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My implementation for the paper Context-Aware Emotion Recognition Networks
I want to plot the architecture diagram of CAERnet can you please help me in doing so? I am unable to figure out what input dimensions should be passed for the model right now I am using this:
model1 = CAERSNet(context=True,context_attention=True,fusion_attention=True)
h1 = hl.build_graph(model1,torch.Tensor(1,3,224,224))
##hl is hiddenlayer library
The error I am getting is this
face_size, context_size = face.shape[2], context.shape[2]
AttributeError: 'NoneType' object has no attribute 'shape'
PLease help
thank you
Hello author! Serious overfitting occurred during training. The training accuracy reached more than 90%, while the verification accuracy and test accuracy were only a little more than 70%. What is the reason for this? Thank you
hi,
I try to download datasets of CAER-S to train,but its so big.
Could you share the model you pre-trained.
Thanks
Hello author, if I use GPU for training, do I directly input it on the command line: python train.py --config config.json, other things do not need to be modified?
Hello, do you know the hyperparameter settings of the original paper?
Hello!,Could you fix the results of dlib's cnn detector for the training set and test set?thank you so much! Meanwhile,Could you upload your trained models?
Hi!
The links for downloading dlib's cnn detector results are offline. Could you please fix them? Thank you
thanks a lot of your implementation, I'm having some problems about the res of caer , so could you please share your res in this implementation?
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