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| import gradio as gr | |
| from handler import EndpointHandler | |
| import io | |
| # Model loading | |
| handler = EndpointHandler(".") | |
| def predict(image): | |
| try: | |
| # 1. PIL Image ko Bytes me convert karein | |
| buf = io.BytesIO() | |
| image.save(buf, format='PNG') | |
| image_bytes = buf.getvalue() | |
| # 2. Handler ko DICTIONARY bhejein (Jaise wo .pop() kar sake) | |
| # Hum wahi format bhej rahe hain jo Hugging Face Inference API bhejti hai | |
| result = handler({"inputs": image_bytes}) | |
| # 3. Result extract karein | |
| if isinstance(result, dict): | |
| return result.get("prediction", "No Prediction Found") | |
| return str(result) | |
| except Exception as e: | |
| return f"Backend Error: {str(e)}" | |
| # Gradio Interface | |
| demo = gr.Interface( | |
| fn=predict, | |
| inputs=gr.Image(type="pil"), | |
| outputs="text", | |
| title="Master Brain Captcha Solver" | |
| ) | |
| demo.launch() | |