Develop

README.md

@@ -67,13 +67,11 @@ python test.py
 If you use arcjetCV in your research, please use the following BibTeX entries to cite it:
 
 ```BibTeX
-@inbook{doi:10.2514/6.2023-1912,
-author = {Alexandre Quintart and Magnus A. Haw},
-title = {ArcjetCV: a new machine learning application for extracting time-resolved recession measurements from arc jet test videos},
-booktitle = {AIAA SCITECH 2023 Forum},
-doi = {10.2514/6.2023-1912},
-URL = {https://arc.aiaa.org/doi/abs/10.2514/6.2023-1912},
-eprint = {https://arc.aiaa.org/doi/pdf/10.2514/6.2023-1912},
+@article{arcjetCV,
+  title={arcjetCV: an open-source software to analyze material ablation},
+  author={Quintart, Alexandre and Haw, Magnus and Semeraro, Federico},
+  journal={arXiv preprint arXiv:2404.11492},
+  year={2024}
 }
 ```
 

docs/source/user_manual/user_manual.md

@@ -101,7 +101,3 @@ The **Analyze** tab contains tools for visualizing and fitting the processed edg
 
    Export the plotted and fitted data to CSV using the "Export CSV/Plots" button.
 
-.. figure:: /path/to/GUI3.png
-   :width: 70%
-   :align: center
-   :caption: The post-processing window.

tests/test_gui.py

@@ -139,13 +139,13 @@ def test_apply_crop(app, qtbot, mocker):
     assert app.video is not None
     assert app.videometa is not None
 
-    app.ui.spinBox_crop_xmin.setValue(117)
-    app.ui.spinBox_crop_xmax.setValue(391)
-    app.ui.spinBox_crop_ymin.setValue(36)
-    app.ui.spinBox_crop_ymax.setValue(641)
+    app.ui.spinBox_crop_xmin.setValue(100)
+    app.ui.spinBox_crop_xmax.setValue(425)
+    app.ui.spinBox_crop_ymin.setValue(10)
+    app.ui.spinBox_crop_ymax.setValue(700)
 
     qtbot.mouseClick(app.ui.applyCrop, Qt.LeftButton)
-    expected_crop_settings = [[36, 641], [117, 391]]
+    expected_crop_settings = [[10, 700], [100, 425]]
     current_crop_settings = app.videometa.crop_range()
 
     assert (
@@ -236,11 +236,11 @@ def test_set_frame_range(app, qtbot, mocker):
     Test setting the frame range for processing.
     """
     test_load_video(app, qtbot, mocker)
-    app.ui.spinBox_FirstGoodFrame.setValue(10)
-    app.ui.spinBox_LastGoodFrame.setValue(150)
+    app.ui.spinBox_FirstGoodFrame.setValue(150)
+    app.ui.spinBox_LastGoodFrame.setValue(400)
     app.process_all()
-    assert app.videometa["FIRST_GOOD_FRAME"] == 10
-    assert app.videometa["LAST_GOOD_FRAME"] == 150
+    assert app.videometa["FIRST_GOOD_FRAME"] == 150
+    assert app.videometa["LAST_GOOD_FRAME"] == 400
 
 
 def test_process_every_nth_frame(app, qtbot, mocker):
@@ -260,7 +260,7 @@ def test_set_output_filename(app, qtbot, mocker):
     test_load_video(app, qtbot, mocker)
     app.ui.lineEdit_filename.setText("output_filename")
     app.process_all()
-    assert app.processor.filename == "output_filename_10_150.json"
+    assert app.processor.filename == "output_filename_150_400.json"
 
 
 def test_toggle_write_video(app, qtbot, mocker):
@@ -301,7 +301,7 @@ def test_load_analysis_files(app, qtbot, mocker):
     """
     Test loading files in the 'Analysis' tab and verifying UI updates.
     """
-    expected_file_path = os.path.join(find_tests_path(), "test_10_150.json")
+    expected_file_path = os.path.join(find_tests_path(), "arcjet_test_150_400.json")
     mocker.patch(
         "PySide6.QtWidgets.QFileDialog.getOpenFileNames",
         return_value=([expected_file_path], ""),
@@ -317,7 +317,7 @@ def test_plot_data_button(app, qtbot, mocker):
     Test the 'Plot Data' button functionality in the 'Analysis' tab after loading analysis files.
     """
 
-    expected_file_path = os.path.join(find_tests_path(), "test_10_150.json")
+    expected_file_path = os.path.join(find_tests_path(), "arcjet_test_150_400.json")
     mocker.patch(
         "PySide6.QtWidgets.QFileDialog.getOpenFileNames",
         return_value=([expected_file_path], ""),

tutorial.ipynb

@@ -1,101 +1,140 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# arcjetCV Tutorial"
-   ]
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "jWLZa2NcV1fa"
+      },
+      "source": [
+        "# arcjetCV Tutorial"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "su6ZgnRMV1fd",
+        "outputId": "9a4c5c2f-9d5c-4dde-fe61-bb170302d4eb"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install git+https://github.com/magnus-haw/arcjetCV.git@develop -q\n",
+        "!pip install segmentation-models-pytorch -q\n",
+        "!pip install imageio[pyav] -q  # to load m4v\n",
+        "!wget https://github.com/magnus-haw/arcjetCV/raw/develop/tests/arcjet_test.mp4 -q  # example video"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "FEoaneAFV1fe"
+      },
+      "outputs": [],
+      "source": [
+        "# functions to convert and display videos\n",
+        "from moviepy.editor import ipython_display as display_video\n",
+        "import imageio\n",
+        "def convert_and_crop_video(video_path, output_path, fps=30, max_frames=None):\n",
+        "  frames = imageio.mimread(video_path, memtest=False)\n",
+        "  if max_frames is None:\n",
+        "    n_frames = len(frames)\n",
+        "  else:\n",
+        "    n_frames = min(max_frames, len(frames))\n",
+        "  writer = imageio.get_writer(output_path, fps=fps)\n",
+        "  for i in range(n_frames):\n",
+        "    writer.append_data(frames[i])\n",
+        "  writer.close()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 779
+        },
+        "id": "XjpxFVexV1fe",
+        "outputId": "1b55f3d0-2953-4ed2-86d9-8fed8ea060ff"
+      },
+      "outputs": [],
+      "source": [
+        "# crop example video and display it\n",
+        "convert_and_crop_video(\"arcjet_test.mp4\", \"arcjet_test_crop.mp4\", max_frames=600)\n",
+        "display_video(\"arcjet_test_crop.mp4\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Ywg0g9myV1fe",
+        "outputId": "7c54132e-4615-4209-f9f0-a5016eb4b0f6"
+      },
+      "outputs": [],
+      "source": [
+        "import arcjetCV as arcv\n",
+        "\n",
+        "video = arcv.Video(\"arcjet_test.mp4\")\n",
+        "\n",
+        "videometa = arcv.VideoMeta(video, \"arcjet_test.meta\")\n",
+        "videometa[\"FLOW_DIRECTION\"] = \"right\"\n",
+        "videometa.set_frame_crop(10, 700, 100, 425)\n",
+        "videometa[\"FIRST_GOOD_FRAME\"] = 100\n",
+        "videometa[\"LAST_GOOD_FRAME\"] = 400\n",
+        "\n",
+        "processor = arcv.ArcjetProcessor(videometa)\n",
+        "output = processor.process_all(\n",
+        "    video,\n",
+        "    options={\"SEGMENT_METHOD\": \"CNN\"},\n",
+        "    first_frame=videometa[\"FIRST_GOOD_FRAME\"],\n",
+        "    last_frame=videometa[\"LAST_GOOD_FRAME\"],\n",
+        "    frame_stride = 5,\n",
+        "    output_prefix=\"arcjet_test\",\n",
+        "    write_json = True,\n",
+        "    write_video = True\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 831
+        },
+        "id": "1S82IKEhV1ff",
+        "outputId": "edcc1295-a3b0-4f35-ecb0-ccc314f700db"
+      },
+      "outputs": [],
+      "source": [
+        "# convert annotated video from m4v to mp4 and display it\n",
+        "convert_and_crop_video(\"video_out_arcjet_test_100_400.m4v\", \"video_out_arcjet_test.mp4\")\n",
+        "display_video('video_out_arcjet_test.mp4')"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python",
+      "version": "3.12.2"
+    }
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!pip install git+https://github.com/magnus-haw/arcjetCV.git@develop -q\n",
-    "!pip install segmentation-models-pytorch -q\n",
-    "!pip install imageio[pyav] -q  # to load m4v\n",
-    "!wget https://github.com/magnus-haw/arcjetCV/raw/main/tests/arcjet_test.mp4 -q  # example video"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# functions to convert and display videos\n",
-    "from moviepy.editor import ipython_display as display_video\n",
-    "import imageio\n",
-    "def convert_and_crop_video(video_path, output_path, fps=30, max_frames=None):\n",
-    "  frames = imageio.mimread(video_path, memtest=False)\n",
-    "  if max_frames is None: \n",
-    "    n_frames = len(frames)\n",
-    "  else:\n",
-    "    n_frames = min(max_frames, len(frames))\n",
-    "  writer = imageio.get_writer(output_path, fps=fps)\n",
-    "  for i in range(n_frames):\n",
-    "    writer.append_data(frames[i])\n",
-    "  writer.close()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# crop example video and display it\n",
-    "convert_and_crop_video(\"arcjet_test.mp4\", \"arcjet_test.mp4\", max_frames=300)\n",
-    "display_video(\"arcjet_test.mp4\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import arcjetCV as arcv\n",
-    "\n",
-    "video = arcv.Video(\"arcjet_test.mp4\")\n",
-    "\n",
-    "videometa = arcv.VideoMeta(video, \"arcjet_test.meta\")\n",
-    "videometa[\"FLOW_DIRECTION\"] = \"right\"\n",
-    "videometa.set_frame_crop(30, 670, 120, 680)\n",
-    "videometa[\"FIRST_GOOD_FRAME\"] = 0\n",
-    "videometa[\"LAST_GOOD_FRAME\"] = 600\n",
-    "\n",
-    "processor = arcv.ArcjetProcessor(videometa)\n",
-    "output = processor.process_all(\n",
-    "    video, \n",
-    "    options={\"SEGMENT_METHOD\": \"CNN\"}, \n",
-    "    first_frame=videometa[\"FIRST_GOOD_FRAME\"], \n",
-    "    last_frame=videometa[\"LAST_GOOD_FRAME\"], \n",
-    "    frame_stride = 5,\n",
-    "    write_json = True,\n",
-    "    write_video = True\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# convert annotated video from m4v to mp4 and display it\n",
-    "convert_and_crop_video(\"video_out_arcjet_test.m4v\", \"video_out_arcjet_test.mp4\")\n",
-    "display_video('video_out_arcjet_test.mp4')"
-   ]
-  }
- ],
- "metadata": {
-  "language_info": {
-   "name": "python"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
+  "nbformat": 4,
+  "nbformat_minor": 0
 }