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您好,我是一名本科的学生,最近在研究rcnn这方面的东西,我之前已经使用过caffe训练过cnn的模型,目前想clone您的代码学习一下rcnn,因为之前训练都是在Intel的devcloud上进行的,所以在本地都是用CPU训练一些小的数据集(本人机器为mac),所以我想问一下您们README上的demo是一定要在支持CUDA驱动的gpu环境的才能运行吗?因为我在mac运行(有CUDA环境但不支持NVDIA的gpu驱动)会报错。
报错信息如下:
nms/gpu_nms.cpp:2074:3: error: no matching function for call to '_nms'
_nms((&(*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int32_t *, __pyx_pybuffernd_keep.rcbuffer->pybuffer.buf, __pyx_t_10, __pyx_pybuffernd_keep.diminfo[0].strides))), (&__pyx_v_num_out), (&(...
^~~~
nms/gpu_nms.hpp:1:6: note: candidate function not viable: no known conversion from '__pyx_t_5numpy_int32_t ' (aka 'long ') to 'int ' for 1st argument
void _nms(int keep_out, int num_out, const float boxes_host, int boxes_num,
您好,我是一名本科的学生,最近在研究rcnn这方面的东西,我之前已经使用过caffe训练过cnn的模型,目前想clone您的代码学习一下rcnn,因为之前训练都是在Intel的devcloud上进行的,所以在本地都是用CPU训练一些小的数据集(本人机器为mac),所以我想问一下您们README上的demo是一定要在支持CUDA驱动的gpu环境的才能运行吗?因为我在mac运行(有CUDA环境但不支持NVDIA的gpu驱动)会报错。
报错信息如下:
nms/gpu_nms.cpp:2074:3: error: no matching function for call to '_nms'
_nms((&(*__Pyx_BufPtrStrided1d(__pyx_t_5numpy_int32_t *, __pyx_pybuffernd_keep.rcbuffer->pybuffer.buf, __pyx_t_10, __pyx_pybuffernd_keep.diminfo[0].strides))), (&__pyx_v_num_out), (&(...
^~~~
nms/gpu_nms.hpp:1:6: note: candidate function not viable: no known conversion from '__pyx_t_5numpy_int32_t ' (aka 'long ') to 'int ' for 1st argument
void _nms(int keep_out, int num_out, const float boxes_host, int boxes_num,
看上去像是gpu驱动的问题。
所以我想请教您,是不是你们测试的demo只能在支持CUDA的gpu环境下才能make成功?
万分感谢。
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