Hi, I have successfully used your tool to convert a custom-trained ResNet101 model from Caffe to Keras 2.2.4 with Tensorflow 1.9 backend. However, it seems that the output of the first convolutional layer is slightly different, despite the weights being loaded correctly, the padding is apparently correct and the output maps have the same size. Both input images are in BGR order.
Do you have any insight as to whether this is normal or are there differences that cannot be 100% compensated?
Hi, I have successfully used your tool to convert a custom-trained ResNet101 model from Caffe to Keras 2.2.4 with Tensorflow 1.9 backend. However, it seems that the output of the first convolutional layer is slightly different, despite the weights being loaded correctly, the padding is apparently correct and the output maps have the same size. Both input images are in BGR order.
Do you have any insight as to whether this is normal or are there differences that cannot be 100% compensated?