Coolcy

@ericj974 I tested your model with `coco_weights` and `image net weights`, however I got the errors: `ValueError: Layer #9 (named "res2a_branch2b") expects 0 weight(s), but the saved weights have 2...

@Cpruce Hello I saw your implementation of maskRcnn with mobilenet224 backbone, very interesting! Do you think it's possible to integrate the model into mobile devices for inference ? (like mobilenet...

@Cpruce When you test with your phone, it's with Android studio or Xcode that you integrate your *.pb ?( I guess that you have to convert .h5 to .pb). I...

@Cpruce Sorry for reply so late.. In fact I have tested with TF DETECT and TF CLASSIFIER, which finally worked( I made a stupid error before..). But the fact is...

@ericj974 I have a problem of the resneXt network. In fact I have already trained a model with resneXt and convert .h5 to .pb successfully.(with your file **export_model.py**) . But...

In my case I used my own data set to do training. At first I took `train.py` then the loss went down very very very slowly (from 10 to 8...

@jannctu Thanks a lot to point it out. I would like to ask you if you have already tested the original implementation (caffe framework)? If so, I wonder if you...

@jannctu Thanks a lot I will check this.

I found the solution: instead to downgrade pytorch to 0.2, you can filter the keys by ignoring `num_batches_tracked` ``` feature_extraction_dict = {k: v for k, v in self.model_aff.FeatureExtraction.state_dict().items() if 'num_batches_tracked'...