res for each web

app-v2.py

@@ -0,0 +1,560 @@
+import os
+import zipfile
+import shutil
+import time
+from PIL import Image, ImageDraw
+import io
+from rembg import remove
+import gradio as gr
+from concurrent.futures import ThreadPoolExecutor
+from transformers import pipeline
+import numpy as np
+import json
+import os
+
+def remove_background_rembg(input_path):
+    print(f"Removing background using rembg for image: {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 remove_background_bria(input_path):
+    print(f"Removing background using bria for image: {input_path}")
+    pipe = pipeline("image-segmentation", model="briaai/RMBG-1.4", trust_remote_code=True, device=0)
+    pillow_image = pipe(input_path)
+    return pillow_image
+
+def get_bounding_box_with_threshold(image, threshold):
+    # Convert image to numpy array
+    img_array = np.array(image)
+    
+    # Get alpha channel
+    alpha = img_array[:,:,3]
+    
+    # Find rows and columns where alpha > threshold
+    rows = np.any(alpha > threshold, axis=1)
+    cols = np.any(alpha > threshold, axis=0)
+    
+    # Find the bounding box
+    top, bottom = np.where(rows)[0][[0, -1]]
+    left, right = np.where(cols)[0][[0, -1]]
+    
+    if left < right and top < bottom:
+        return (left, top, right, bottom)
+    else:
+        return None
+
+def position_logic(image_path, use_threshold=True):
+    image = Image.open(image_path)
+    image = image.convert("RGBA")
+    
+    # Get the bounding box of the non-blank area with threshold
+    if use_threshold:
+        bbox = get_bounding_box_with_threshold(image, threshold=10)
+    else:
+        bbox = image.getbbox()
+    log = []
+
+    if bbox:
+        # Check 1 pixel around the image for non-transparent pixels
+        width, height = image.size
+        cropped_sides = []
+        
+        # Define tolerance for transparency
+        tolerance = 30  # Adjust this value as needed
+        
+        # Check top edge
+        if any(image.getpixel((x, 0))[3] > tolerance for x in range(width)):
+            cropped_sides.append("top")
+        
+        # Check bottom edge
+        if any(image.getpixel((x, height-1))[3] > tolerance for x in range(width)):
+            cropped_sides.append("bottom")
+        
+        # Check left edge
+        if any(image.getpixel((0, y))[3] > tolerance for y in range(height)):
+            cropped_sides.append("left")
+        
+        # Check right edge
+        if any(image.getpixel((width-1, y))[3] > tolerance for y in range(height)):
+            cropped_sides.append("right")
+        
+        if cropped_sides:
+            info_message = f"Info for {os.path.basename(image_path)}: The following sides of the image may contain cropped objects: {', '.join(cropped_sides)}"
+            print(info_message)
+            log.append({"info": info_message})
+        else:
+            info_message = f"Info for {os.path.basename(image_path)}: The image is not cropped."
+            print(info_message)
+            log.append({"info": info_message})
+        
+        # Crop the image to the bounding box
+        image = image.crop(bbox)
+        log.append({"action": "crop", "bbox": [str(bbox[0]), str(bbox[1]), str(bbox[2]), str(bbox[3])]})
+        
+        # Calculate the new size to expand the image
+        padding = 125
+        target_size = 1080
+        aspect_ratio = image.width / image.height
+        
+        if len(cropped_sides) == 4:
+            # If the image is cropped on all sides, center crop it to fit the canvas
+            if aspect_ratio > 1:  # Landscape
+                new_height = target_size
+                new_width = int(new_height * aspect_ratio)
+                left = (new_width - target_size) // 2
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                image = image.crop((left, 0, left + target_size, target_size))
+            else:  # Portrait or square
+                new_width = target_size
+                new_height = int(new_width / aspect_ratio)
+                top = (new_height - target_size) // 2
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                image = image.crop((0, top, target_size, top + target_size))
+            log.append({"action": "center_crop_resize", "new_size": f"{target_size}x{target_size}"})
+            x, y = 0, 0
+        elif not cropped_sides:
+            # If the image is not cropped, expand it from center until it touches the padding
+            new_height = 1080 - 2 * padding  # Ensure it touches top and bottom padding
+            new_width = int(new_height * aspect_ratio)
+            
+            if new_width > 1080 - 2 * padding:
+                # If width exceeds available space, adjust based on width
+                new_width = 1080 - 2 * padding
+                new_height = int(new_width / aspect_ratio)
+            
+            # Resize the image
+            image = image.resize((new_width, new_height), Image.LANCZOS)
+            log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+            
+            x = (1080 - new_width) // 2
+            y = 1080 - new_height - padding
+        else:
+            # New logic for handling cropped top and left, or top and right
+            if set(cropped_sides) == {"top", "left"} or set(cropped_sides) == {"top", "right"}:
+                new_height = target_size - padding  # Ensure bottom padding
+                new_width = int(new_height * aspect_ratio)
+                
+                # If new width exceeds canvas width, adjust based on width
+                if new_width > target_size:
+                    new_width = target_size
+                    new_height = int(new_width / aspect_ratio)
+                
+                # Resize the image
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                # Set position
+                if "left" in cropped_sides:
+                    x = 0
+                else:  # right in cropped_sides
+                    x = target_size - new_width
+                y = 0
+                
+                # If the resized image is taller than the canvas minus padding, crop from the bottom
+                if new_height > target_size - padding:
+                    crop_bottom = new_height - (target_size - padding)
+                    image = image.crop((0, 0, new_width, new_height - crop_bottom))
+                    new_height = target_size - padding
+                    log.append({"action": "crop_vertical", "bottom_pixels_removed": str(crop_bottom)})
+                
+                log.append({"action": "position", "x": str(x), "y": str(y)})
+            elif set(cropped_sides) == {"bottom", "left"} or set(cropped_sides) == {"bottom", "right"}:
+                # Handle bottom & left or bottom & right cropped images
+                new_height = target_size - padding  # Ensure top padding
+                new_width = int(new_height * aspect_ratio)
+                
+                # If new width exceeds canvas width, adjust based on width
+                if new_width > target_size - padding:
+                    new_width = target_size - padding
+                    new_height = int(new_width / aspect_ratio)
+                
+                # Resize the image without cropping or stretching
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                # Set position
+                if "left" in cropped_sides:
+                    x = 0
+                else:  # right in cropped_sides
+                    x = target_size - new_width
+                y = target_size - new_height
+                
+                log.append({"action": "position", "x": str(x), "y": str(y)})
+            elif set(cropped_sides) == {"bottom", "left", "right"}:
+                # Expand the image from the center
+                new_width = target_size
+                new_height = int(new_width / aspect_ratio)
+                
+                if new_height < target_size:
+                    new_height = target_size
+                    new_width = int(new_height * aspect_ratio)
+                
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                
+                # Crop to fit the canvas
+                left = (new_width - target_size) // 2
+                top = 0
+                image = image.crop((left, top, left + target_size, top + target_size))
+                
+                log.append({"action": "expand_and_crop", "new_size": f"{target_size}x{target_size}"})
+                x, y = 0, 0
+            elif cropped_sides == ["top"]:
+                # New logic for handling only top-cropped images
+                if image.width > image.height:
+                    new_width = target_size
+                    new_height = int(target_size / aspect_ratio)
+                else:
+                    new_height = target_size - padding  # Ensure bottom padding
+                    new_width = int(new_height * aspect_ratio)
+                
+                # Resize the image
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                x = (1080 - new_width) // 2
+                y = 0  # Align to top
+                
+                # Apply padding only to non-cropped sides
+                x = max(padding, min(x, 1080 - new_width - padding))
+            elif cropped_sides in [["right"], ["left"]]:
+                # New logic for handling only right-cropped or left-cropped images
+                if image.width > image.height:
+                    new_width = target_size - padding  # Ensure padding on non-cropped side
+                    new_height = int(new_width / aspect_ratio)
+                else:
+                    new_height = target_size - (2 * padding)  # Ensure top and bottom padding
+                    new_width = int(new_height * aspect_ratio)
+                
+                # Resize the image
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                if cropped_sides == ["right"]:
+                    x = 1080 - new_width  # Align to right
+                else:  # cropped_sides == ["left"]
+                    x = 0  # Align to left
+                y = 1080 - new_height - padding  # Respect bottom padding
+                
+                # Ensure top padding is respected
+                if y < padding:
+                    y = padding
+                    
+                log.append({"action": "position", "x": str(x), "y": str(y)})
+            elif set(cropped_sides) == {"left", "right"}:
+                # Logic for handling images cropped on both left and right sides
+                new_width = 1080  # Expand to full width of canvas
+                
+                # Calculate the aspect ratio of the original image
+                aspect_ratio = image.width / image.height
+                
+                # Calculate the new height while maintaining aspect ratio
+                new_height = int(new_width / aspect_ratio)
+                
+                # Resize the image
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                # Set horizontal position (always 0 as it spans full width)
+                x = 0
+                
+                # Calculate vertical position to respect bottom padding
+                y = 1080 - new_height - padding
+                
+                # If the resized image is taller than the canvas, crop from the top only
+                if new_height > 1080 - padding:
+                    crop_top = new_height - (1080 - padding)
+                    image = image.crop((0, crop_top, new_width, new_height))
+                    new_height = 1080 - padding
+                    y = 0
+                    log.append({"action": "crop_vertical", "top_pixels_removed": str(crop_top)})
+                else:
+                    # Align the image to the bottom with padding
+                    y = 1080 - new_height - padding
+                
+                log.append({"action": "position", "x": str(x), "y": str(y)})
+            elif cropped_sides == ["bottom"]:
+                # Logic for handling images cropped on the bottom side
+                # Calculate the aspect ratio of the original image
+                aspect_ratio = image.width / image.height
+                
+                if aspect_ratio < 1:  # Portrait orientation
+                    new_height = 1080 - padding  # Full height with top padding
+                    new_width = int(new_height * aspect_ratio)
+                    
+                    # If the new width exceeds the canvas width, adjust it
+                    if new_width > 1080:
+                        new_width = 1080
+                        new_height = int(new_width / aspect_ratio)
+                else:  # Landscape orientation
+                    new_width = 1080 - (2 * padding)
+                    new_height = int(new_width / aspect_ratio)
+                    
+                    # If the new height exceeds the canvas height, adjust it
+                    if new_height > 1080:
+                        new_height = 1080
+                        new_width = int(new_height * aspect_ratio)
+                
+                # Resize the image
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                # Set horizontal position (centered)
+                x = (1080 - new_width) // 2
+                
+                # Set vertical position (touching bottom edge for all cases)
+                y = 1080 - new_height
+                
+                log.append({"action": "position", "x": str(x), "y": str(y)})
+            else:
+                # Use the original resizing logic for other partially cropped images
+                if image.width > image.height:
+                    new_width = target_size
+                    new_height = int(target_size / aspect_ratio)
+                else:
+                    new_height = target_size
+                    new_width = int(target_size * aspect_ratio)
+                
+                # Resize the image
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                # Center horizontally for all images
+                x = (1080 - new_width) // 2
+                y = 1080 - new_height - padding
+                
+                # Adjust positions for cropped sides
+                if "top" in cropped_sides:
+                    y = 0
+                elif "bottom" in cropped_sides:
+                    y = 1080 - new_height
+                if "left" in cropped_sides:
+                    x = 0
+                elif "right" in cropped_sides:
+                    x = 1080 - new_width
+                
+                # Apply padding only to non-cropped sides, but keep horizontal centering
+                if "left" not in cropped_sides and "right" not in cropped_sides:
+                    x = (1080 - new_width) // 2  # Always center horizontally
+                if "top" not in cropped_sides and "bottom" not in cropped_sides:
+                    y = max(padding, min(y, 1080 - new_height - padding))
+
+    return log, image, x, y
+
+def process_single_image(image_path, output_folder, bg_method, output_format, bg_choice, custom_color, watermark_path=None):
+    add_padding_line = False
+    padding = 125
+    
+    filename = os.path.basename(image_path)
+    try:
+        print(f"Processing image: {filename}")
+        if bg_method == 'rembg':
+            image_with_no_bg = remove_background_rembg(image_path)
+        elif bg_method == 'bria':
+            image_with_no_bg = remove_background_bria(image_path)
+            
+        temp_image_path = os.path.join(output_folder, f"temp_{filename}")
+        image_with_no_bg.save(temp_image_path, format='PNG')
+
+        log, new_image, x, y = position_logic(temp_image_path)
+
+        # Create a new 1080x1080 canvas with the appropriate background
+        if bg_choice == 'white':
+            canvas = Image.new("RGBA", (1080, 1080), "WHITE")
+        elif bg_choice == 'custom':
+            canvas = Image.new("RGBA", (1080, 1080), custom_color)
+        else:  # transparent
+            canvas = Image.new("RGBA", (1080, 1080), (0, 0, 0, 0))
+
+        # Paste the resized image onto the canvas
+        canvas.paste(new_image, (x, y), new_image)
+        log.append({"action": "paste", "position": [str(x), str(y)]})
+
+        # Add visible black line for padding when background is not transparent
+        if add_padding_line:
+            draw = ImageDraw.Draw(canvas)
+            draw.rectangle([padding, padding, 1080 - padding, 1080 - padding], outline="black", width=5)
+            log.append({"action": "add_padding_line"})
+
+        output_ext = 'jpg' if output_format == 'JPG' else 'png'
+        output_filename = f"{os.path.splitext(filename)[0]}.{output_ext}"
+        output_path = os.path.join(output_folder, output_filename)
+
+        # Apply watermark only if the filename ends with "_01" and watermark_path is provided
+        if os.path.splitext(filename)[0].endswith("_01") and watermark_path:
+            watermark = Image.open(watermark_path).convert("RGBA")
+            canvas.paste(watermark, (0, 0), watermark)
+            log.append({"action": "add_watermark"})
+
+        if output_format == 'JPG':
+            canvas.convert('RGB').save(output_path, format='JPEG')
+        else:
+            canvas.save(output_path, format='PNG')
+
+        os.remove(temp_image_path)
+
+        print(f"Processed image path: {output_path}")
+        return [(output_path, image_path)], log
+
+    except Exception as e:
+        print(f"Error processing {filename}: {e}")
+        return None, None
+
+def process_images(input_files, bg_method='rembg', watermark_path=None, output_format='PNG', bg_choice='transparent', custom_color="#ffffff", num_workers=4, progress=gr.Progress()):
+    start_time = time.time()
+    
+    output_folder = "processed_images"
+    if os.path.exists(output_folder):
+        shutil.rmtree(output_folder)
+    os.makedirs(output_folder)
+    
+    processed_images = []
+    original_images = []
+    all_logs = []
+    
+    if isinstance(input_files, str) and input_files.lower().endswith(('.zip', '.rar')):
+        # Handle zip file
+        input_folder = "temp_input"
+        if os.path.exists(input_folder):
+            shutil.rmtree(input_folder)
+        os.makedirs(input_folder)
+        
+        try:
+            with zipfile.ZipFile(input_files, 'r') as zip_ref:
+                zip_ref.extractall(input_folder)
+        except zipfile.BadZipFile as e:
+            print(f"Error extracting zip file: {e}")
+            return [], None, 0
+        
+        image_files = [os.path.join(input_folder, f) for f in os.listdir(input_folder) if f.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif', '.webp'))]
+    elif isinstance(input_files, list):
+        # Handle multiple files
+        image_files = input_files
+    else:
+        # Handle single file
+        image_files = [input_files]
+    
+    total_images = len(image_files)
+    print(f"Total images to process: {total_images}")
+
+    avg_processing_time = 0
+    with ThreadPoolExecutor(max_workers=num_workers) as executor:
+        future_to_image = {executor.submit(process_single_image, image_path, output_folder, bg_method, output_format, bg_choice, custom_color, watermark_path): image_path for image_path in image_files}
+        for idx, future in enumerate(future_to_image):
+            try:
+                start_time_image = time.time()
+                result, log = future.result()
+                end_time_image = time.time()
+                image_processing_time = end_time_image - start_time_image
+                
+                # Update average processing time
+                avg_processing_time = (avg_processing_time * idx + image_processing_time) / (idx + 1)
+                
+                if result:
+                    processed_images.extend(result)
+                    original_images.append(future_to_image[future])
+                    all_logs.append({os.path.basename(future_to_image[future]): log})
+                
+                # Estimate remaining time
+                remaining_images = total_images - (idx + 1)
+                estimated_remaining_time = remaining_images * avg_processing_time
+                
+                progress((idx + 1) / total_images, f"{idx + 1}/{total_images} images processed. Estimated time remaining: {estimated_remaining_time:.2f} seconds")
+            except Exception as e:
+                print(f"Error processing image {future_to_image[future]}: {e}")
+
+    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))
+
+    # Write the comprehensive log for all images
+    with open(os.path.join(output_folder, 'process_log.json'), 'w') as log_file:
+        json.dump(all_logs, log_file, indent=4)
+    print("Comprehensive log saved to", os.path.join(output_folder, 'process_log.json'))
+
+    end_time = time.time()
+    processing_time = end_time - start_time
+    print(f"Processing time: {processing_time} seconds")
+    
+    return original_images, processed_images, output_zip_path, processing_time
+
+def gradio_interface(input_files, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
+    progress = gr.Progress()
+    watermark_path = watermark.name if watermark else None
+    
+    # Check input_files, is it single image, list image, or zip/rar
+    if isinstance(input_files, str) and input_files.lower().endswith(('.zip', '.rar')):
+        return process_images(input_files, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
+    elif isinstance(input_files, list):
+        return process_images(input_files, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
+    else:
+        return process_images(input_files.name, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
+
+def show_color_picker(bg_choice):
+    if bg_choice == 'custom':
+        return gr.update(visible=True)
+    return gr.update(visible=False)
+
+def update_compare(evt: gr.SelectData):
+    if isinstance(evt.value, dict) and 'caption' in evt.value:
+        input_path = evt.value['caption']
+        output_path = evt.value['image']['path']
+        input_path = input_path.split("Input: ")[-1]
+        
+        # Open the original and processed images
+        original_img = Image.open(input_path)
+        processed_img = Image.open(output_path)
+        
+        # Calculate the aspect ratios
+        original_ratio = f"{original_img.width}x{original_img.height}"
+        processed_ratio = f"{processed_img.width}x{processed_img.height}"
+        
+        return gr.update(value=input_path), gr.update(value=output_path), gr.update(value=original_ratio), gr.update(value=processed_ratio)
+    else:
+        print("No caption found in selection")
+        return gr.update(value=None), gr.update(value=None), gr.update(value=None), gr.update(value=None)
+
+def process(input_files, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
+    _, processed_images, zip_path, time_taken = gradio_interface(input_files, bg_method, watermark, output_format, bg_choice, custom_color, num_workers)
+    processed_images_with_captions = [(img, f"Input: {caption}") for img, caption in processed_images]
+    return processed_images_with_captions, zip_path, f"{time_taken:.2f} seconds"
+
+with gr.Blocks() as iface:
+    gr.Markdown("# Image Background Removal and Resizing with Optional Watermark")
+    gr.Markdown("Choose to upload multiple images or a ZIP/RAR file, select the crop mode, optionally upload a watermark image, and choose the output format.")
+    
+    with gr.Row():
+        input_files = gr.File(label="Upload Image or ZIP/RAR file", file_types=[".zip", ".rar", "image"], interactive=True)
+        watermark = gr.File(label="Upload Watermark Image (Optional)", file_types=[".png"])
+    
+    with gr.Row():
+        output_format = gr.Radio(choices=["PNG", "JPG"], label="Output Format", value="JPG")
+        num_workers = gr.Slider(minimum=1, maximum=16, step=1, label="Number of Workers", value=5)
+
+    with gr.Row():
+        bg_method = gr.Radio(choices=["bria", "rembg"], label="Background Removal Method", value="bria")
+        bg_choice = gr.Radio(choices=["transparent", "white", "custom"], label="Background Choice", value="white")
+        custom_color = gr.ColorPicker(label="Custom Background Color", value="#ffffff", visible=False)
+
+    process_button = gr.Button("Process Images")
+
+    with gr.Row():
+        gallery_processed = gr.Gallery(label="Processed Images")
+    with gr.Row():
+        image_original = gr.Image(label="Original Images", interactive=False)
+        image_processed = gr.Image(label="Processed Images", interactive=False)
+    with gr.Row():
+        original_ratio = gr.Textbox(label="Original Ratio")
+        processed_ratio = gr.Textbox(label="Processed Ratio")
+    with gr.Row():
+        output_zip = gr.File(label="Download Processed Images as ZIP")
+        processing_time = gr.Textbox(label="Processing Time (seconds)")
+
+    bg_choice.change(show_color_picker, inputs=bg_choice, outputs=custom_color)
+    process_button.click(process, inputs=[input_files, bg_method, watermark, output_format, bg_choice, custom_color, num_workers], outputs=[gallery_processed, output_zip, processing_time])
+    gallery_processed.select(update_compare, outputs=[image_original, image_processed, original_ratio, processed_ratio])
+
+iface.launch()

app.py

@@ -46,7 +46,7 @@ def get_bounding_box_with_threshold(image, threshold):
     else:
         return None
 
-def position_logic(image_path, use_threshold=True):
+def position_logic(image_path, canvas_size, padding_top, padding_right, padding_bottom, padding_left, use_threshold=True):
     image = Image.open(image_path)
     image = image.convert("RGBA")
     
@@ -63,7 +63,7 @@ def position_logic(image_path, use_threshold=True):
         cropped_sides = []
         
         # Define tolerance for transparency
-        tolerance = 10  # Adjust this value as needed
+        tolerance = 30  # Adjust this value as needed
         
         # Check top edge
         if any(image.getpixel((x, 0))[3] > tolerance for x in range(width)):
@@ -95,51 +95,50 @@ def position_logic(image_path, use_threshold=True):
         log.append({"action": "crop", "bbox": [str(bbox[0]), str(bbox[1]), str(bbox[2]), str(bbox[3])]})
         
         # Calculate the new size to expand the image
-        padding = 125
-        target_size = 1080
+        target_width, target_height = canvas_size
         aspect_ratio = image.width / image.height
         
         if len(cropped_sides) == 4:
             # If the image is cropped on all sides, center crop it to fit the canvas
             if aspect_ratio > 1:  # Landscape
-                new_height = target_size
+                new_height = target_height
                 new_width = int(new_height * aspect_ratio)
-                left = (new_width - target_size) // 2
+                left = (new_width - target_width) // 2
                 image = image.resize((new_width, new_height), Image.LANCZOS)
-                image = image.crop((left, 0, left + target_size, target_size))
+                image = image.crop((left, 0, left + target_width, target_height))
             else:  # Portrait or square
-                new_width = target_size
+                new_width = target_width
                 new_height = int(new_width / aspect_ratio)
-                top = (new_height - target_size) // 2
+                top = (new_height - target_height) // 2
                 image = image.resize((new_width, new_height), Image.LANCZOS)
-                image = image.crop((0, top, target_size, top + target_size))
-            log.append({"action": "center_crop_resize", "new_size": f"{target_size}x{target_size}"})
+                image = image.crop((0, top, target_width, top + target_height))
+            log.append({"action": "center_crop_resize", "new_size": f"{target_width}x{target_height}"})
             x, y = 0, 0
         elif not cropped_sides:
             # If the image is not cropped, expand it from center until it touches the padding
-            new_height = 1080 - 2 * padding  # Ensure it touches top and bottom padding
+            new_height = target_height - padding_top - padding_bottom
             new_width = int(new_height * aspect_ratio)
             
-            if new_width > 1080 - 2 * padding:
+            if new_width > target_width - padding_left - padding_right:
                 # If width exceeds available space, adjust based on width
-                new_width = 1080 - 2 * padding
+                new_width = target_width - padding_left - padding_right
                 new_height = int(new_width / aspect_ratio)
             
             # Resize the image
             image = image.resize((new_width, new_height), Image.LANCZOS)
             log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
             
-            x = (1080 - new_width) // 2
-            y = 1080 - new_height - padding
+            x = (target_width - new_width) // 2
+            y = target_height - new_height - padding_bottom
         else:
             # New logic for handling cropped top and left, or top and right
             if set(cropped_sides) == {"top", "left"} or set(cropped_sides) == {"top", "right"}:
-                new_height = target_size - padding  # Ensure bottom padding
+                new_height = target_height - padding_bottom
                 new_width = int(new_height * aspect_ratio)
                 
                 # If new width exceeds canvas width, adjust based on width
-                if new_width > target_size:
-                    new_width = target_size
+                if new_width > target_width:
+                    new_width = target_width
                     new_height = int(new_width / aspect_ratio)
                 
                 # Resize the image
@@ -150,60 +149,82 @@ def position_logic(image_path, use_threshold=True):
                 if "left" in cropped_sides:
                     x = 0
                 else:  # right in cropped_sides
-                    x = target_size - new_width
+                    x = target_width - new_width
                 y = 0
                 
                 # If the resized image is taller than the canvas minus padding, crop from the bottom
-                if new_height > target_size - padding:
-                    crop_bottom = new_height - (target_size - padding)
+                if new_height > target_height - padding_bottom:
+                    crop_bottom = new_height - (target_height - padding_bottom)
                     image = image.crop((0, 0, new_width, new_height - crop_bottom))
-                    new_height = target_size - padding
+                    new_height = target_height - padding_bottom
                     log.append({"action": "crop_vertical", "bottom_pixels_removed": str(crop_bottom)})
                 
+                log.append({"action": "position", "x": str(x), "y": str(y)})
+            elif set(cropped_sides) == {"bottom", "left"} or set(cropped_sides) == {"bottom", "right"}:
+                # Handle bottom & left or bottom & right cropped images
+                new_height = target_height - padding_top
+                new_width = int(new_height * aspect_ratio)
+                
+                # If new width exceeds canvas width, adjust based on width
+                if new_width > target_width - padding_left - padding_right:
+                    new_width = target_width - padding_left - padding_right
+                    new_height = int(new_width / aspect_ratio)
+                
+                # Resize the image without cropping or stretching
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                # Set position
+                if "left" in cropped_sides:
+                    x = 0
+                else:  # right in cropped_sides
+                    x = target_width - new_width
+                y = target_height - new_height
+                
                 log.append({"action": "position", "x": str(x), "y": str(y)})
             elif set(cropped_sides) == {"bottom", "left", "right"}:
                 # Expand the image from the center
-                new_width = target_size
+                new_width = target_width
                 new_height = int(new_width / aspect_ratio)
                 
-                if new_height < target_size:
-                    new_height = target_size
+                if new_height < target_height:
+                    new_height = target_height
                     new_width = int(new_height * aspect_ratio)
                 
                 image = image.resize((new_width, new_height), Image.LANCZOS)
                 
                 # Crop to fit the canvas
-                left = (new_width - target_size) // 2
+                left = (new_width - target_width) // 2
                 top = 0
-                image = image.crop((left, top, left + target_size, top + target_size))
+                image = image.crop((left, top, left + target_width, top + target_height))
                 
-                log.append({"action": "expand_and_crop", "new_size": f"{target_size}x{target_size}"})
+                log.append({"action": "expand_and_crop", "new_size": f"{target_width}x{target_height}"})
                 x, y = 0, 0
             elif cropped_sides == ["top"]:
                 # New logic for handling only top-cropped images
                 if image.width > image.height:
-                    new_width = target_size
-                    new_height = int(target_size / aspect_ratio)
+                    new_width = target_width
+                    new_height = int(target_width / aspect_ratio)
                 else:
-                    new_height = target_size - padding  # Ensure bottom padding
+                    new_height = target_height - padding_bottom
                     new_width = int(new_height * aspect_ratio)
                 
                 # Resize the image
                 image = image.resize((new_width, new_height), Image.LANCZOS)
                 log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
                 
-                x = (1080 - new_width) // 2
+                x = (target_width - new_width) // 2
                 y = 0  # Align to top
                 
                 # Apply padding only to non-cropped sides
-                x = max(padding, min(x, 1080 - new_width - padding))
+                x = max(padding_left, min(x, target_width - new_width - padding_right))
             elif cropped_sides in [["right"], ["left"]]:
                 # New logic for handling only right-cropped or left-cropped images
                 if image.width > image.height:
-                    new_width = target_size - padding  # Ensure padding on non-cropped side
+                    new_width = target_width - max(padding_left, padding_right)
                     new_height = int(new_width / aspect_ratio)
                 else:
-                    new_height = target_size - padding  # Ensure bottom padding
+                    new_height = target_height - padding_top - padding_bottom
                     new_width = int(new_height * aspect_ratio)
                 
                 # Resize the image
@@ -211,13 +232,19 @@ def position_logic(image_path, use_threshold=True):
                 log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
                 
                 if cropped_sides == ["right"]:
-                    x = 1080 - new_width  # Align to right
+                    x = target_width - new_width  # Align to right
                 else:  # cropped_sides == ["left"]
-                    x = 0  # Align to left without padding
-                y = 1080 - new_height - padding  # Respect bottom padding
+                    x = 0  # Align to left
+                y = target_height - new_height - padding_bottom  # Respect bottom padding
+                
+                # Ensure top padding is respected
+                if y < padding_top:
+                    y = padding_top
+                    
+                log.append({"action": "position", "x": str(x), "y": str(y)})
             elif set(cropped_sides) == {"left", "right"}:
                 # Logic for handling images cropped on both left and right sides
-                new_width = 1080  # Expand to full width of canvas
+                new_width = target_width  # Expand to full width of canvas
                 
                 # Calculate the aspect ratio of the original image
                 aspect_ratio = image.width / image.height
@@ -233,58 +260,110 @@ def position_logic(image_path, use_threshold=True):
                 x = 0
                 
                 # Calculate vertical position to respect bottom padding
-                y = 1080 - new_height - padding
+                y = target_height - new_height - padding_bottom
                 
                 # If the resized image is taller than the canvas, crop from the top only
-                if new_height > 1080 - padding:
-                    crop_top = new_height - (1080 - padding)
+                if new_height > target_height - padding_bottom:
+                    crop_top = new_height - (target_height - padding_bottom)
                     image = image.crop((0, crop_top, new_width, new_height))
-                    new_height = 1080 - padding
+                    new_height = target_height - padding_bottom
                     y = 0
                     log.append({"action": "crop_vertical", "top_pixels_removed": str(crop_top)})
                 else:
                     # Align the image to the bottom with padding
-                    y = 1080 - new_height - padding
+                    y = target_height - new_height - padding_bottom
+                
+                log.append({"action": "position", "x": str(x), "y": str(y)})
+            elif cropped_sides == ["bottom"]:
+                # Logic for handling images cropped on the bottom side
+                # Calculate the aspect ratio of the original image
+                aspect_ratio = image.width / image.height
+                
+                if aspect_ratio < 1:  # Portrait orientation
+                    new_height = target_height - padding_top  # Full height with top padding
+                    new_width = int(new_height * aspect_ratio)
+                    
+                    # If the new width exceeds the canvas width, adjust it
+                    if new_width > target_width:
+                        new_width = target_width
+                        new_height = int(new_width / aspect_ratio)
+                else:  # Landscape orientation
+                    new_width = target_width - padding_left - padding_right
+                    new_height = int(new_width / aspect_ratio)
+                    
+                    # If the new height exceeds the canvas height, adjust it
+                    if new_height > target_height:
+                        new_height = target_height
+                        new_width = int(new_height * aspect_ratio)
+                
+                # Resize the image
+                image = image.resize((new_width, new_height), Image.LANCZOS)
+                log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
+                
+                # Set horizontal position (centered)
+                x = (target_width - new_width) // 2
+                
+                # Set vertical position (touching bottom edge for all cases)
+                y = target_height - new_height
                 
                 log.append({"action": "position", "x": str(x), "y": str(y)})
             else:
                 # Use the original resizing logic for other partially cropped images
                 if image.width > image.height:
-                    new_width = target_size
-                    new_height = int(target_size / aspect_ratio)
+                    new_width = target_width
+                    new_height = int(target_width / aspect_ratio)
                 else:
-                    new_height = target_size
-                    new_width = int(target_size * aspect_ratio)
+                    new_height = target_height
+                    new_width = int(target_height * aspect_ratio)
                 
                 # Resize the image
                 image = image.resize((new_width, new_height), Image.LANCZOS)
                 log.append({"action": "resize", "new_width": str(new_width), "new_height": str(new_height)})
                 
                 # Center horizontally for all images
-                x = (1080 - new_width) // 2
-                y = 1080 - new_height - padding
+                x = (target_width - new_width) // 2
+                y = target_height - new_height - padding_bottom
                 
                 # Adjust positions for cropped sides
                 if "top" in cropped_sides:
                     y = 0
                 elif "bottom" in cropped_sides:
-                    y = 1080 - new_height
+                    y = target_height - new_height
                 if "left" in cropped_sides:
                     x = 0
                 elif "right" in cropped_sides:
-                    x = 1080 - new_width
+                    x = target_width - new_width
                 
                 # Apply padding only to non-cropped sides, but keep horizontal centering
                 if "left" not in cropped_sides and "right" not in cropped_sides:
-                    x = (1080 - new_width) // 2  # Always center horizontally
+                    x = (target_width - new_width) // 2  # Always center horizontally
                 if "top" not in cropped_sides and "bottom" not in cropped_sides:
-                    y = max(padding, min(y, 1080 - new_height - padding))
+                    y = max(padding_top, min(y, target_height - new_height - padding_bottom))
 
     return log, image, x, y
 
-def process_single_image(image_path, output_folder, bg_method, output_format, bg_choice, custom_color, watermark_path=None):
+def process_single_image(image_path, output_folder, bg_method, canvas_size_name, output_format, bg_choice, custom_color, watermark_path=None):
     add_padding_line = False
-    padding = 125
+
+    if canvas_size_name == 'Rox':
+        canvas_size = (1080, 1080)
+        padding_top = 112
+        padding_right = 125
+        padding_bottom = 116
+        padding_left = 125
+    elif canvas_size_name == 'Columbia':
+        canvas_size = (730, 610)
+        padding_top = 30
+        padding_right = 105
+        padding_bottom = 35
+        padding_left = 105
+    elif canvas_size_name == 'Zalora':
+        canvas_size = (763, 1100)
+        padding_top = 50
+        padding_right = 50
+        padding_bottom = 200
+        padding_left = 50
+
     
     filename = os.path.basename(image_path)
     try:
@@ -297,15 +376,15 @@ def process_single_image(image_path, output_folder, bg_method, output_format, bg
         temp_image_path = os.path.join(output_folder, f"temp_{filename}")
         image_with_no_bg.save(temp_image_path, format='PNG')
 
-        log, new_image, x, y = position_logic(temp_image_path)
+        log, new_image, x, y = position_logic(temp_image_path, canvas_size, padding_top, padding_right, padding_bottom, padding_left)
 
-        # Create a new 1080x1080 canvas with the appropriate background
+        # Create a new canvas with the appropriate background
         if bg_choice == 'white':
-            canvas = Image.new("RGBA", (1080, 1080), "WHITE")
+            canvas = Image.new("RGBA", canvas_size, "WHITE")
         elif bg_choice == 'custom':
-            canvas = Image.new("RGBA", (1080, 1080), custom_color)
+            canvas = Image.new("RGBA", canvas_size, custom_color)
         else:  # transparent
-            canvas = Image.new("RGBA", (1080, 1080), (0, 0, 0, 0))
+            canvas = Image.new("RGBA", canvas_size, (0, 0, 0, 0))
 
         # Paste the resized image onto the canvas
         canvas.paste(new_image, (x, y), new_image)
@@ -314,53 +393,44 @@ def process_single_image(image_path, output_folder, bg_method, output_format, bg
         # Add visible black line for padding when background is not transparent
         if add_padding_line:
             draw = ImageDraw.Draw(canvas)
-            draw.rectangle([padding, padding, 1080 - padding, 1080 - padding], outline="black", width=5)
+            draw.rectangle([padding_left, padding_top, canvas_size[0] - padding_right, canvas_size[1] - padding_bottom], outline="black", width=5)
             log.append({"action": "add_padding_line"})
 
-        images_paths = []
-
         output_ext = 'jpg' if output_format == 'JPG' else 'png'
-        output_path_without_watermark = os.path.join(output_folder, f"without_watermark_{os.path.splitext(filename)[0]}.{output_ext}")
-        if output_format == 'JPG':
-            canvas.convert('RGB').save(output_path_without_watermark, format='JPEG')
-        else:
-            canvas.save(output_path_without_watermark, format='PNG')
-        images_paths.append((output_path_without_watermark, image_path))
+        output_filename = f"{os.path.splitext(filename)[0]}.{output_ext}"
+        output_path = os.path.join(output_folder, output_filename)
 
-        if watermark_path:
+        # Apply watermark only if the filename ends with "_01" and watermark_path is provided
+        if os.path.splitext(filename)[0].endswith("_01") and watermark_path:
             watermark = Image.open(watermark_path).convert("RGBA")
-            canvas_with_watermark = canvas.copy()
-            canvas_with_watermark.paste(watermark, (0, 0), watermark)
-            output_path_with_watermark = os.path.join(output_folder, f"with_watermark_{os.path.splitext(filename)[0]}.{output_ext}")
-            if output_format == 'JPG':
-                canvas_with_watermark.convert('RGB').save(output_path_with_watermark, format='JPEG')
-            else:
-                canvas_with_watermark.save(output_path_with_watermark, format='PNG')
-            images_paths.append((output_path_with_watermark, image_path))            
+            canvas.paste(watermark, (0, 0), watermark)
+            log.append({"action": "add_watermark"})
 
-        os.remove(temp_image_path)
+        if output_format == 'JPG':
+            canvas.convert('RGB').save(output_path, format='JPEG')
+        else:
+            canvas.save(output_path, format='PNG')
 
-        with open(os.path.join(output_folder, 'process_log.json'), 'w') as log_file:
-            json.dump(log, log_file, indent=4)
-        print("Log saved to", os.path.join(output_folder, 'process_log.json'))
+        os.remove(temp_image_path)
 
-        print(f"Processed image paths: {images_paths}")
-        return images_paths
+        print(f"Processed image path: {output_path}")
+        return [(output_path, image_path)], log
 
     except Exception as e:
         print(f"Error processing {filename}: {e}")
-        return None
+        return None, None
 
-def process_images(input_files, bg_method='rembg', watermark_path=None, output_format='PNG', bg_choice='transparent', custom_color="#ffffff", num_workers=4, progress=gr.Progress()):
+def process_images(input_files, bg_method='rembg', watermark_path=None, canvas_size='Rox', output_format='PNG', bg_choice='transparent', custom_color="#ffffff", num_workers=4, progress=gr.Progress()):
     start_time = time.time()
     
-    output_folder = "temp_output"
+    output_folder = "processed_images"
     if os.path.exists(output_folder):
         shutil.rmtree(output_folder)
     os.makedirs(output_folder)
     
     processed_images = []
     original_images = []
+    all_logs = []
     
     if isinstance(input_files, str) and input_files.lower().endswith(('.zip', '.rar')):
         # Handle zip file
@@ -389,11 +459,11 @@ def process_images(input_files, bg_method='rembg', watermark_path=None, output_f
 
     avg_processing_time = 0
     with ThreadPoolExecutor(max_workers=num_workers) as executor:
-        future_to_image = {executor.submit(process_single_image, image_path, output_folder, bg_method, output_format, bg_choice, custom_color, watermark_path): image_path for image_path in image_files}
+        future_to_image = {executor.submit(process_single_image, image_path, output_folder, bg_method, canvas_size, output_format, bg_choice, custom_color, watermark_path): image_path for image_path in image_files}
         for idx, future in enumerate(future_to_image):
             try:
                 start_time_image = time.time()
-                result = future.result()
+                result, log = future.result()
                 end_time_image = time.time()
                 image_processing_time = end_time_image - start_time_image
                 
@@ -403,6 +473,7 @@ def process_images(input_files, bg_method='rembg', watermark_path=None, output_f
                 if result:
                     processed_images.extend(result)
                     original_images.append(future_to_image[future])
+                    all_logs.append({os.path.basename(future_to_image[future]): log})
                 
                 # Estimate remaining time
                 remaining_images = total_images - (idx + 1)
@@ -415,10 +486,12 @@ def process_images(input_files, bg_method='rembg', watermark_path=None, output_f
     output_zip_path = "processed_images.zip"
     with zipfile.ZipFile(output_zip_path, 'w') as zipf:
         for file, _ in processed_images:
-            if "with_watermark" in file:
-                zipf.write(file, os.path.join("with_watermark", os.path.basename(file)))
-            else:
-                zipf.write(file, os.path.join("without_watermark", os.path.basename(file)))
+            zipf.write(file, os.path.basename(file))
+
+    # Write the comprehensive log for all images
+    with open(os.path.join(output_folder, 'process_log.json'), 'w') as log_file:
+        json.dump(all_logs, log_file, indent=4)
+    print("Comprehensive log saved to", os.path.join(output_folder, 'process_log.json'))
 
     end_time = time.time()
     processing_time = end_time - start_time
@@ -426,17 +499,17 @@ def process_images(input_files, bg_method='rembg', watermark_path=None, output_f
     
     return original_images, processed_images, output_zip_path, processing_time
 
-def gradio_interface(input_files, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
+def gradio_interface(input_files, bg_method, watermark, canvas_size, output_format, bg_choice, custom_color, num_workers):
     progress = gr.Progress()
     watermark_path = watermark.name if watermark else None
     
     # Check input_files, is it single image, list image, or zip/rar
     if isinstance(input_files, str) and input_files.lower().endswith(('.zip', '.rar')):
-        return process_images(input_files, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
+            return process_images(input_files, bg_method, watermark_path, canvas_size, output_format, bg_choice, custom_color, num_workers, progress)
     elif isinstance(input_files, list):
-        return process_images(input_files, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
+        return process_images(input_files, bg_method, watermark_path, canvas_size, output_format, bg_choice, custom_color, num_workers, progress)
     else:
-        return process_images(input_files.name, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
+        return process_images(input_files.name, bg_method, watermark_path, canvas_size, output_format, bg_choice, custom_color, num_workers, progress)
 
 def show_color_picker(bg_choice):
     if bg_choice == 'custom':
@@ -462,8 +535,8 @@ def update_compare(evt: gr.SelectData):
         print("No caption found in selection")
         return gr.update(value=None), gr.update(value=None), gr.update(value=None), gr.update(value=None)
 
-def process(input_files, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
-    _, processed_images, zip_path, time_taken = gradio_interface(input_files, bg_method, watermark, output_format, bg_choice, custom_color, num_workers)
+def process(input_files, bg_method, watermark, canvas_size, output_format, bg_choice, custom_color, num_workers):
+    _, processed_images, zip_path, time_taken = gradio_interface(input_files, bg_method, watermark, canvas_size, output_format, bg_choice, custom_color, num_workers)
     processed_images_with_captions = [(img, f"Input: {caption}") for img, caption in processed_images]
     return processed_images_with_captions, zip_path, f"{time_taken:.2f} seconds"
 
@@ -476,6 +549,7 @@ with gr.Blocks() as iface:
         watermark = gr.File(label="Upload Watermark Image (Optional)", file_types=[".png"])
     
     with gr.Row():
+        canvas_size = gr.Radio(choices=["Rox", "Columbia", "Zalora"], label="Canvas Size", value="Rox")
         output_format = gr.Radio(choices=["PNG", "JPG"], label="Output Format", value="JPG")
         num_workers = gr.Slider(minimum=1, maximum=16, step=1, label="Number of Workers", value=5)
 
@@ -499,7 +573,7 @@ with gr.Blocks() as iface:
         processing_time = gr.Textbox(label="Processing Time (seconds)")
 
     bg_choice.change(show_color_picker, inputs=bg_choice, outputs=custom_color)
-    process_button.click(process, inputs=[input_files, bg_method, watermark, output_format, bg_choice, custom_color, num_workers], outputs=[gallery_processed, output_zip, processing_time])
+    process_button.click(process, inputs=[input_files, bg_method, watermark, canvas_size, output_format, bg_choice, custom_color, num_workers], outputs=[gallery_processed, output_zip, processing_time])
     gallery_processed.select(update_compare, outputs=[image_original, image_processed, original_ratio, processed_ratio])
 
 iface.launch()

app_old.py

@@ -1,307 +0,0 @@
-import os
-import zipfile
-import shutil
-import time
-from PIL import Image
-import io
-from rembg import remove
-import gradio as gr
-from concurrent.futures import ThreadPoolExecutor
-from transformers import pipeline
-
-def colors_within_tolerance(color1, color2, tolerance):
-    return all(abs(c1 - c2) <= tolerance for c1, c2 in zip(color1, color2))
-
-def check_border_colors(image_path, tolerance):
-    image = Image.open(image_path)
-    pixels = image.load()
-    
-    width, height = image.size
-
-    left_border_color = pixels[0, 0]
-    right_border_color = pixels[width - 1, 0]
-
-    for y in range(height):
-        if not colors_within_tolerance(pixels[0, y], left_border_color, tolerance):
-            return False
-        if not colors_within_tolerance(pixels[width - 1, y], right_border_color, tolerance):
-            return False
-
-    return True
-
-def resize_and_crop_image(image_path, target_size=(1080, 1080), crop_mode='center'):
-    print(f"Resizing and cropping image: {image_path}")
-    with Image.open(image_path) as img:
-        width, height = img.size
-        print(f"Original image size: {width}x{height}")
-
-        scaling_factor = max(target_size[0] / width, target_size[1] / height)
-
-        new_size = (int(width * scaling_factor), int(height * scaling_factor))
-        resized_img = img.resize(new_size, Image.LANCZOS)
-        print(f"Resized image size: {new_size}")
-
-        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]
-
-        cropped_img = resized_img.crop((left, top, right, bottom))
-        print(f"Cropped image size: {cropped_img.size}")
-
-        return cropped_img
-
-def remove_background_rembg(input_path):
-    print(f"Removing background using rembg for image: {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 remove_background_bria(input_path):
-    print(f"Removing background using bria for image: {input_path}")
-    pipe = pipeline("image-segmentation", model="briaai/RMBG-1.4", trust_remote_code=True, device=0)
-    pillow_image = pipe(input_path)
-    return pillow_image
-
-def process_single_image(image_path, output_folder, crop_mode, bg_method, output_format, bg_choice, custom_color, watermark_path=None):
-    filename = os.path.basename(image_path)
-    try:
-        print(f"Processing image: {filename}")
-        if bg_method == 'rembg':
-            image_with_no_bg = remove_background_rembg(image_path)
-        elif bg_method == 'bria':
-            image_with_no_bg = remove_background_bria(image_path)
-            
-        temp_image_path = os.path.join(output_folder, f"temp_{filename}")
-        image_with_no_bg.save(temp_image_path, format='PNG')
-
-        if check_border_colors(temp_image_path, tolerance=50):
-            print(f"Border colors are the same for image: {filename}")
-            if bg_choice == 'transparent':
-                new_image = Image.new("RGBA", (1080, 1080), (255, 255, 255, 0))
-            else:
-                new_image = Image.new("RGBA", (1080, 1080), custom_color)
-
-            width, height = image_with_no_bg.size
-            scaling_factor = min(1080 / width, 1080 / height)
-            new_size = (int(width * scaling_factor), int(height * scaling_factor))
-            resized_img = image_with_no_bg.resize(new_size, Image.LANCZOS)
-            print(f"Resized image size: {new_size}")
-            new_image.paste(resized_img, ((1080 - resized_img.width) // 2, (1080 - resized_img.height) // 2))
-        else:
-            print(f"Border colors are different for image: {filename}")
-            new_image = resize_and_crop_image(temp_image_path, crop_mode=crop_mode)
-
-        if bg_choice == 'white':
-            new_image = new_image.convert("RGBA")
-            white_bg = Image.new("RGBA", new_image.size, "WHITE")
-            new_image = Image.alpha_composite(white_bg, new_image)
-        elif bg_choice == 'custom':
-            new_image = new_image.convert("RGBA")
-            custom_bg = Image.new("RGBA", new_image.size, custom_color)
-            new_image = Image.alpha_composite(custom_bg, new_image)
-
-        images_paths = []
-
-        output_ext = 'jpg' if output_format == 'JPG' else 'png'
-        output_path_without_watermark = os.path.join(output_folder, f"without_watermark_{os.path.splitext(filename)[0]}.{output_ext}")
-        if output_format == 'JPG':
-            new_image.convert('RGB').save(output_path_without_watermark, format='JPEG')
-        else:
-            new_image.save(output_path_without_watermark, format='PNG')
-        images_paths.append((output_path_without_watermark, image_path))
-
-        if watermark_path:
-            watermark = Image.open(watermark_path).convert("RGBA")
-            new_image_with_watermark = new_image.copy()
-            new_image_with_watermark.paste(watermark, (0, 0), watermark)
-            output_path_with_watermark = os.path.join(output_folder, f"with_watermark_{os.path.splitext(filename)[0]}.{output_ext}")
-            if output_format == 'JPG':
-                new_image_with_watermark.convert('RGB').save(output_path_with_watermark, format='JPEG')
-            else:
-                new_image_with_watermark.save(output_path_with_watermark, format='PNG')
-            images_paths.append((output_path_with_watermark, image_path))
-
-        os.remove(temp_image_path)
-
-        print(f"Processed image paths: {images_paths}")
-        return images_paths
-
-    except Exception as e:
-        print(f"Error processing {filename}: {e}")
-        return None
-
-def process_images(input_files, crop_mode='center', bg_method='rembg', watermark_path=None, output_format='PNG', bg_choice='transparent', custom_color="#ffffff", num_workers=4, progress=gr.Progress()):
-    start_time = time.time()
-    
-    output_folder = "temp_output"
-    if os.path.exists(output_folder):
-        shutil.rmtree(output_folder)
-    os.makedirs(output_folder)
-    
-    processed_images = []
-    original_images = []
-    
-    if isinstance(input_files, str) and input_files.lower().endswith(('.zip', '.rar')):
-        input_folder = "temp_input"
-        if os.path.exists(input_folder):
-            shutil.rmtree(input_folder)
-        os.makedirs(input_folder)
-        
-        try:
-            with zipfile.ZipFile(input_files, 'r') as zip_ref:
-                zip_ref.extractall(input_folder)
-        except zipfile.BadZipFile as e:
-            print(f"Error extracting zip file: {e}")
-            return [], None, 0
-        
-        image_files = [os.path.join(input_folder, f) for f in os.listdir(input_folder) if f.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif', '.webp'))]
-    else:
-        image_files = [f.name for f in input_files]
-    
-    total_images = len(image_files)
-    print(f"Total images to process: {total_images}")
-
-    avg_processing_time = 0
-    with ThreadPoolExecutor(max_workers=num_workers) as executor:
-        future_to_image = {executor.submit(process_single_image, image_path, output_folder, crop_mode, bg_method, output_format, bg_choice, custom_color, watermark_path): image_path for image_path in image_files}
-        for idx, future in enumerate(future_to_image):
-            try:
-                start_time_image = time.time()
-                result = future.result()
-                end_time_image = time.time()
-                image_processing_time = end_time_image - start_time_image
-                
-                # Update average processing time
-                avg_processing_time = (avg_processing_time * idx + image_processing_time) / (idx + 1)
-                
-                if result:
-                    processed_images.extend(result)
-                    original_images.append(future_to_image[future])
-                
-                # Estimate remaining time
-                remaining_images = total_images - (idx + 1)
-                estimated_remaining_time = remaining_images * avg_processing_time
-                
-                progress((idx + 1) / total_images, f"{idx + 1}/{total_images} images processed. Estimated time remaining: {estimated_remaining_time:.2f} seconds")
-            except Exception as e:
-                print(f"Error processing image {future_to_image[future]}: {e}")
-
-    output_zip_path = "processed_images.zip"
-    with zipfile.ZipFile(output_zip_path, 'w') as zipf:
-        for file, _ in processed_images:
-            if "with_watermark" in file:
-                zipf.write(file, os.path.join("with_watermark", os.path.basename(file)))
-            else:
-                zipf.write(file, os.path.join("without_watermark", os.path.basename(file)))
-
-    end_time = time.time()
-    processing_time = end_time - start_time
-    print(f"Processing time: {processing_time} seconds")
-    
-    return original_images, processed_images, output_zip_path, processing_time
-
-def gradio_interface(input_type, input_files, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
-    progress = gr.Progress()
-    watermark_path = watermark.name if watermark else None
-    
-    if input_type == "zip_rar":
-        return process_images(input_files.name, crop_mode, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
-    else:
-        return process_images(input_files, crop_mode, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
-
-def show_color_picker(bg_choice):
-    if bg_choice == 'custom':
-        return gr.update(visible=True)
-    return gr.update(visible=False)
-
-def update_slider(evt: gr.SelectData):
-    if isinstance(evt.value, dict) and 'caption' in evt.value:
-        input_path = evt.value['caption']
-        output_path = evt.value['image']['path']
-        input_path = input_path.split("Input: ")[-1]
-        
-        # Open the original and processed images
-        original_img = Image.open(input_path)
-        processed_img = Image.open(output_path)
-        
-        # Calculate the aspect ratios
-        original_ratio = f"{original_img.width}x{original_img.height}"
-        processed_ratio = f"{processed_img.width}x{processed_img.height}"
-        
-        return gr.update(value=input_path), gr.update(value=output_path), gr.update(value=original_ratio), gr.update(value=processed_ratio)
-    else:
-        print("No caption found in selection")
-        return gr.update(value=None), gr.update(value=None), gr.update(value=None), gr.update(value=None)
-
-def process(input_type, input_files, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
-    _, processed_images, zip_path, time_taken = gradio_interface(input_type, input_files, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers)
-    processed_images_with_captions = [(img, f"Input: {caption}") for img, caption in processed_images]
-    return processed_images_with_captions, zip_path, f"{time_taken:.2f} seconds"
-
-def update_input_type(choice):
-    if choice == "zip_rar":
-        return gr.update(visible=True), gr.update(visible=False)
-    else:
-        return gr.update(visible=False), gr.update(visible=True)
-
-with gr.Blocks() as iface:
-    gr.Markdown("# Image Background Removal and Resizing with Optional Watermark")
-    gr.Markdown("Choose to upload multiple images or a ZIP/RAR file, select the crop mode, optionally upload a watermark image, and choose the output format.")
-
-    input_type = gr.Radio(choices=["multiple_images", "zip_rar"], label="Input Type", value="multiple_images")
-    
-    with gr.Row():
-        zip_file = gr.File(label="Upload ZIP/RAR file of images", file_types=[".zip", ".rar"], visible=False)
-        multiple_images = gr.File(label="Upload multiple images", file_types=["image"], file_count="multiple")
-    
-    watermark = gr.File(label="Upload Watermark Image (Optional)", file_types=[".png"])
-    
-    with gr.Row():
-        crop_mode = gr.Radio(choices=["center", "top", "bottom", "left", "right"], label="Crop Mode", value="center")
-        output_format = gr.Radio(choices=["PNG", "JPG"], label="Output Format", value="JPG")
-        num_workers = gr.Slider(minimum=1, maximum=16, step=1, label="Number of Workers", value=5)
-
-    with gr.Row():
-        bg_method = gr.Radio(choices=["bria", "rembg"], label="Background Removal Method", value="bria")
-        bg_choice = gr.Radio(choices=["transparent", "white", "custom"], label="Background Choice", value="white")
-        custom_color = gr.ColorPicker(label="Custom Background Color", value="#ffffff", visible=False)
-
-    with gr.Row():
-        gallery_processed = gr.Gallery(label="Processed Images")
-    with gr.Row():
-        image_original = gr.Image(label="Original Images", interactive=False)
-        image_processed = gr.Image(label="Processed Images", interactive=False)
-    with gr.Row():
-        original_ratio = gr.Textbox(label="Original Ratio")
-        processed_ratio = gr.Textbox(label="Processed Ratio")
-    with gr.Row():
-        output_zip = gr.File(label="Download Processed Images as ZIP")
-        processing_time = gr.Textbox(label="Processing Time (seconds)")
-
-    input_type.change(update_input_type, inputs=input_type, outputs=[zip_file, multiple_images])
-
-    bg_choice.change(show_color_picker, inputs=bg_choice, outputs=custom_color)
-
-    process_button = gr.Button("Process Images")
-    process_button.click(process, inputs=[input_type, multiple_images, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers], outputs=[gallery_processed, output_zip, processing_time])
-
-    gallery_processed.select(update_slider, outputs=[image_original, image_processed, original_ratio, processed_ratio])
-
-iface.launch()

processed_images/process_log.json

@@ -0,0 +1,30 @@
+[
+    {
+        "1000116610.jpg": [
+            {
+                "info": "Info for temp_1000116610.jpg: The following sides of the image may contain cropped objects: top, bottom"
+            },
+            {
+                "action": "crop",
+                "bbox": [
+                    "60",
+                    "0",
+                    "639",
+                    "799"
+                ]
+            },
+            {
+                "action": "resize",
+                "new_width": "797",
+                "new_height": "1100"
+            },
+            {
+                "action": "paste",
+                "position": [
+                    "-17",
+                    "0"
+                ]
+            }
+        ]
+    }
+]