| import gradio as gr | |
| from PIL import Image | |
| from model import predict | |
| def predict_crop(image, crop_name): | |
| if image is None or not crop_name: | |
| return {"error": "Image and crop_name are required"} | |
| prediction, confidence = predict(image, crop_name) | |
| return { | |
| "prediction": prediction, | |
| "confidence": confidence | |
| } | |
| gr.Interface( | |
| fn=predict_crop, | |
| inputs=[ | |
| gr.Image(type="pil"), | |
| gr.Textbox(label="Crop Name (banana, tomato, rice)") | |
| ], | |
| outputs="json", | |
| api_name="/predict_crop", | |
| title="LeafBuddy Crop Disease Detection" | |
| ).launch() | |