Index Error

[Manasa-3]

IndexError Traceback (most recent call last) in <cell line: 65>() 63 64 # Initialize Model, Loss Function, and Optimizer ---> 65 model = smp.Unet( 66 'resnet34', 67 encoder_weights=None,

7 frames /usr/local/lib/python3.10/dist-packages/keras/src/layers/normalization/batch_normalization.py in build(self, input_shape) 168 169 def build(self, input_shape): --> 170 shape = (input_shape[self.axis],) 171 if self.scale: 172 self.gamma = self.add_weight(

IndexError: tuple index out of range. Please help me out for this error, My image is of shape (256,128,128)

[ZFTurbo]

Can you post your code at line 65 and a bit after?

[Manasa-3]

train_loader = DataLoader(train_dataset, batch_size=2, shuffle=True, collate_fn=custom_collate_fn, pin_memory=True) print(f"Number of workers: {train_loader.num_workers}") test_loader = DataLoader(test_dataset, batch_size=2, shuffle=False, collate_fn=custom_collate_fn, pin_memory=True) val_loader = DataLoader(val_dataset, batch_size=2, shuffle=False, collate_fn=custom_collate_fn, pin_memory=True)

model = smp.Unet( 'resnet34', encoder_weights=None, input_shape=image.shape )

criterion = nn.MSELoss() optimizer = Adam(model.parameters(), lr=0.001)

num_epochs = 10 # Define the number of epochs

scaler = GradScaler() for epoch in range(num_epochs): model.train()
running_loss = 0.0 for batch_idx, (images, masks) in enumerate(train_loader): images, masks = images.to(device), masks.to(device) images = images.unsqueeze(0)
optimizer.zero_grad()

    with autocast():
        outputs = model(images)
        loss = criterion(outputs, masks)

    # Scale the loss and call backward
    scaler.scale(loss).backward()

    # Unscales the gradients and calls optimizer.step
    scaler.step(optimizer)

    # Updates the scale for next iteration
    scaler.update()

    running_loss += loss.item()
    if True:  # Always true, so this block runs for every batch
      print(f"Epoch [{epoch+1}/{num_epochs}], Batch [{batch_idx+1}/{len(train_loader)}], Loss: {running_loss/(batch_idx+1):.4f}")
      running_loss = 0.0
      gc.collect()

This is the code from line 65...

[ZFTurbo]

What's value of image.shape?

[ZFTurbo]

From example:

# If you need to specify non-standard input shape
model5 = sm.Unet(
    'resnet50', 
    input_shape=(96, 128, 128, 6), 
    encoder_weights=None
)

It must be 4 numbers: (W, H, D, C)

[Manasa-3]

okay thankyou, I'll check it out.