add app

app.py

@@ -0,0 +1,133 @@
+import os
+import zipfile
+import shutil
+from PIL import Image
+import io
+from rembg import remove
+import gradio as gr
+
+def resize_and_crop_image(image_path, target_size=(1080, 1080), crop_mode='center'):
+    with Image.open(image_path) as img:
+        width, height = img.size
+
+        # Calculate the scaling factor
+        scaling_factor = max(target_size[0] / width, target_size[1] / height)
+
+        # Resize the image with high-quality resampling
+        new_size = (int(width * scaling_factor), int(height * scaling_factor))
+        resized_img = img.resize(new_size, Image.LANCZOS)
+
+        if crop_mode == 'center':
+            left = (resized_img.width - target_size[0]) / 2
+            top = (resized_img.height - target_size[1]) / 2
+        elif crop_mode == 'top':
+            left = (resized_img.width - target_size[0]) / 2
+            top = 0
+        elif crop_mode == 'bottom':
+            left = (resized_img.width - target_size[0]) / 2
+            top = resized_img.height - target_size[1]
+        elif crop_mode == 'left':
+            left = 0
+            top = (resized_img.height - target_size[1]) / 2
+        elif crop_mode == 'right':
+            left = resized_img.width - target_size[0]
+            top = (resized_img.height - target_size[1]) / 2
+
+        right = left + target_size[0]
+        bottom = top + target_size[1]
+
+        # Crop the image
+        cropped_img = resized_img.crop((left, top, right, bottom))
+
+        return cropped_img
+
+def remove_background(input_path):
+    with open(input_path, 'rb') as i:
+        input_image = i.read()
+    output_image = remove(input_image)
+    img = Image.open(io.BytesIO(output_image)).convert("RGBA")
+    return img
+
+def process_images(zip_file, crop_mode='center', remove_bg='yes', progress=gr.Progress()):
+    # Create a temporary directory
+    input_folder = "temp_input"
+    output_folder = "temp_output"
+    if os.path.exists(input_folder):
+        shutil.rmtree(input_folder)
+    if os.path.exists(output_folder):
+        shutil.rmtree(output_folder)
+    os.makedirs(input_folder)
+    os.makedirs(output_folder)
+    
+    # Extract the zip file
+    with zipfile.ZipFile(zip_file, 'r') as zip_ref:
+        zip_ref.extractall(input_folder)
+    
+    processed_images = []
+    image_files = [f for f in os.listdir(input_folder) if f.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif'))]
+    total_images = len(image_files)
+    for idx, filename in enumerate(image_files):
+        image_path = os.path.join(input_folder, filename)
+        try:
+            if remove_bg == 'yes':
+                # Remove background
+                image_with_no_bg = remove_background(image_path)
+                temp_image_path = os.path.join(output_folder, f"temp_{filename}")
+                image_with_no_bg.save(temp_image_path, format='PNG')
+            else:
+                temp_image_path = image_path
+
+            # Resize and crop the image with or without background removal
+            new_image = resize_and_crop_image(temp_image_path, crop_mode=crop_mode)
+
+            # Save the final image
+            output_path = os.path.join(output_folder, f"{os.path.splitext(filename)[0]}.png")
+            new_image.save(output_path, format='PNG')
+
+            processed_images.append(output_path)
+
+            if remove_bg == 'yes':
+                # Remove the temporary file
+                os.remove(temp_image_path)
+
+            # Update progress
+            progress((idx + 1) / total_images, f"{idx + 1}/{total_images} images processed")
+
+        except Exception as e:
+            print(f"Error processing {filename}: {e}")
+    
+    # Create a zip file of the processed images
+    output_zip_path = "processed_images.zip"
+    with zipfile.ZipFile(output_zip_path, 'w') as zipf:
+        for file in processed_images:
+            zipf.write(file, os.path.basename(file))
+    
+    # Return the images and the zip file path
+    return processed_images, output_zip_path
+
+def gradio_interface(zip_file, crop_mode, remove_bg):
+    progress = gr.Progress()  # Initialize progress
+    return process_images(zip_file.name, crop_mode, remove_bg, progress)
+
+# Create the Gradio interface
+with gr.Blocks() as iface:
+    gr.Markdown("# Image Background Removal and Resizing")
+    gr.Markdown("Upload a ZIP or RAR file containing images, choose the crop mode, and get the processed images.")
+    
+    with gr.Row():
+        zip_file = gr.File(label="Upload ZIP/RAR file of images", file_types=[".zip", ".rar"])
+        crop_mode = gr.Radio(choices=["center", "top", "bottom", "left", "right"], label="Crop Mode", value="center")
+        remove_bg = gr.Radio(choices=["yes", "no"], label="Remove Background", value="yes")
+
+    gallery = gr.Gallery(label="Processed Images")
+    output_zip = gr.File(label="Download Processed Images as ZIP")
+
+    def process(zip_file, crop_mode, remove_bg):
+        processed_images, zip_path = gradio_interface(zip_file, crop_mode, remove_bg)
+        return processed_images, zip_path
+
+    process_button = gr.Button("Process Images")
+    process_button.click(process, inputs=[zip_file, crop_mode, remove_bg], outputs=[gallery, output_zip])
+
+# Launch the interface
+iface.launch()

requirements.txt

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+gradio==4.37.2
+Pillow==10.4.0
+rembg==2.0.57