I am working on different size of image dataset. While preprocessing I got this error,
RuntimeError: Error when trying to collate the data into batches with fa_collate, at least two tensors in the batch are not the same size.
Mismatch found on axis 0 of the batch and is of type Tensor:
Item at index 0 has shape: torch.Size([1, 114, 114])
Item at index 1 has shape: torch.Size([3, 161, 162])
Please include a transform in after_item that ensures all data of type Tensor is the same size
Please tell me how to solve this error as I am first time see this type error. Thank you in advance.
'''
class MTLDataset(Dataset):
def __init__(self,df, transform=None):
self.path = list(df.path)
self.age = list(df.age)
self.gender = list(df.gender)
#self.ethnicity = list(df.ethnicity)
self.transform = transform
def __len__(self):
return len(self.path)
def __getitem__(self,idx):
#image
path = self.path[idx]
image = read_image(path)
image = convert_image_dtype(image,dtype = torch.float32)
if self.transform:
image = self.transform(image)
#age,gender,ethnicity
age = self.age[idx]
gender = self.gender[idx]
#ethnicity = self.ethnicity[idx]
return image, age, gender
'''
'''
def generate_dataloader(df, transformation = None):
ds = MTLDataset(
df,
transformation
)
return DataLoader(
ds,
batch_size = 100,
num_workers = 4,
)
'''
'''
transformation = transforms.Compose([
transforms.Resize((100, 100)),
transforms.ToTensor(),
# transforms.Normalize(mean=[0.485, 0.456, 0.406],
# std=[0.229, 0.224, 0.225])
])
'''
'''
train_dataloader = generate_dataloader(train_df)
test_dataloader = generate_dataloader(test_df)
'''
'''
train_features, train_age, train_gender = next(iter(train_dataloader))
print(f"Feature batch shape: {train_features.size()}")
print(f"Feature: {train_features[0]}")
'''
This is my code. I tried to solve this error but I Couldn’t.