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import gradio as gr
from PIL import Image, ImageOps
import numpy as np
import os
import uuid
# Ensure there's a directory for outputs
os.makedirs("outputs", exist_ok=True)
def make_square(img, size=3000, fill_color=(0, 0, 0)):
x, y = img.size
scale = size / max(x, y)
new_size = (int(x * scale), int(y * scale))
# Replace deprecated ANTIALIAS with modern equivalent
img = img.resize(new_size, Image.Resampling.LANCZOS)
new_img = Image.new("RGB", (size, size), fill_color)
new_img.paste(img, ((size - new_size[0]) // 2, (size - new_size[1]) // 2))
return new_img
def blend_images(images):
if len(images) < 2:
return "Upload at least two images.", None
try:
# Add error handling for image processing
processed = []
for img in images:
try:
processed.append(make_square(Image.open(img)))
except Exception as e:
return f"Error processing image: {str(e)}", None
base = np.array(processed[0]).astype(np.float32)
for img in processed[1:]:
base = (base + np.array(img).astype(np.float32)) / 2
final = Image.fromarray(np.uint8(base))
# Save to file
output_path = f"outputs/amalgam_{uuid.uuid4().hex[:8]}.png"
final.save(output_path)
return final, output_path
except Exception as e:
return f"Error during blending: {str(e)}", None
demo = gr.Interface(
fn=blend_images,
inputs=gr.File(file_types=["image"], file_count="multiple", label="Upload 2–5 stills"),
outputs=[
gr.Image(label="Blended Image"),
gr.File(label="Download Image")
],
title="Amalgamator",
description="Upload up to 5 stills. Outputs a 3000x3000 blended image preserving the aesthetic. Save it as PNG below."
)
demo.launch() |