Yolov5 : Where is the ModelClass ????

[Lee-jaehyun]

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• I have searched the YOLOv5 issues and discussions and found no similar questions.

Question

Hello, Everyone!!

I have a question, so I'm writing.

In general, there are two cases when loading a trained model in PyTorch.

1. model = torch.hub.load(~~~, 'custom', path='bset.pt' , source = 'local')
   torch.save(model, "./aaa.pt")

   yolo_model = torch.load("aaa.pt") ==> This method saves and loads the entire model.

2. model = torch.hub.load(~~~, 'custom', path='bset.pt' , source = 'local')
   torch.save(model.state_dict(), "./aaa.pt")

In the above case, we know that the learned weights are loaded after defining the model class.

In general, PyTorch uses it like this:
model = TheModelClass(*args, **kwargs)
model.load_state_dict(torch.load(PATH))

How to load state_dict in YOLO???

I wonder where the model class definition is.

I'm curious about loading the model with the load_state_dict method.

Additional

Help me, plz

[iumyx2612]

Search before asking

• I have searched the YOLOv5 issues and discussions and found no similar questions.

Question

Hello, Everyone!!

I have a question, so I'm writing.

In general, there are two cases when loading a trained model in PyTorch.

1. model = torch.hub.load(~~~, 'custom', path='bset.pt' , source = 'local')
   torch.save(model, "./aaa.pt")
   yolo_model = torch.load("aaa.pt") ==> This method saves and loads the entire model.
2. model = torch.hub.load(~~~, 'custom', path='bset.pt' , source = 'local')
   torch.save(model.state_dict(), "./aaa.pt")

In the above case, we know that the learned weights are loaded after defining the model class.

In general, PyTorch uses it like this: model = TheModelClass(*args, **kwargs) model.load_state_dict(torch.load(PATH))

How to load state_dict in YOLO???

I wonder where the model class definition is.

I'm curious about loading the model with the load_state_dict method.

Additional

Help me, plz

YOLOv5 save the whole model, not just the weights and biases, see here
if you want to load the state_dict, check here
the reason for saving the model like that can be found here
if you want to know about the Model and how it's construct, check models/yolo.py, line 309

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