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| import gradio as gr | |
| from fastai.vision.all import * | |
| # Load your trained model | |
| def load_model(): | |
| path = 'export.pkl' | |
| learn = load_learner(path) | |
| return learn | |
| learn = load_model() | |
| # Define prediction function | |
| def predict_image(img): | |
| pred, pred_idx, probs = learn.predict(img) | |
| return {learn.dls.vocab[i]: float(probs[i]) for i in range(len(learn.dls.vocab))} | |
| # Ensure this matches the function name used in the Interface | |
| interface = gr.Interface(fn=predict_image, | |
| inputs=gr.Image(type="pil"), # Corrected to use gr.Image | |
| outputs=gr.Label(num_top_classes=3), | |
| title="Image Classifier", | |
| description="Upload an image to classify.") | |
| # Use the defined 'interface' variable to launch the Gradio interface | |
| if __name__ == "__main__": | |
| interface.launch() | |