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Output directory #42
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Hello, i have the same problem of Claudia-hue, if someone could send me the files of the output directory, |
Weights of the trained models for segmentation and EF prediction have already been released here For example, to load the weights into the EF model: EJECTION_FRACTION_WEIGHTS_PATH = 'https://github.com/echonet/dynamic/releases/download/v1.0.0/r2plus1d_18_32_2_pretrained.pt'
weights_destination_dir = '/path/to/downloaded/weights'
model = torchvision.models.video.r2plus1d_18(pretrained=False)
model.fc = torch.nn.Linear(model.fc.in_features, 1)
device = torch.device("cuda")
model = torch.nn.DataParallel(model)
model.to(device)
checkpoint = torch.load(os.path.join(weights_destination_dir, os.path.basename(EJECTION_FRACTION_WEIGHTS_PATH)))
model.load_state_dict(checkpoint['state_dict']) |
Hi, I tried loading the pretrained model with the above script and got the following error:
I also tried running inference on the pretrained model (having put one video of the test set in the a4c-video-dir ) by using this command:
and got a similar error:
Could you maybe help me with this? What am I doing wrong? |
@chrilouk From the error message I guess there's a mismatch between the model architecture loaded from the torchvision module and the pretrained weights that you are trying to load into it. Can you please double check that you are loading the correct weights (the ones that correspond to the model architecture that you have loaded)? |
@GKalliatakis thank you for your fast response. I used 'deeplabv3_resnet50' for the segmentation and I got the same error message. Should I be using something else?
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Hello. I'm tryng to use EchoNet but I have computational problems (each epoch needs more than 5 hours), so is it possible to have the output directory? In that way, I could use the trained network to do transfer learning.
Thank you!
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