Example: Rescale File (Python only)

This example covers reading of a LayeredFile (A Photoshop file) after which we rescale all of the image data inside of it as well as any masks. Finally, we save out the file again

Relevant documentation links:

• psapi.ImageLayer_8bit

• psapi.LayeredFile_8bit

Python

# Example of replacing image data on a layer
import os
from typing import Union

import numpy as np
import cv2
import photoshopapi as psapi


def is_image_layer(layer: Union[psapi.Layer_8bit, psapi.Layer_16bit, psapi.Layer_32bit]) -> bool:
    return isinstance(layer, (psapi.ImageLayer_8bit, psapi.ImageLayer_16bit, psapi.ImageLayer_32bit))


def scale_dimensions(layer: Union[psapi.Layer_8bit, psapi.Layer_16bit, psapi.Layer_32bit], scaling_factor: float) -> None:
    """
    Apply the scaling factor to width, height, center_x and center_y of the layer
    """
    layer.width    *= scaling_factor 
    layer.height   *= scaling_factor 
    layer.center_x *= scaling_factor 
    layer.center_y *= scaling_factor


def main() -> None:
    layered_file = psapi.LayeredFile.read(os.path.join(os.path.dirname(__file__), "BaseFile.psb"))

    # Scale up our canvas, this will not change any of the image data but only prepare it for later
    scaling_factor = 2
    layered_file.width *= scaling_factor
    layered_file.height *= scaling_factor

    # Loop over all the layers in the file and rescale them
    # Note that we have to do it in the following order:
    #
    # - Extract the image data we want to process
    # - Modify the layers' width and height properties
    # - Set the Image data back on the channel
    #
    # The reason for this is that we internally use the layers' width and height to deduce and 
    # verify the numpy array's shape. 

    for layer in layered_file.flat_layers:
        new_shape = (layer.width * scaling_factor, layer.height * scaling_factor)
        if is_image_layer(layer):
            image_data = layer.get_image_data()
            scale_dimensions(layer, scaling_factor)
            for index, channel in image_data.items():

                rescaled_channel = cv2.resize(channel, new_shape, interpolation=cv2.INTER_LINEAR)
                layer[index] = rescaled_channel
        # As for image layers the image_data property will also return a mask channel we can safely 
        # apply the scaling here regardless
        elif layer.has_mask():
            mask = layer.mask
            scale_dimensions(layer, scaling_factor)
            layer.mask = cv2.resize(mask, new_shape, interpolation=cv2.INTER_LINEAR)
            
    # We can now write the scaled file back out!
    layered_file.write(os.path.join(os.path.dirname(__file__), "RescaledFile.psb"))



if __name__ == "__main__":
    main()