Sasan Asadiabadi

could you fix this issue? have the same problem with OpenCV4.3.0

are all the models (face detection, landmarking and gaze detection) based on mobilenet-v3?

Great thanks. I was wondering if its possible to share the pytorch pre-trained weights as well. I'm trying to run the codes in opencv dnn module instead of onnxruntime. current...

Thanks for sharing the files. I was able to convert the models and run them in opencv's dnn module. fps seems to be quite similar with both onnxruntime and dnn...

I converted the pytorch weights to onnx and using cv2.dnn.readNetFromONNX() with opencv 4.3 version I could run the inference (no other change to your original code). But the outputs of...

yeah the problem was because of align_corners=True in nn.Upsample layer. dnn module is not supporting it yet somehow. therefore needs to set False for inference in dnn module. I will...

Finally solved. Thanks for pointing out the problem. with align_corners=True, converting from pytorch with onnx opset 11 and re-building opencv master (4.3.0-dev), the dnn module returns similar predictions as onnxruntime....

Great! However the landmarking looks very robust to various occlusion and illumination types, I think the pupil detection can be improved. As you are not planning to release the training...

no doubt about its decent performance. I just found poor performance on some challenging cases such as extreme glass reflections and outside sunny environments, which is mainly due to the...

Actually I tried a HG network (2 stacks) to train the pupil detector on the UnityEye set (with lots of augmentation) but it didn't improve much on my test set....