blurhash

import os from PIL import Image from blurhash import encode, decode # 1. Create a dummy image for demonstration width, height = 32, 32 img = Image.new('RGBA', (width, height), color = 'red') img.putpixel((0, 0), (0, 255, 0, 255)) # Green pixel at top-left img.putpixel((width-1, height-1), (0, 0, 255, 255)) # Blue pixel at bottom-right # Prepare image data for blurhash (flat list of RGBA values) # The library expects pixel data as a flat list, not a Pillow Image object directly. # If your image is RGB, you might need to convert it to RGBA first. pixel_data = [] for y in range(height): for x in range(width): r, g, b, a = img.getpixel((x, y)) pixel_data.extend([r, g, b, a]) # 2. Encode the image x_components = 4 # How many color components horizontally y_components = 3 # How many color components vertically blurhash_string = encode(pixel_data, width, height, x_components, y_components) print(f"Generated BlurHash: {blurhash_string}") # 3. Decode the blurhash string back into pixel data output_width = 160 output_height = 90 decoded_pixels = decode(blurhash_string, output_width, output_height) # 4. Reconstruct image from decoded pixels (using Pillow) decoded_img = Image.new('RGBA', (output_width, output_height)) decoded_img.putdata(list(zip(*[iter(decoded_pixels)]*4))) # 5. Save the original and decoded images original_path = 'original_image.png' decoded_path = 'decoded_blurhash.png' img.save(original_path) decoded_img.save(decoded_path) print(f"Original image saved to {original_path}") print(f"Decoded blurhash image saved to {decoded_path}") # Clean up (optional) # os.remove(original_path) # os.remove(decoded_path)