Hi,

I have a matlab file where inside there are two matrices representing 60 frame videos.

The first matrix (“data_m”) is composed of 1200 x 120 x 60, the second matrix ("ground_truth) consists of k x 60 x 4, the two matrices are linked, that is the i-th frame (data_m) corresponds to the i-th column (ground_truth). I need to be able to unpack these matrices so that I can see them as 60 single images.

This is my dataloader:

```
def __init__(self, snapshot_dir,transform):
self.snapshot_dir = snapshot_dir
self.transform = transform
def __len__(self):
return len([img for img in os.listdir(self.snapshot_dir) if img.endswith('.mat')]) * 60
def __getitem__(self, idx):
# image path
snapshot = os.path.join(self.snapshot_dir, "snapshot_n_" + str(idx+1) + ".mat")
matrix_TBD = scipy.io.loadmat(snapshot)
data_matrix = matrix_TBD.get('data_matrix')
ground_truth = matrix_TBD.get('ground_truth')
frame_size = data_matrix.shape[2]
for i in range(frame_size):
img = data_matrix[:, :, i]
target = ground_truth[:, i, :]
sample = {'image': img,
'target': target}
if self.transform:
image, target = sample['image'], sample['target']
return {'image': torch.tensor(image),
'target': torch.tensor(target)}
return sample
```

I debug to see the result

```
dataset = TBD_Dataset(snapshot_dir=snapshot_dir, transform=True)
# DEBUG: show all samples in GMM Dataset
if debug_dataset:
for i in range(len(dataset)):
sample = dataset[i]
print(i, ",",
"Image shape: ", sample['image'].shape, ",",
"target shape: ", sample['target'].shape)
```

I know this way I will only get the latest img and target but I can’t find a way to get the 60 images, can anyone help me?