| """# Visualize a specific image and its label
|
| for images, labels in data_loader:
|
| sample_image = images[0] # First image in the batch
|
| sample_label = labels[0] # Corresponding label
|
| plt.imshow(sample_image.squeeze(0).numpy(), cmap='gray')
|
| plt.title(f"Label: {sample_label}")
|
| plt.show()
|
| break
|
|
|
| # Inspect image and label properties
|
| for images, labels in data_loader:
|
| print("Image batch shape:", images.shape) # Should be [batch_size, 1, 64, 64]
|
| print("Label batch shape:", labels.shape) # Should be [batch_size, 6]
|
| print("Image min:", images.min().item(), "Image max:", images.max().item()) # Values: 0.0 to 1.0
|
| print("Sample label:", labels[0]) # Check one label
|
| break
|
|
|
| # Visualize multiple samples with labels
|
| for images, labels in data_loader:
|
| for i in range(5): # Display the first 5 samples
|
| plt.imshow(images[i].squeeze(0).numpy(), cmap='gray')
|
| plt.title(f"Label: {labels[i].tolist()}")
|
| plt.show()
|
| break"""
|