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| import gradio as gr | |
| import numpy as np | |
| from PIL import Image | |
| import cv2 | |
| from rembg import remove | |
| def remove_background(image): | |
| try: | |
| # PIL β bytes | |
| img = Image.fromarray(np.array(image)) | |
| # π₯ AI Background Remove | |
| output = remove(img) | |
| # RGBA image | |
| output = np.array(output) | |
| # π₯ Edge smooth (important) | |
| if output.shape[2] == 4: | |
| alpha = output[:, :, 3] | |
| # smooth mask | |
| alpha = cv2.GaussianBlur(alpha, (5,5), 0) | |
| output[:, :, 3] = alpha | |
| return Image.fromarray(output) | |
| except Exception as e: | |
| print("ERROR:", e) | |
| return image | |
| demo = gr.Interface( | |
| fn=remove_background, | |
| inputs=gr.Image(type="pil"), | |
| outputs=gr.Image(type="pil"), | |
| title="π₯ AI Background Remover (Pro)", | |
| description="Clean Cut + Smooth Hair + HD Output" | |
| ) | |
| demo.launch() |