I am using the NCS2 for inference of the popular FACENET CNN for face recognition. I have observed that when I use the model on the NCS2, I get a decreased accuracy as compared to Tensorflow output. Is this normal? To have a fair comparison, I gave the same input images to the model on both platforms.
I thought that the performance of a model should remain the same on NCS as it was on the other platform (Tensorflow in my case). Is there some optimization that needs to be done in order to get the identical performance?
Thanks in Advance.
I've tested your code and model, the performance of CPU and VPU are better than tensorflow run on CPU. Also I can't see the accuracy drop issue, can you let me know how do you compare the result accuracy between tf and OpenVINO?
I am giving the same image as input to both the scripts (tensorflow and VCS2) and compare the output of the model. I am attaching here the out put of the same model via tensorflow and openVino NCS2.
front_face.jpg (u'khushboo', 82.0228824217682)
face_2.jpg (u'khushboo', 70.19255365615679)
face_3.jpg ('Unknown', 54.716366131550984)
Front_face.jpg [('khushboo', 79.44055289492539)]
face_2.jpg [('khushboo', 70.27896715998985)]
face_side.jpg [('khushboo', 75.9920282922568)]
face_3.jpg [('Unknown', 54.853669788701346)]
Is there any format difference between the images of face_2.jpg and face_side.jpg? I am able to execute the python file with "face_2.jpg" or "face_3.jpg" but when I try to test with "face_side.jpg" and "front_face.jpg", openCV throw out the error as attached. Have you encountered this problem before?
No they should have the same format. I have never encountered this problem before. I also tried but so far I haven't got this error. Are you trying with tensorflow or the intel stick code?