - INFO - Epoch [12][4900/6779]\tlr: 0.00010, eta: 0:34:32, time: 1.105, data_time: 0.138, memory: 4182, loss_rpn_cls: 0.0127, loss_rpn_bbox: 0.0184, rbbox_loss_cls: 0.0834, rbbox_acc: 96.8301, rbbox_loss_bbox: 0.1256, loss: 0.2400\n",
            "2021-07-26 18:23:16,012 - INFO - Epoch [12][4950/6779]\tlr: 0.00010, eta: 0:33:36, time: 1.029, data_time: 0.092, memory: 4182, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0191, rbbox_loss_cls: 0.0974, rbbox_acc: 96.1699, rbbox_loss_bbox: 0.1486, loss: 0.2755\n",
            "2021-07-26 18:24:18,638 - INFO - Epoch [12][5000/6779]\tlr: 0.00010, eta: 0:32:43, time: 1.252, data_time: 0.213, memory: 4182, loss_rpn_cls: 0.0114, loss_rpn_bbox: 0.0204, rbbox_loss_cls: 0.0940, rbbox_acc: 96.3066, rbbox_loss_bbox: 0.1280, loss: 0.2538\n",
            "2021-07-26 18:25:14,711 - INFO - Epoch [12][5050/6779]\tlr: 0.00010, eta: 0:31:49, time: 1.121, data_time: 0.133, memory: 4182, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0170, rbbox_loss_cls: 0.0981, rbbox_acc: 96.1699, rbbox_loss_bbox: 0.1471, loss: 0.2726\n",
            "2021-07-26 18:26:10,634 - INFO - Epoch [12][5100/6779]\tlr: 0.00010, eta: 0:30:54, time: 1.118, data_time: 0.139, memory: 4182, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0173, rbbox_loss_cls: 0.0928, rbbox_acc: 96.5605, rbbox_loss_bbox: 0.1187, loss: 0.2382\n",
            "2021-07-26 18:27:04,073 - INFO - Epoch [12][5150/6779]\tlr: 0.00010, eta: 0:29:58, time: 1.069, data_time: 0.123, memory: 4182, loss_rpn_cls: 0.0080, loss_rpn_bbox: 0.0165, rbbox_loss_cls: 0.0879, rbbox_acc: 96.5898, rbbox_loss_bbox: 0.1198, loss: 0.2323\n",
            "2021-07-26 18:27:58,521 - INFO - Epoch [12][5200/6779]\tlr: 0.00010, eta: 0:29:02, time: 1.089, data_time: 0.135, memory: 4182, loss_rpn_cls: 0.0101, loss_rpn_bbox: 0.0179, rbbox_loss_cls: 0.0975, rbbox_acc: 96.1914, rbbox_loss_bbox: 0.1235, loss: 0.2490\n",
            "2021-07-26 18:28:53,485 - INFO - Epoch [12][5250/6779]\tlr: 0.00010, eta: 0:28:07, time: 1.099, data_time: 0.106, memory: 4182, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0195, rbbox_loss_cls: 0.0970, rbbox_acc: 96.1328, rbbox_loss_bbox: 0.1277, loss: 0.2548\n",
            "2021-07-26 18:29:52,604 - INFO - Epoch [12][5300/6779]\tlr: 0.00010, eta: 0:27:13, time: 1.182, data_time: 0.172, memory: 4182, loss_rpn_cls: 0.0094, loss_rpn_bbox: 0.0182, rbbox_loss_cls: 0.1008, rbbox_acc: 96.1250, rbbox_loss_bbox: 0.1234, loss: 0.2517\n",
            "2021-07-26 18:30:49,478 - INFO - Epoch [12][5350/6779]\tlr: 0.00010, eta: 0:26:18, time: 1.138, data_time: 0.170, memory: 4182, loss_rpn_cls: 0.0102, loss_rpn_bbox: 0.0141, rbbox_loss_cls: 0.0862, rbbox_acc: 96.5723, rbbox_loss_bbox: 0.1466, loss: 0.2571\n",
            "2021-07-26 18:31:40,186 - INFO - Epoch [12][5400/6779]\tlr: 0.00010, eta: 0:25:22, time: 1.014, data_time: 0.084, memory: 4182, loss_rpn_cls: 0.0090, loss_rpn_bbox: 0.0162, rbbox_loss_cls: 0.1024, rbbox_acc: 96.0137, rbbox_loss_bbox: 0.1411, loss: 0.2687\n",
            "2021-07-26 18:32:41,705 - INFO - Epoch [12][5450/6779]\tlr: 0.00010, eta: 0:24:28, time: 1.230, data_time: 0.271, memory: 4182, loss_rpn_cls: 0.0074, loss_rpn_bbox: 0.0151, rbbox_loss_cls: 0.0838, rbbox_acc: 96.7129, rbbox_loss_bbox: 0.1178, loss: 0.2241\n",
            "2021-07-26 18:33:43,864 - INFO - Epoch [12][5500/6779]\tlr: 0.00010, eta: 0:23:35, time: 1.243, data_time: 0.234, memory: 4182, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0172, rbbox_loss_cls: 0.0892, rbbox_acc: 96.5645, rbbox_loss_bbox: 0.1415, loss: 0.2602\n",
            "2021-07-26 18:34:41,587 - INFO - Epoch [12][5550/6779]\tlr: 0.00010, eta: 0:22:40, time: 1.154, data_time: 0.133, memory: 4182, loss_rpn_cls: 0.0138, loss_rpn_bbox: 0.0193, rbbox_loss_cls: 0.1030, rbbox_acc: 95.9746, rbbox_loss_bbox: 0.1825, loss: 0.3185\n",
            "2021-07-26 18:35:42,286 - INFO - Epoch [12][5600/6779]\tlr: 0.00010, eta: 0:21:46, time: 1.214, data_time: 0.193, memory: 4182, loss_rpn_cls: 0.0096, loss_rpn_bbox: 0.0178, rbbox_loss_cls: 0.0964, rbbox_acc: 96.2812, rbbox_loss_bbox: 0.1389, loss: 0.2627\n",
            "2021-07-26 18:36:50,482 - INFO - Epoch [12][5650/6779]\tlr: 0.00010, eta: 0:20:53, time: 1.364, data_time: 0.378, memory: 4182, loss_rpn_cls: 0.0099, loss_rpn_bbox: 0.0145, rbbox_loss_cls: 0.0914, rbbox_acc: 96.5703, rbbox_loss_bbox: 0.1313, loss: 0.2472\n",
            "2021-07-26 18:37:49,974 - INFO - Epoch [12][5700/6779]\tlr: 0.00010, eta: 0:19:58, time: 1.190, data_time: 0.170, memory: 4182, loss_rpn_cls: 0.0123, loss_rpn_bbox: 0.0190, rbbox_loss_cls: 0.0970, rbbox_acc: 96.1777, rbbox_loss_bbox: 0.1385, loss: 0.2668\n",
            "2021-07-26 18:38:43,655 - INFO - Epoch [12][5750/6779]\tlr: 0.00010, eta: 0:19:02, time: 1.074, data_time: 0.127, memory: 4182, loss_rpn_cls: 0.0085, loss_rpn_bbox: 0.0141, rbbox_loss_cls: 0.0859, rbbox_acc: 96.4863, rbbox_loss_bbox: 0.1146, loss: 0.2232\n",
            "2021-07-26 18:39:34,351 - INFO - Epoch [12][5800/6779]\tlr: 0.00010, eta: 0:18:06, time: 1.014, data_time: 0.080, memory: 4182, loss_rpn_cls: 0.0085, loss_rpn_bbox: 0.0147, rbbox_loss_cls: 0.1010, rbbox_acc: 96.0820, rbbox_loss_bbox: 0.1524, loss: 0.2766\n",
            "2021-07-26 18:40:30,101 - INFO - Epoch [12][5850/6779]\tlr: 0.00010, eta: 0:17:10, time: 1.115, data_time: 0.121, memory: 4182, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0172, rbbox_loss_cls: 0.0974, rbbox_acc: 96.0625, rbbox_loss_bbox: 0.1477, loss: 0.2726\n",
            "2021-07-26 18:41:24,840 - INFO - Epoch [12][5900/6779]\tlr: 0.00010, eta: 0:16:15, time: 1.095, data_time: 0.130, memory: 4182, loss_rpn_cls: 0.0080, loss_rpn_bbox: 0.0147, rbbox_loss_cls: 0.0906, rbbox_acc: 96.4375, rbbox_loss_bbox: 0.1132, loss: 0.2266\n",
            "2021-07-26 18:42:20,562 - INFO - Epoch [12][5950/6779]\tlr: 0.00010, eta: 0:15:19, time: 1.114, data_time: 0.118, memory: 4182, loss_rpn_cls: 0.0155, loss_rpn_bbox: 0.0199, rbbox_loss_cls: 0.1085, rbbox_acc: 95.7500, rbbox_loss_bbox: 0.1316, loss: 0.2756\n",
            "2021-07-26 18:43:17,026 - INFO - Epoch [12][6000/6779]\tlr: 0.00010, eta: 0:14:24, time: 1.129, data_time: 0.127, memory: 4182, loss_rpn_cls: 0.0088, loss_rpn_bbox: 0.0188, rbbox_loss_cls: 0.0928, rbbox_acc: 96.2441, rbbox_loss_bbox: 0.1469, loss: 0.2673\n",
            "2021-07-26 18:44:16,719 - INFO - Epoch [12][6050/6779]\tlr: 0.00010, eta: 0:13:29, time: 1.194, data_time: 0.185, memory: 4182, loss_rpn_cls: 0.0122, loss_rpn_bbox: 0.0205, rbbox_loss_cls: 0.1066, rbbox_acc: 95.7871, rbbox_loss_bbox: 0.1408, loss: 0.2800\n",
            "2021-07-26 18:45:13,208 - INFO - Epoch [12][6100/6779]\tlr: 0.00010, eta: 0:12:34, time: 1.130, data_time: 0.125, memory: 4182, loss_rpn_cls: 0.0116, loss_rpn_bbox: 0.0158, rbbox_loss_cls: 0.1010, rbbox_acc: 96.1348, rbbox_loss_bbox: 0.1159, loss: 0.2442\n",
            "2021-07-26 18:46:05,228 - INFO - Epoch [12][6150/6779]\tlr: 0.00010, eta: 0:11:38, time: 1.040, data_time: 0.089, memory: 4182, loss_rpn_cls: 0.0105, loss_rpn_bbox: 0.0159, rbbox_loss_cls: 0.0905, rbbox_acc: 96.4434, rbbox_loss_bbox: 0.1025, loss: 0.2194\n",
            "2021-07-26 18:47:10,012 - INFO - Epoch [12][6200/6779]\tlr: 0.00010, eta: 0:10:43, time: 1.296, data_time: 0.277, memory: 4182, loss_rpn_cls: 0.0087, loss_rpn_bbox: 0.0165, rbbox_loss_cls: 0.0958, rbbox_acc: 96.2520, rbbox_loss_bbox: 0.1424, loss: 0.2635\n",
            "2021-07-26 18:48:05,187 - INFO - Epoch [12][6250/6779]\tlr: 0.00010, eta: 0:09:47, time: 1.104, data_time: 0.135, memory: 4182, loss_rpn_cls: 0.0098, loss_rpn_bbox: 0.0163, rbbox_loss_cls: 0.0946, rbbox_acc: 96.3730, rbbox_loss_bbox: 0.1440, loss: 0.2647\n",
            "2021-07-26 18:49:02,071 - INFO - Epoch [12][6300/6779]\tlr: 0.00010, eta: 0:08:52, time: 1.138, data_time: 0.157, memory: 4182, loss_rpn_cls: 0.0106, loss_rpn_bbox: 0.0157, rbbox_loss_cls: 0.0978, rbbox_acc: 96.2559, rbbox_loss_bbox: 0.1132, loss: 0.2373\n",
            "2021-07-26 18:49:54,974 - INFO - Epoch [12][6350/6779]\tlr: 0.00010, eta: 0:07:56, time: 1.058, data_time: 0.105, memory: 4182, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0140, rbbox_loss_cls: 0.0827, rbbox_acc: 96.7441, rbbox_loss_bbox: 0.1212, loss: 0.2284\n",
            "2021-07-26 18:50:52,956 - INFO - Epoch [12][6400/6779]\tlr: 0.00010, eta: 0:07:01, time: 1.160, data_time: 0.152, memory: 4182, loss_rpn_cls: 0.0100, loss_rpn_bbox: 0.0182, rbbox_loss_cls: 0.0958, rbbox_acc: 96.2559, rbbox_loss_bbox: 0.1492, loss: 0.2733\n",
            "2021-07-26 18:51:49,241 - INFO - Epoch [12][6450/6779]\tlr: 0.00010, eta: 0:06:05, time: 1.126, data_time: 0.124, memory: 4182, loss_rpn_cls: 0.0124, loss_rpn_bbox: 0.0189, rbbox_loss_cls: 0.1017, rbbox_acc: 95.9160, rbbox_loss_bbox: 0.1515, loss: 0.2844\n",
            "2021-07-26 18:52:44,734 - INFO - Epoch [12][6500/6779]\tlr: 0.00010, eta: 0:05:10, time: 1.110, data_time: 0.132, memory: 4182, loss_rpn_cls: 0.0083, loss_rpn_bbox: 0.0158, rbbox_loss_cls: 0.0904, rbbox_acc: 96.4941, rbbox_loss_bbox: 0.1404, loss: 0.2549\n",
            "2021-07-26 18:54:08,223 - INFO - Epoch [12][6550/6779]\tlr: 0.00010, eta: 0:04:15, time: 1.670, data_time: 0.680, memory: 4182, loss_rpn_cls: 0.0091, loss_rpn_bbox: 0.0138, rbbox_loss_cls: 0.0871, rbbox_acc: 96.6855, rbbox_loss_bbox: 0.1520, loss: 0.2620\n",
            "2021-07-26 18:55:06,746 - INFO - Epoch [12][6600/6779]\tlr: 0.00010, eta: 0:03:19, time: 1.170, data_time: 0.192, memory: 4182, loss_rpn_cls: 0.0086, loss_rpn_bbox: 0.0180, rbbox_loss_cls: 0.0961, rbbox_acc: 96.2168, rbbox_loss_bbox: 0.1311, loss: 0.2538\n",
            "2021-07-26 18:56:04,209 - INFO - Epoch [12][6650/6779]\tlr: 0.00010, eta: 0:02:24, time: 1.149, data_time: 0.138, memory: 4182, loss_rpn_cls: 0.0104, loss_rpn_bbox: 0.0163, rbbox_loss_cls: 0.0908, rbbox_acc: 96.4141, rbbox_loss_bbox: 0.1554, loss: 0.2729\n",
            "2021-07-26 18:56:58,484 - INFO - Epoch [12][6700/6779]\tlr: 0.00010, eta: 0:01:28, time: 1.086, data_time: 0.098, memory: 4182, loss_rpn_cls: 0.0141, loss_rpn_bbox: 0.0161, rbbox_loss_cls: 0.0969, rbbox_acc: 96.2715, rbbox_loss_bbox: 0.1593, loss: 0.2864\n",
            "2021-07-26 18:58:05,050 - INFO - Epoch [12][6750/6779]\tlr: 0.00010, eta: 0:00:32, time: 1.331, data_time: 0.310, memory: 4182, loss_rpn_cls: 0.0130, loss_rpn_bbox: 0.0194, rbbox_loss_cls: 0.1041, rbbox_acc: 95.7461, rbbox_loss_bbox: 0.1249, loss: 0.2614\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9Q552hcSkPMd"
      },
      "source": [
        "!mv /content/AerialDetection/data/dota /content/drive/MyDrive/dota_dataaaaa"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9IqZOzLQjQ5r"
      },
      "source": [
        "# تست کردن شبکه"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lHhkDYeLje_T"
      },
      "source": [
        "ReDet_re50_refpn_1x_dota1 test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S-04lRL0jUwQ",
        "outputId": "6d909195-1bff-47e2-b798-614b8f583214"
      },
      "source": [
        "!python /content/ReDet/tools/test.py /content/ReDet/configs/ReDet/ReDet_re50_refpn_1x_dota1.py  \\\n",
        "  /content/ReDet/work_dirs/pth/ReDet_re50_refpn_1x_dota1-a025e6b1.pth --out /content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/results.pkl "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ReResNet Orientation: 8\tFix Params: False\n",
            "loading annotations into memory...\n",
            "Done (t=0.01s)\n",
            "creating index...\n",
            "index created!\n",
            "The model and loaded state dict do not match exactly\n",
            "\n",
            "missing keys in source state_dict: backbone.layer2.0.conv2.filter, backbone.layer3.4.conv2.filter, neck.lateral_convs.0.conv.expanded_bias, backbone.layer2.2.conv2.filter, backbone.layer3.0.conv3.filter, neck.fpn_convs.0.conv.filter, backbone.layer3.4.conv3.filter, backbone.layer3.2.conv2.filter, backbone.layer2.1.conv1.filter, backbone.layer3.0.downsample.0.filter, backbone.layer2.1.conv2.filter, neck.fpn_convs.1.conv.filter, backbone.layer2.3.conv2.filter, neck.lateral_convs.2.conv.filter, backbone.layer4.2.conv3.filter, backbone.layer3.1.conv1.filter, backbone.layer2.2.conv3.filter, backbone.layer4.0.conv3.filter, backbone.layer3.5.conv2.filter, neck.lateral_convs.1.conv.expanded_bias, backbone.layer3.5.conv1.filter, backbone.layer3.3.conv2.filter, backbone.layer4.0.conv1.filter, backbone.layer4.1.conv1.filter, backbone.layer4.2.conv2.filter, backbone.layer3.3.conv3.filter, backbone.layer3.2.conv3.filter, backbone.layer3.0.conv1.filter, neck.lateral_convs.3.conv.filter, backbone.layer4.0.conv2.filter, neck.fpn_convs.1.conv.expanded_bias, neck.lateral_convs.1.conv.filter, neck.fpn_convs.3.conv.expanded_bias, backbone.layer3.4.conv1.filter, neck.fpn_convs.0.conv.expanded_bias, neck.fpn_convs.2.conv.filter, backbone.layer3.1.conv2.filter, backbone.conv1.filter, backbone.layer4.1.conv2.filter, neck.fpn_convs.2.conv.expanded_bias, backbone.layer2.3.conv3.filter, backbone.layer3.1.conv3.filter, backbone.layer2.3.conv1.filter, backbone.layer2.0.conv3.filter, backbone.layer4.0.downsample.0.filter, backbone.layer4.1.conv3.filter, neck.lateral_convs.2.conv.expanded_bias, neck.lateral_convs.0.conv.filter, neck.lateral_convs.3.conv.expanded_bias, backbone.layer3.3.conv1.filter, neck.fpn_convs.3.conv.filter, backbone.layer3.5.conv3.filter, backbone.layer2.2.conv1.filter, backbone.layer3.2.conv1.filter, backbone.layer4.2.conv1.filter, backbone.layer2.0.conv1.filter, backbone.layer2.1.conv3.filter, backbone.layer3.0.conv2.filter, backbone.layer2.0.downsample.0.filter\n",
            "\n",
            "terminal width is too small (0), please consider widen the terminal for better progressbar visualization\n",
            "[          ] 0/4750, elapsed: 0s, ETA:THCudaCheck FAIL file=/pytorch/aten/src/THC/THCGeneral.cpp line=383 error=11 : invalid argument\n",
            "[>>>>>>>>>>] 4750/4750, 2.1 task/s, elapsed: 2243s, ETA:     0s\n",
            "writing results to /content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/results.pkl\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-7o54deMlsoE"
      },
      "source": [
        "faster_rcnn_RoITrans_r50_fpn_1x_dota test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7o7oXfislrxn"
      },
      "source": [
        "!python /content/ReDet/tools/test.py /content/ReDet/configs/DOTA/faster_rcnn_RoITrans_r50_fpn_1x_dota.py  \\\n",
        "  /content/ReDet/work_dirs/faster_rcnn_RoITrans_r50_fpn_1x_dota/epoch_12.pth --out /content/ReDet/work_dirs/faster_rcnn_RoITrans_r50_fpn_1x_dota/results.pkl "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-KXGXmfkoEJm"
      },
      "source": [
        "faster_rcnn_obb_r50_fpn_1x_dota.py test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ayvhovoBnemV",
        "outputId": "3b91b7c3-8934-4f37-ed06-3f4d75ed2c98"
      },
      "source": [
        "!python /content/ReDet/tools/test.py /content/ReDet/configs/DOTA/faster_rcnn_obb_r50_fpn_1x_dota.py  \\\n",
        "        /content/ReDet/work_dirs/faster_rcnn_obb_r50_fpn_1x_dota/epoch_12.pth --out /content/ReDet/work_dirs/faster_rcnn_obb_r50_fpn_1x_dota/results.pkl "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ReResNet Orientation: 8\tFix Params: False\n",
            "loading annotations into memory...\n",
            "Done (t=0.01s)\n",
            "creating index...\n",
            "index created!\n",
            "terminal width is too small (0), please consider widen the terminal for better progressbar visualization\n",
            "[          ] 0/4750, elapsed: 0s, ETA:THCudaCheck FAIL file=/pytorch/aten/src/THC/THCGeneral.cpp line=383 error=11 : invalid argument\n",
            "[>>        ] 1356/4750, 2.1 task/s, elapsed: 636s, ETA:  1591s"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EIfe_MCUaMSp",
        "outputId": "65d55fd7-a1c2-4e62-cad7-fba624664037"
      },
      "source": [
        "# %pycat /content/AerialDetection/tools/parse_results.py\n",
        "%%writefile /content/ReDet/tools/parse_results.py\n",
        "\n",
        "from __future__ import division\n",
        "\n",
        "import argparse\n",
        "import os.path as osp\n",
        "import shutil\n",
        "import tempfile\n",
        "\n",
        "import mmcv\n",
        "from mmdet.apis import init_dist\n",
        "from mmdet.core import results2json, coco_eval, \\\n",
        "    HBBSeg2Comp4, OBBDet2Comp4, OBBDetComp4, \\\n",
        "    HBBOBB2Comp4, HBBDet2Comp4\n",
        "\n",
        "import argparse\n",
        "\n",
        "from mmdet import __version__\n",
        "from mmdet.datasets import get_dataset\n",
        "from mmdet.apis import (train_detector, init_dist, get_root_logger,\n",
        "                        set_random_seed)\n",
        "from mmdet.models import build_detector\n",
        "import torch\n",
        "import json\n",
        "from mmcv import Config\n",
        "import sys\n",
        "# sys.path.insert(0, '../')\n",
        "# import DOTA_devkit.ResultMerge_multi_process as RM\n",
        "from DOTA_devkit.ResultMerge_multi_process import *\n",
        "# import pdb; pdb.set_trace()\n",
        "def parse_args():\n",
        "    parser = argparse.ArgumentParser(description='Train a detector')\n",
        "    parser.add_argument('--config', default='configs/DOTA/faster_rcnn_r101_fpn_1x_dota2_v3_RoITrans_v5.py')\n",
        "    parser.add_argument('--type', default=r'HBB',\n",
        "                        help='parse type of detector')\n",
        "    args = parser.parse_args()\n",
        "\n",
        "    return args\n",
        "\n",
        "def OBB2HBB(srcpath, dstpath):\n",
        "    filenames = util.GetFileFromThisRootDir(srcpath)\n",
        "    if not os.path.exists(dstpath):\n",
        "        os.makedirs(dstpath)\n",
        "    for file in filenames:\n",
        "        with open(file, 'r') as f_in:\n",
        "            with open(os.path.join(dstpath, os.path.basename(os.path.splitext(file)[0]) + '.txt'), 'w') as f_out:\n",
        "                lines = f_in.readlines()\n",
        "                splitlines = [x.strip().split() for x in lines]\n",
        "                for index, splitline in enumerate(splitlines):\n",
        "                    imgname = splitline[0]\n",
        "                    score = splitline[1]\n",
        "                    poly = splitline[2:]\n",
        "                    poly = list(map(float, poly))\n",
        "                    xmin, xmax, ymin, ymax = min(poly[0::2]), max(poly[0::2]), min(poly[1::2]), max(poly[1::2])\n",
        "                    rec_poly = [xmin, ymin, xmax, ymax]\n",
        "                    outline = imgname + ' ' + score + ' ' + ' '.join(map(str, rec_poly))\n",
        "                    if index != (len(splitlines) - 1):\n",
        "                        outline = outline + '\\n'\n",
        "                    f_out.write(outline)\n",
        "\n",
        "def parse_results(config_file, resultfile, dstpath, type):\n",
        "    cfg = Config.fromfile(config_file)\n",
        "\n",
        "    data_test = cfg.data['test']\n",
        "    dataset = get_dataset(data_test)\n",
        "    outputs = mmcv.load(resultfile)\n",
        "    if type == 'OBB':\n",
        "        #  dota1 has tested\n",
        "        obb_results_dict = OBBDetComp4(dataset, outputs)\n",
        "        current_thresh = 0.1\n",
        "    elif type == 'HBB':\n",
        "        # dota1 has tested\n",
        "        hbb_results_dict = HBBDet2Comp4(dataset, outputs)\n",
        "    elif type == 'HBBOBB':\n",
        "        # dota1 has tested\n",
        "        # dota2\n",
        "        hbb_results_dict, obb_results_dict = HBBOBB2Comp4(dataset, outputs)\n",
        "        current_thresh = 0.3\n",
        "    elif type == 'Mask':\n",
        "        # TODO: dota1 did not pass\n",
        "        # dota2, hbb has passed, obb has passed\n",
        "        hbb_results_dict, obb_results_dict = HBBSeg2Comp4(dataset, outputs)\n",
        "        current_thresh = 0.3\n",
        "\n",
        "    dataset_type = cfg.dataset_type\n",
        "\n",
        "    if 'obb_results_dict' in vars():\n",
        "        if not os.path.exists(os.path.join(dstpath, 'Task1_results')):\n",
        "            os.makedirs(os.path.join(dstpath, 'Task1_results'))\n",
        "\n",
        "        for cls in obb_results_dict:\n",
        "            with open(os.path.join(dstpath, 'Task1_results', cls + '.txt'), 'w') as obb_f_out:\n",
        "                for index, outline in enumerate(obb_results_dict[cls]):\n",
        "                    if index != (len(obb_results_dict[cls]) - 1):\n",
        "                        obb_f_out.write(outline + '\\n')\n",
        "                    else:\n",
        "                        obb_f_out.write(outline)\n",
        "\n",
        "        if not os.path.exists(os.path.join(dstpath, 'Task1_results_nms')):\n",
        "            os.makedirs(os.path.join(dstpath, 'Task1_results_nms'))\n",
        "\n",
        "        mergebypoly_multiprocess(os.path.join(dstpath, 'Task1_results'),\n",
        "                                 os.path.join(dstpath, 'Task1_results_nms'), nms_type=r'py_cpu_nms_poly_fast', o_thresh=current_thresh)\n",
        "\n",
        "        OBB2HBB(os.path.join(dstpath, 'Task1_results_nms'),\n",
        "                         os.path.join(dstpath, 'Transed_Task2_results_nms'))\n",
        "\n",
        "    if 'hbb_results_dict' in vars():\n",
        "        if not os.path.exists(os.path.join(dstpath, 'Task2_results')):\n",
        "            os.makedirs(os.path.join(dstpath, 'Task2_results'))\n",
        "        for cls in hbb_results_dict:\n",
        "            with open(os.path.join(dstpath, 'Task2_results', cls + '.txt'), 'w') as f_out:\n",
        "                for index, outline in enumerate(hbb_results_dict[cls]):\n",
        "                    if index != (len(hbb_results_dict[cls]) - 1):\n",
        "                        f_out.write(outline + '\\n')\n",
        "                    else:\n",
        "                        f_out.write(outline)\n",
        "\n",
        "        if not os.path.exists(os.path.join(dstpath, 'Task2_results_nms')):\n",
        "            os.makedirs(os.path.join(dstpath, 'Task2_results_nms'))\n",
        "        mergebyrec(os.path.join(dstpath, 'Task2_results'),\n",
        "            os.path.join(dstpath, 'Task2_results_nms'))\n",
        "\n",
        "if __name__ == '__main__':\n",
        "    args = parse_args()\n",
        "    config_file = args.config\n",
        "    config_name = os.path.splitext(os.path.basename(config_file))[0]\n",
        "\n",
        "    ######################################################################################/content/AerialDetection/work_dirs\n",
        "    pkl_file = os.path.join('/content/ReDet/work_dirs', config_name, 'results.pkl')\n",
        "    output_path = os.path.join('/content/ReDet/work_dirs', config_name)\n",
        "    type = args.type\n",
        "    parse_results(config_file, pkl_file, output_path, type)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Overwriting /content/ReDet/tools/parse_results.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6orwO2Vuo9JY"
      },
      "source": [
        "به کمک دستورات زیر از فایل تولید شده‌ی سریالایز شده سه فلدر پارس شده دریافت می‌شود"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-KX5UTkkqbt0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ae826479-259c-46b8-d70c-c52d5665fa2f"
      },
      "source": [
        "!python /content/ReDet/tools/parse_results.py --config /content/ReDet/configs/ReDet/ReDet_re50_refpn_1x_dota1.py --type OBB"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ReResNet Orientation: 8\tFix Params: False\n",
            "loading annotations into memory...\n",
            "Done (t=0.29s)\n",
            "creating index...\n",
            "index created!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fUManRxhoep1"
      },
      "source": [
        "!python /content/ReDet/tools/parse_results.py --config /content/ReDet/configs/DOTA/faster_rcnn_RoITrans_r50_fpn_1x_dota.py --type OBB"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sri6v9OsonQq"
      },
      "source": [
        "!python /content/ReDet/tools/parse_results.py --config /content/ReDet/configs/DOTA/faster_rcnn_obb_r50_fpn_1x_dota.py --type OBB"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hRIjpHiopbE9"
      },
      "source": [
        "باید دانلود شده زیپ شده و آپلود شود Task1_results_nms برای ارزیابی تسک اول فایل "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "72VgnGJBbHrA",
        "outputId": "fcd265b2-a074-4364-9761-a7a8759cc2c9"
      },
      "source": [
        "!tar -cvf '/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms.tar' '/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms'"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tar: Removing leading `/' from member names\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/basketball-court.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/ground-track-field.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/roundabout.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/baseball-diamond.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/helicopter.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/soccer-ball-field.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/tennis-court.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/storage-tank.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/swimming-pool.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/bridge.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/plane.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/large-vehicle.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/harbor.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/small-vehicle.txt\n",
            "/content/ReDet/work_dirs/ReDet_re50_refpn_1x_dota1/Task1_results_nms/ship.txt\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}