Function load_image

utils/utils.py:10–34

Load an image, preprocess it, and prepare it for use in a deep learning model. Parameters: image_path (str): The file path to the image. device (torch.device): The PyTorch device (CPU or GPU) on which the image should be loaded. Returns: torch.Tensor: A PyTorch

(image_path, device)

from matplotlib import cm

def load_image(image_path, device):
    """
    Load an image, preprocess it, and prepare it for use in a deep learning model.

    Parameters:
        image_path (str): The file path to the image.
        device (torch.device): The PyTorch device (CPU or GPU) on which the image should be loaded.

    Returns:
        torch.Tensor: A PyTorch tensor representing the preprocessed image.

    Example:
        >>> image = load_image('example.jpg', device='cuda')
    """
    # Load the image
    image = read_image(image_path)  # You should have a read_image function to load the image

    # Preprocess the image
    image = image[:3].unsqueeze_(0).float() / 127.5 - 1.  # Normalize pixel values to the range [-1, 1]
    image = F.interpolate(image, (512, 512))  # Resize the image to a specified size

    # Move the preprocessed image to the specified PyTorch device
    image = image.to(device)

    return image

def load_mask(mask_path, device, size=(128, 128), mode='nearest'):
    """