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av-savchenko / face-emotion-recognition

Efficient face emotion recognition in photos and videos
Apache License 2.0
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QUestion about inference #3

Closed DaddyWesker closed 3 years ago

DaddyWesker commented 3 years ago

Hello.

THanks for your code. I've tried to run your code on webcam and for that i've needed to load model properly from pretrained weights. I've took a look into your train_emotions-pytorch and sought that you're loading model as

model=timm.create_model('tf_efficientnet_b0_ns', pretrained=False)
model.classifier=torch.nn.Identity()
model.load_state_dict(torch.load('../models/pretrained_faces/state_vggface2_enet0_new.pt'))

Then you're adding model.classifier=nn.Sequential(nn.Linear(in_features=1280, out_features=num_classes)) and training your model. If i got it right, you're providing pre-trained weights at the models/affectnet_emotions folder. But question is, how to load them? I've thought it should be something like this 

model=timm.create_model('tf_efficientnet_b0_ns', pretrained=False)
model.classifier=nn.Sequential(nn.Linear(in_features=1280, out_features=8))
model.load_state_dict(torch.load('../models/affectnet_emotions/enet_b0_8_best_afew.pt'))

But no, i've got an error. AttributeError: 'EfficientNet' object has no attribute 'copy'. So my guess is wrong then. Should i load it some different way? THanks in advance.

av-savchenko commented 3 years ago

You do not need to create emotion model from scratch. Please try to load the whole model using the following code model = torch.load('../models/affectnet_emotions/enet_b0_8_best_afew.pt') model.eval()

There is an example in file train_emotions-pytorch.ipynb, where similar code is used but variable PATH is used

вт, 3 авг. 2021 г., 10:42 DaddyWesker @.***>:

Hello.

THanks for your code. I've tried to run your code on webcam and for that i've needed to load model properly from pretrained weights. I've took a look into your train_emotions-pytorch and sought that you're loading model as

model=timm.create_model('tf_efficientnet_b0_ns', pretrained=False) model.classifier=torch.nn.Identity() model.load_state_dict(torch.load('../models/pretrained_faces/state_vggface2_enet0_new.pt'))

Then you're adding model.classifier=nn.Sequential(nn.Linear(in_features=1280, out_features=num_classes)) and training your model. If i got it right, you're providing pre-trained weights at the models/affectnet_emotions folder. But question is, how to load them? I've thought it should be something like this

model=timm.create_model('tf_efficientnet_b0_ns', pretrained=False) model.classifier=nn.Sequential(nn.Linear(in_features=1280, out_features=8)) model.load_state_dict(torch.load('../models/affectnet_emotions/enet_b0_8_best_afew.pt'))

But no, i've got an error. AttributeError: 'EfficientNet' object has no attribute 'copy'. So my guess is wrong then. Should i load it some different way? THanks in advance.

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DaddyWesker commented 3 years ago

Hm. THanks. It works. Strange, i thought it won't work without model class with just "torch.load". But i guess i won't comply about that =)