| import gradio as gr | |
| from inference import predict | |
| from PIL import Image | |
| import io | |
| def predict_image(img: Image.Image): | |
| with io.BytesIO() as buffer: | |
| img.save(buffer, format="JPEG") | |
| img_bytes = buffer.getvalue() | |
| return predict(img_bytes) | |
| iface = gr.Interface( | |
| fn=predict_image, | |
| inputs=gr.Image(type="pil"), | |
| outputs=gr.JSON(), | |
| title="Sitting Posture Detection", | |
| description="Upload an image to detect sitting postures using YOLOv8" | |
| ) | |
| if __name__ == "__main__": | |
| iface.launch() | |