Create app.py

app.py

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+import gradio as gr
+from PIL import Image, ImageStat
+import numpy as np
+import os
+import math
+import shutil
+import random
+
+def get_dominant_color(image):
+    """Get the dominant color of an image or return None."""
+    try:
+        stat = ImageStat.Stat(image)
+        r, g, b = stat.mean[:3]
+        return int(r), int(g), int(b)
+    except:
+        return None
+
+def resize_and_pad(image, target_size):
+    """Resize the image and pad it to match target size."""
+    img = image.convert("RGB")
+    aspect_ratio = img.width / img.height
+    target_aspect_ratio = target_size[0] / target_size[1]
+
+    if aspect_ratio > target_aspect_ratio:
+        # Wider than target aspect ratio
+        new_width = target_size[0]
+        new_height = int(new_width / aspect_ratio)
+    else:
+        # Taller than target aspect ratio
+        new_height = target_size[1]
+        new_width = int(new_height * aspect_ratio)
+
+    img = img.resize((new_width, new_height), Image.ANTIALIAS)
+
+    # Determine padding color
+    dominant_color = get_dominant_color(img)
+    if dominant_color is None:
+        dominant_color = (255, 255, 255) if random.choice([True, False]) else (0, 0, 0)
+
+    # Create a new image with the determined background color
+    new_img = Image.new("RGB", target_size, dominant_color)
+    offset = ((target_size[0] - new_width) // 2, (target_size[1] - new_height) // 2)
+    new_img.paste(img, offset)
+    return new_img
+
+def combine_images(images, target_size=(2048, 2048)):
+    """Combine four images into a single one."""
+    num_images = len(images)
+    output_images = []
+
+    # Group images into chunks of 4
+    for i in range(0, num_images, 4):
+        group = images[i:i+4]
+        if len(group) < 4:
+            continue
+
+        # Resize and pad each image
+        resized_images = [resize_and_pad(img, (512, 512)) for img in group]
+
+        # Create a blank canvas
+        combined_img = Image.new("RGB", (1024, 1024), (0, 0, 0))
+        combined_img.paste(resized_images[0], (0, 0))
+        combined_img.paste(resized_images[1], (512, 0))
+        combined_img.paste(resized_images[2], (0, 512))
+        combined_img.paste(resized_images[3], (512, 512))
+
+        # Resize if the final size exceeds target
+        if combined_img.width > target_size[0] or combined_img.height > target_size[1]:
+            combined_img = combined_img.resize(target_size, Image.ANTIALIAS)
+
+        output_images.append(combined_img)
+
+    return output_images
+
+def process_images(uploaded_images):
+    """Main processing function."""
+    images = [Image.open(img) for img in uploaded_images]
+    combined_images = combine_images(images)
+    result_paths = []
+
+    # Save combined images
+    output_dir = "output_images"
+    os.makedirs(output_dir, exist_ok=True)
+    for idx, img in enumerate(combined_images):
+        output_path = os.path.join(output_dir, f"combined_{idx + 1}.png")
+        img.save(output_path)
+        result_paths.append(output_path)
+
+    # Create a ZIP file
+    zip_path = "combined_images.zip"
+    shutil.make_archive("combined_images", 'zip', output_dir)
+
+    return zip_path
+
+# Gradio UI
+interface = gr.Interface(
+    fn=process_images,
+    inputs=gr.inputs.File(file_types=[".png", ".jpg", ".jpeg"], label="Upload Images", type="file", multi=True),
+    outputs=gr.outputs.File(label="Download ZIP"),
+    title="Image Resizer and Combiner",
+    description="Upload multiple images. This tool will resize and pad them to match a consistent size, then combine every four images into one. The output will be resized if it exceeds 2048x2048, and all results are available as a ZIP file."
+)
+
+interface.launch()