| import gradio as gr | |
| from fastai.vision.all import load_learner | |
| from PIL import Image | |
| model = load_learner('./export.pkl') | |
| def classify_image(img): | |
| # Convert the image to a format the model expects | |
| img = Image.fromarray(img.astype('uint8'), 'RGB') | |
| # Make a prediction | |
| pred, idx, probs = model.predict(img) | |
| # Return the result | |
| return {model.dls.vocab[i]: float(probs[i]) for i in range(len(model.dls.vocab))} | |
| demo = gr.Interface(fn=classify_image, inputs="image", outputs="label") | |
| if __name__ == "__main__": | |
| demo.launch() |