Hello guys, thank you all for everything.
The problem is that the feature vectors obtained in the onnx model are completely different from the TRT version, and I don’t know where the problem lies.
I tried several different methods, such as changing the color channel or the order of the channels (chw , whc , hcw )and how the network blob was created, but I didn’t get the right output.
Thanks for the solutions and answers. For more information, you can check this page :
opened 11:51AM - 29 Dec 24 UTC
help wanted
Hello guys, thank you all for everything.
I am trying to use the s_face face_re… cognition model in tensorRT mode :
https://github.com/opencv/opencv_zoo/tree/main/models/face_recognition_sface
To start, I checked the model with the netron tool to get the model inputs and outputs :
Now, let's compare two photos for a test :
This is my program at this address
https://github.com/sayyid-abolfazl/sface_trt
and its output is not correct
The problem is that the feature vectors obtained in the onnx model are completely different from the Nvidia TRT version, and I don't know where the problem lies.
https://github.com/opencv/opencv_zoo/blob/main/models/face_recognition_sface/demo.cpp
It should be noted that if you use the align and crop method, the results are slightly different from the case where you just send the cropped face image without alignment, but in the TRT the results are completely different.
I tried several different methods, such as changing the color channel or the order of the channels and how the network blob was created, but I didn't get the right output.
I am trying to use the model's own alignment and cropping mode and send the image with 15 facial coordinates to it, but currently the output in normal mode is completely wrong.
TensorRT Version : 8.6.1.6GPU Type : GTX1650Nvidia Driver Version : 560.35.03CUDA Version : 12.6CUDNN Version : 12.6, V12.6.20Operating System + Version : 141~20.04.1-Ubuntu