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change tread logic
Browse files
app.py
CHANGED
@@ -6,30 +6,24 @@ from PIL import Image
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import io
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from rembg import remove
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import gradio as gr
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from concurrent.futures import ThreadPoolExecutor
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from transformers import pipeline
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def colors_within_tolerance(color1, color2, tolerance):
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return all(abs(c1 - c2) <= tolerance for c1, c2 in zip(color1, color2))
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def check_border_colors(image_path, tolerance):
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# Open the image
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image = Image.open(image_path)
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pixels = image.load()
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width, height = image.size
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# Get the color of the first pixel on the left and right borders
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left_border_color = pixels[0, 0]
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right_border_color = pixels[width - 1, 0]
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# Check the left border
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for y in range(height):
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if not colors_within_tolerance(pixels[0, y], left_border_color, tolerance):
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return False
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-
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# Check the right border
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for y in range(height):
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if not colors_within_tolerance(pixels[width - 1, y], right_border_color, tolerance):
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return False
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@@ -41,10 +35,8 @@ def resize_and_crop_image(image_path, target_size=(1080, 1080), crop_mode='cente
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width, height = img.size
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print(f"Original image size: {width}x{height}")
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# Calculate the scaling factor
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scaling_factor = max(target_size[0] / width, target_size[1] / height)
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# Resize the image with high-quality resampling
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new_size = (int(width * scaling_factor), int(height * scaling_factor))
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resized_img = img.resize(new_size, Image.LANCZOS)
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print(f"Resized image size: {new_size}")
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@@ -68,7 +60,6 @@ def resize_and_crop_image(image_path, target_size=(1080, 1080), crop_mode='cente
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right = left + target_size[0]
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bottom = top + target_size[1]
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# Crop the image
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cropped_img = resized_img.crop((left, top, right, bottom))
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print(f"Cropped image size: {cropped_img.size}")
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@@ -85,7 +76,7 @@ def remove_background_rembg(input_path):
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def remove_background_bria(input_path):
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print(f"Removing background using bria for image: {input_path}")
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pipe = pipeline("image-segmentation", model="briaai/RMBG-1.4", trust_remote_code=True)
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pillow_image = pipe(input_path)
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return pillow_image
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def process_single_image(image_path, output_folder, crop_mode, bg_method, output_format, bg_choice, custom_color, watermark_path=None):
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@@ -93,25 +84,20 @@ def process_single_image(image_path, output_folder, crop_mode, bg_method, output
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try:
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print(f"Processing image: {filename}")
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if bg_method == 'rembg':
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# Remove background using rembg
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image_with_no_bg = remove_background_rembg(image_path)
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elif bg_method == 'bria':
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# Remove background using bria
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image_with_no_bg = remove_background_bria(image_path)
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temp_image_path = os.path.join(output_folder, f"temp_{filename}")
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image_with_no_bg.save(temp_image_path, format='PNG')
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# Check border colors and categorize
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if check_border_colors(temp_image_path, tolerance=50):
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print(f"Border colors are the same for image: {filename}")
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# Create a new 1080x1080 canvas
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if bg_choice == 'transparent':
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new_image = Image.new("RGBA", (1080, 1080), (255, 255, 255, 0))
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else:
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new_image = Image.new("RGBA", (1080, 1080), custom_color)
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# Scale image to fit inside the canvas without stretching
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width, height = image_with_no_bg.size
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scaling_factor = min(1080 / width, 1080 / height)
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new_size = (int(width * scaling_factor), int(height * scaling_factor))
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@@ -122,7 +108,6 @@ def process_single_image(image_path, output_folder, crop_mode, bg_method, output
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print(f"Border colors are different for image: {filename}")
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new_image = resize_and_crop_image(temp_image_path, crop_mode=crop_mode)
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# Change background color if needed
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if bg_choice == 'white':
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new_image = new_image.convert("RGBA")
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white_bg = Image.new("RGBA", new_image.size, "WHITE")
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@@ -132,10 +117,8 @@ def process_single_image(image_path, output_folder, crop_mode, bg_method, output
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custom_bg = Image.new("RGBA", new_image.size, custom_color)
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new_image = Image.alpha_composite(custom_bg, new_image)
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# Save both versions of the image (with and without watermark)
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images_paths = []
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# Save without watermark
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output_ext = 'jpg' if output_format == 'JPG' else 'png'
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output_path_without_watermark = os.path.join(output_folder, f"without_watermark_{os.path.splitext(filename)[0]}.{output_ext}")
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if output_format == 'JPG':
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@@ -144,7 +127,6 @@ def process_single_image(image_path, output_folder, crop_mode, bg_method, output
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new_image.save(output_path_without_watermark, format='PNG')
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images_paths.append(output_path_without_watermark)
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# Apply watermark if provided and save the version with watermark
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if watermark_path:
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watermark = Image.open(watermark_path).convert("RGBA")
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new_image_with_watermark = new_image.copy()
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@@ -156,7 +138,6 @@ def process_single_image(image_path, output_folder, crop_mode, bg_method, output
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new_image_with_watermark.save(output_path_with_watermark, format='PNG')
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images_paths.append(output_path_with_watermark)
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# Remove the temporary file
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os.remove(temp_image_path)
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print(f"Processed image paths: {images_paths}")
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@@ -169,7 +150,6 @@ def process_single_image(image_path, output_folder, crop_mode, bg_method, output
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def process_images(zip_file, crop_mode='center', bg_method='rembg', watermark_path=None, output_format='PNG', bg_choice='transparent', custom_color="#ffffff", num_workers=4, progress=gr.Progress()):
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start_time = time.time()
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# Create a temporary directory
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input_folder = "temp_input"
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output_folder = "temp_output"
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if os.path.exists(input_folder):
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@@ -179,7 +159,6 @@ def process_images(zip_file, crop_mode='center', bg_method='rembg', watermark_pa
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os.makedirs(input_folder)
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os.makedirs(output_folder)
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# Extract the zip file
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try:
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with zipfile.ZipFile(zip_file, 'r') as zip_ref:
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zip_ref.extractall(input_folder)
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@@ -188,25 +167,23 @@ def process_images(zip_file, crop_mode='center', bg_method='rembg', watermark_pa
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return [], None, 0
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processed_images = []
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image_files = [os.path.join(input_folder, f) for f in os.listdir(input_folder) if f.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif'))]
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total_images = len(image_files)
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print(f"Total images to process: {total_images}")
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progress((idx + 1) / total_images, f"{idx + 1}/{total_images} images processed")
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# Create a zip file of the processed images
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output_zip_path = "processed_images.zip"
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with zipfile.ZipFile(output_zip_path, 'w') as zipf:
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for file in processed_images:
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@@ -219,11 +196,10 @@ def process_images(zip_file, crop_mode='center', bg_method='rembg', watermark_pa
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processing_time = end_time - start_time
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print(f"Processing time: {processing_time} seconds")
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return processed_images, output_zip_path, processing_time
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def gradio_interface(zip_file, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
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progress = gr.Progress()
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watermark_path = watermark.name if watermark else None
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return process_images(zip_file.name, crop_mode, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
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@@ -237,7 +213,6 @@ def show_color_picker(bg_choice):
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return gr.update(visible=True)
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return gr.update(visible=False)
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# Create the Gradio interface
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with gr.Blocks() as iface:
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gr.Markdown("# Image Background Removal and Resizing with Optional Watermark")
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gr.Markdown("Upload a ZIP or RAR file containing images, choose the crop mode, optionally upload a watermark image, and select the output format.")
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@@ -248,7 +223,6 @@ with gr.Blocks() as iface:
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with gr.Row():
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crop_mode = gr.Radio(choices=["center", "top", "bottom", "left", "right"], label="Crop Mode", value="center")
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output_format = gr.Radio(choices=["PNG", "JPG"], label="Output Format", value="PNG")
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num_workers = gr.Slider(minimum=1, maximum=16, step=1, label="Number of Workers", value=2)
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@@ -257,19 +231,21 @@ with gr.Blocks() as iface:
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bg_choice = gr.Radio(choices=["transparent", "white", "custom"], label="Background Choice", value="transparent", visible=True)
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custom_color = gr.ColorPicker(label="Custom Background Color", value="#ffffff", visible=False)
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bg_choice.change(show_color_picker, inputs=bg_choice, outputs=custom_color)
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output_format.change(show_bg_choice, inputs=output_format, outputs=bg_choice)
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gallery = gr.Gallery(label="Processed Images")
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output_zip = gr.File(label="Download Processed Images as ZIP")
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processing_time = gr.Textbox(label="Processing Time (seconds)")
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def process(zip_file, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
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processed_images, zip_path, time_taken = gradio_interface(zip_file, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers)
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return processed_images, zip_path, f"{time_taken:.2f} seconds"
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process_button = gr.Button("Process Images")
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process_button.click(process, inputs=[zip_file, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers], outputs=[
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# Launch the interface
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iface.launch()
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import io
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from rembg import remove
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import gradio as gr
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from concurrent.futures import ThreadPoolExecutor
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from transformers import pipeline
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def colors_within_tolerance(color1, color2, tolerance):
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return all(abs(c1 - c2) <= tolerance for c1, c2 in zip(color1, color2))
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def check_border_colors(image_path, tolerance):
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image = Image.open(image_path)
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pixels = image.load()
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width, height = image.size
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left_border_color = pixels[0, 0]
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right_border_color = pixels[width - 1, 0]
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for y in range(height):
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if not colors_within_tolerance(pixels[0, y], left_border_color, tolerance):
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return False
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if not colors_within_tolerance(pixels[width - 1, y], right_border_color, tolerance):
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return False
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width, height = img.size
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print(f"Original image size: {width}x{height}")
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scaling_factor = max(target_size[0] / width, target_size[1] / height)
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new_size = (int(width * scaling_factor), int(height * scaling_factor))
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resized_img = img.resize(new_size, Image.LANCZOS)
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print(f"Resized image size: {new_size}")
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right = left + target_size[0]
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bottom = top + target_size[1]
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cropped_img = resized_img.crop((left, top, right, bottom))
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print(f"Cropped image size: {cropped_img.size}")
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def remove_background_bria(input_path):
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print(f"Removing background using bria for image: {input_path}")
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pipe = pipeline("image-segmentation", model="briaai/RMBG-1.4", trust_remote_code=True)
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pillow_image = pipe(input_path)
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return pillow_image
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def process_single_image(image_path, output_folder, crop_mode, bg_method, output_format, bg_choice, custom_color, watermark_path=None):
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try:
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print(f"Processing image: {filename}")
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if bg_method == 'rembg':
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image_with_no_bg = remove_background_rembg(image_path)
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elif bg_method == 'bria':
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image_with_no_bg = remove_background_bria(image_path)
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temp_image_path = os.path.join(output_folder, f"temp_{filename}")
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image_with_no_bg.save(temp_image_path, format='PNG')
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if check_border_colors(temp_image_path, tolerance=50):
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print(f"Border colors are the same for image: {filename}")
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if bg_choice == 'transparent':
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new_image = Image.new("RGBA", (1080, 1080), (255, 255, 255, 0))
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else:
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new_image = Image.new("RGBA", (1080, 1080), custom_color)
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width, height = image_with_no_bg.size
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scaling_factor = min(1080 / width, 1080 / height)
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new_size = (int(width * scaling_factor), int(height * scaling_factor))
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print(f"Border colors are different for image: {filename}")
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new_image = resize_and_crop_image(temp_image_path, crop_mode=crop_mode)
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if bg_choice == 'white':
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new_image = new_image.convert("RGBA")
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white_bg = Image.new("RGBA", new_image.size, "WHITE")
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custom_bg = Image.new("RGBA", new_image.size, custom_color)
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new_image = Image.alpha_composite(custom_bg, new_image)
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images_paths = []
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output_ext = 'jpg' if output_format == 'JPG' else 'png'
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output_path_without_watermark = os.path.join(output_folder, f"without_watermark_{os.path.splitext(filename)[0]}.{output_ext}")
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if output_format == 'JPG':
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new_image.save(output_path_without_watermark, format='PNG')
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images_paths.append(output_path_without_watermark)
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if watermark_path:
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watermark = Image.open(watermark_path).convert("RGBA")
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new_image_with_watermark = new_image.copy()
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new_image_with_watermark.save(output_path_with_watermark, format='PNG')
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images_paths.append(output_path_with_watermark)
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os.remove(temp_image_path)
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print(f"Processed image paths: {images_paths}")
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def process_images(zip_file, crop_mode='center', bg_method='rembg', watermark_path=None, output_format='PNG', bg_choice='transparent', custom_color="#ffffff", num_workers=4, progress=gr.Progress()):
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start_time = time.time()
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input_folder = "temp_input"
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output_folder = "temp_output"
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if os.path.exists(input_folder):
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os.makedirs(input_folder)
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os.makedirs(output_folder)
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try:
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with zipfile.ZipFile(zip_file, 'r') as zip_ref:
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zip_ref.extractall(input_folder)
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return [], None, 0
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processed_images = []
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original_images = []
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image_files = [os.path.join(input_folder, f) for f in os.listdir(input_folder) if f.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif'))]
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total_images = len(image_files)
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print(f"Total images to process: {total_images}")
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with ThreadPoolExecutor(max_workers=num_workers) as executor:
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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}
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for idx, future in enumerate(future_to_image):
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try:
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result = future.result()
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if result:
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processed_images.extend(result)
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original_images.append(future_to_image[future])
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except Exception as e:
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print(f"Error processing image {future_to_image[future]}: {e}")
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progress((idx + 1) / total_images, f"{idx + 1}/{total_images} images processed")
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output_zip_path = "processed_images.zip"
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with zipfile.ZipFile(output_zip_path, 'w') as zipf:
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for file in processed_images:
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processing_time = end_time - start_time
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print(f"Processing time: {processing_time} seconds")
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return original_images, processed_images, output_zip_path, processing_time
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def gradio_interface(zip_file, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
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progress = gr.Progress()
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watermark_path = watermark.name if watermark else None
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return process_images(zip_file.name, crop_mode, bg_method, watermark_path, output_format, bg_choice, custom_color, num_workers, progress)
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return gr.update(visible=True)
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return gr.update(visible=False)
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with gr.Blocks() as iface:
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gr.Markdown("# Image Background Removal and Resizing with Optional Watermark")
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gr.Markdown("Upload a ZIP or RAR file containing images, choose the crop mode, optionally upload a watermark image, and select the output format.")
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with gr.Row():
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crop_mode = gr.Radio(choices=["center", "top", "bottom", "left", "right"], label="Crop Mode", value="center")
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output_format = gr.Radio(choices=["PNG", "JPG"], label="Output Format", value="PNG")
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num_workers = gr.Slider(minimum=1, maximum=16, step=1, label="Number of Workers", value=2)
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bg_choice = gr.Radio(choices=["transparent", "white", "custom"], label="Background Choice", value="transparent", visible=True)
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custom_color = gr.ColorPicker(label="Custom Background Color", value="#ffffff", visible=False)
|
233 |
|
234 |
+
with gr.Row():
|
235 |
+
gallery_original = gr.Gallery(label="Original Images")
|
236 |
+
gallery_processed = gr.Gallery(label="Processed Images")
|
237 |
+
with gr.Row():
|
238 |
+
output_zip = gr.File(label="Download Processed Images as ZIP")
|
239 |
+
processing_time = gr.Textbox(label="Processing Time (seconds)")
|
240 |
+
|
241 |
bg_choice.change(show_color_picker, inputs=bg_choice, outputs=custom_color)
|
242 |
output_format.change(show_bg_choice, inputs=output_format, outputs=bg_choice)
|
243 |
|
|
|
|
|
|
|
|
|
244 |
def process(zip_file, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers):
|
245 |
+
original_images, processed_images, zip_path, time_taken = gradio_interface(zip_file, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers)
|
246 |
+
return original_images, processed_images, zip_path, f"{time_taken:.2f} seconds"
|
247 |
|
248 |
process_button = gr.Button("Process Images")
|
249 |
+
process_button.click(process, inputs=[zip_file, crop_mode, bg_method, watermark, output_format, bg_choice, custom_color, num_workers], outputs=[gallery_original, gallery_processed, output_zip, processing_time])
|
250 |
|
|
|
251 |
iface.launch()
|