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Update app.py
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app.py
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import gradio as gr
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from PIL import Image
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from rembg import remove
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import io
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with gr.Row():
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demo.launch()
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import gradio as gr
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from rembg import remove
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from PIL import Image
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import io
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# Preserve original resolution & optimize for high-res images
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def process_image(image, background_type, bg_color, bg_image):
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try:
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input_image = Image.open(image).convert("RGBA")
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# Use rembg with bytes instead of loading into RAM completely
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buffered = io.BytesIO()
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input_image.save(buffered, format="PNG")
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result = remove(buffered.getvalue())
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output = Image.open(io.BytesIO(result)).convert("RGBA")
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if background_type == "Solid Color":
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bg = Image.new("RGBA", output.size, bg_color)
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bg.paste(output, (0, 0), output)
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return bg
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elif background_type == "Custom Image" and bg_image:
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custom_bg = Image.open(bg_image).convert("RGBA").resize(output.size)
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custom_bg.paste(output, (0, 0), output)
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return custom_bg
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else:
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return output
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except Exception as e:
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return f"❌ Error: {str(e)}"
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# For multiple images
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def batch_process(images, background_type, bg_color, bg_image):
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return [process_image(img, background_type, bg_color, bg_image) for img in images]
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# Gradio UI
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with gr.Blocks() as demo:
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gr.Markdown("## 🎯 High-Resolution AI Background Remover with Custom Background")
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with gr.Row():
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images_input = gr.File(label="📤 Upload High-Res Image(s)", file_types=["image"], file_count="multiple")
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with gr.Row():
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background_type = gr.Radio(
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["Transparent", "Solid Color", "Custom Image"],
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label="Choose Background Type",
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value="Transparent"
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)
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bg_color = gr.ColorPicker(label="Solid Color", value="#ffffff", visible=False)
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bg_image = gr.File(label="Custom Background Image", file_types=["image"], visible=False)
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output_gallery = gr.Gallery(label="🖼️ Output Images", columns=2, height=600)
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def toggle_visibility(bg_type):
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return (
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gr.update(visible=(bg_type == "Solid Color")),
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gr.update(visible=(bg_type == "Custom Image"))
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)
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background_type.change(toggle_visibility, inputs=background_type, outputs=[bg_color, bg_image])
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run_btn = gr.Button("🚀 Start Processing")
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run_btn.click(fn=batch_process, inputs=[images_input, background_type, bg_color, bg_image], outputs=output_gallery)
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demo.launch()
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