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echonet / dynamic

EchoNet-Dynamic is a deep learning model for assessing cardiac function in echocardiogram videos.
https://echonet.github.io/dynamic
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External test #35

Closed gt-madanb closed 3 years ago

gt-madanb commented 3 years ago

I am trying to run on an Initialization notebook with external test videos which is already in avi format.

RuntimeError: Caught RuntimeError in DataLoader worker process 0. Original Traceback (most recent call last): File "C:\Users\MadanB\anaconda3\lib\site-packages\torch\utils\data_utils\worker.py", line 202, in _worker_loop data = fetcher.fetch(index) File "C:\Users\MadanB\anaconda3\lib\site-packages\torch\utils\data_utils\fetch.py", line 47, in fetch return self.collate_fn(data) File "C:\Users\MadanB\anaconda3\lib\site-packages\torch\utils\data_utils\collate.py", line 83, in default_collate return [default_collate(samples) for samples in transposed] File "C:\Users\MadanB\anaconda3\lib\site-packages\torch\utils\data_utils\collate.py", line 83, in return [default_collate(samples) for samples in transposed] File "C:\Users\MadanB\anaconda3\lib\site-packages\torch\utils\data_utils\collate.py", line 63, in default_collate return default_collate([torch.as_tensor(b) for b in batch]) File "C:\Users\MadanB\anaconda3\lib\site-packages\torch\utils\data_utils\collate.py", line 55, in default_collate return torch.stack(batch, 0, out=out) RuntimeError: stack expects each tensor to be equal size, but got [3, 16, 472, 636] at entry 0 and [3, 16, 600, 800] at entry

douyang commented 3 years ago

AVIs need to be resized, model expects 112x112 videos.

gt-madanb commented 2 years ago

AVIs need to be resized, model expects 112x112 videos.

when I try to test the video from dynamic dataset, I got the following error

loading weights from D:\stanford_AIMI\weights\r2plus1d_18_32_2_pretrained cuda is not available, cpu weights EXTERNAL_TEST ['0X1A58B506ED05C1D4.avi'] 100%|████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:02<00:00, 2.83s/it]

TypeError Traceback (most recent call last)

in 49 50 test_dataloader = torch.utils.data.DataLoader(ds, batch_size = 1, num_workers = 5, shuffle = True, pin_memory=(device.type == "cuda")) ---> 51 loss, yhat, y = echonet.utils.video.run_epoch(model, test_dataloader, "test", None, device, save_all=True)#, blocks=25) 52 53 with open(output, "w") as g: ~\dynamic-master\echonet\utils\video.py in run_epoch(model, dataloader, train, optim, device, save_all, block_size) 312 y = [] 313 --> 314 with torch.set_grad_enabled(train): 315 with tqdm.tqdm(total=len(dataloader)) as pbar: 316 for (X, outcome) in dataloader: ~\anaconda3\lib\site-packages\torch\autograd\grad_mode.py in __init__(self, mode) 200 def __init__(self, mode: bool) -> None: 201 self.prev = torch.is_grad_enabled() --> 202 torch._C._set_grad_enabled(mode) 203 204 def __enter__(self) -> None: TypeError: enabled must be a bool (got str)