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| from PIL import Image | |
| import torchvision.transforms as transforms | |
| IMAGE_SHAPE = (200, 200) | |
| def transform_image(image_path): | |
| """ | |
| Loads, transforms, and prepares the image for the model. | |
| Args: | |
| image_path (str): Path to the image. | |
| Returns: | |
| torch.Tensor: Transformed image ready for the model. | |
| """ | |
| transform = transforms.Compose([ | |
| transforms.Resize(IMAGE_SHAPE), | |
| transforms.RandomHorizontalFlip(), | |
| transforms.RandomRotation(degrees=10), | |
| transforms.ToTensor(), | |
| ]) | |
| image = Image.open(image_path).convert('RGB') | |
| image = transform(image) | |
| image = image.unsqueeze(0) # Add batch dimension | |
| return image |