使用深度学习算法实现虚拟试衣镜，结合了人体姿态估计、人体分割、几何匹配和GAN，四种模型。仅仅只依赖opencv库就能运行
使用深度学习算法实现虚拟试衣，结合了人体姿态估计、人体分割、几何匹配和GAN，四种模型。仅仅只依赖opencv库就能运行
这套程序实现起来挺复杂的，因为它里面包含了4种深度学习模型，而且有一个自定义层CorrelationLayer，需要自己编程实现它。 然而我想使用onnxruntime作为推理引擎时，onnxruntime不支持自定义层的，这算是opencv的一个优势的。
本套程序的主程序文件是 main.py，模型文件从百度云盘下载， 链接：https://pan.baidu.com/s/13Eic0aiMtCGY7iigjg71DQ 提取码：xsl5
这套程序只有Python版本的，我在本地编写了C++程序，但是输出结果跟Python版本的输出结果始终不一致， 对于这个bug我还没有找到原因，因此我在github只发布python程序的。程序启动运行之后，要等几秒种后才能弹窗显示结果， 程序运行速度慢的问题还有待优化。
还有openvino是否可以支持？现在太慢了，i3 8100要30秒才能出图
5个模型文件 四个在PYCHARM 里标志是问号，且程序跑起来说模型文件不存在。求问该怎么办
首先从项目描述上看，作者能力应当很强，项目功能也很吸引人，所以尝试执行。
但下载模型后运行时，发现会报下列错误：
[ERROR:[email protected]] global /Users/xperience/actions-runner/_work/opencv-python/opencv-python/opencv/modules/dnn/src/dnn.cpp (3875) getLayerShapesRecursively OPENCV/DNN: [Permute]:(Mean/nhwc): getMemoryShapes() throws exception. inputs=1 outputs=0/1 blobs=0
[ERROR:[email protected]] global /Users/xperience/actions-runner/_work/opencv-python/opencv-python/opencv/modules/dnn/src/dnn.cpp (3878) getLayerShapesRecursively input[0] = [ 1 2 20 384 384 ]
[ERROR:[email protected]] global /Users/xperience/actions-runner/_work/opencv-python/opencv-python/opencv/modules/dnn/src/dnn.cpp (3888) getLayerShapesRecursively Exception message: OpenCV(4.5.5) /Users/xperience/actions-runner/_work/opencv-python/opencv-python/opencv/modules/dnn/src/layers/permute_layer.cpp:140: error: (-215:Assertion failed) (int)_numAxes == inputs[0].size() in function 'getMemoryShapes'
定位到 报错 出现在human_parsing.py文件的run_net()下
net.forward()这句。
猜测问题可能出在 lip_jppnet_384.pb 上，路径用的是绝对路径？
因为对onnx这些完全不熟悉，只能希望作者看到后，有空处理一下。
谢谢。
Can you provide Google drive link or any other means to download pretrained model? Thanks
cv2.error: OpenCV(4.6.0) D:\a\opencv-python\opencv-python\opencv\modules\dnn\src\layers\permute_layer.cpp:161: error: (-215:Assertion failed) (int)_numAxes == inputs[0].size() in function 'cv::dnn::PermuteLayerImpl::getMemoryShapes'
File "C:/Project/PycharmProject/virtual_try_on_use_deep_learning/main.py", line 79, in _precompute_coeffs
points = np.array([np.arange(row) + xmins[i] for i, row in enumerate(bounds[1::2])]) / filterscale
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (12,) + inhomogeneous part.
请问大佬用的opencv的版本号是多少
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