Color blindness helper in Shiny Express

app.py

# Live demo at https://shinylive.io/py/app/#code=NobwRAdghgtgpmAXGKAHVA6VBPMAaMAYwHsIAXOcpMAMwCdiYACABQEkAZJgSxlWLpkmbGFADmcADoRe-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-YAakxQ24ANbA+Vc7lOush0NPUwa1VV9f1iCMOgTHUPd3QjYhSgAmM4yLYkCxQnMiXQrNizpCs6AzDCa2dRdJx7MdPhvJh2TgWxmzUTJrEIKAqiYRRUC-Y8Dj-F0AMQ2im1RIF4QXCRELDYMBObUTTS9OjUXLAAqLi9npDQyGwVFqi9PJyAADgdSiKJ+JgxSZe8FRUZVQNfD9OPYLhWgkHjF2IFIhgtJy4BxYIQNtf8w34+TnmOJ0XDIRQ6FrF03LIIZpDAABfIkgA

from PIL import Image
import numpy as np
import colorsys

from shiny import reactive, req
from shiny.express import input, render, ui

ui.input_file("file", "Image file")
ui.input_slider("hue", "Hue shift", 0, 255, 0)


@render.plot
def shifted():
    # Load the image
    image = Image.open(req(input.file())[0]["datapath"]).convert('RGB')
    
    # Convert the image to numpy array for manipulation
    image_np = np.array(image)
    
    image_hsv = np.array([colorsys.rgb_to_hsv(pixel[0]/255, pixel[1]/255, pixel[2]/255) for pixel in image_np.reshape(-1, 3)])

    # Shift hue
    image_hsv[:, 0] = (image_hsv[:, 0] + (input.hue() / 255)) % 1
    
    # Convert HSV back to RGB
    image_rgb = np.array([colorsys.hsv_to_rgb(pixel[0], pixel[1], pixel[2]) for pixel in image_hsv])
    
    # Reshape and scale up to 255
    image_rgb_reshaped = (image_rgb.reshape(image_np.shape) * 255).astype(np.uint8)
    
    # Convert numpy array back to PIL Image
    image_output = Image.fromarray(image_rgb_reshaped)

    return image_output