# app.py __all__ = ['bird', 'learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf'] # Load categories from label.txt with open('labels.txt', 'r') as file: categories = [line.strip() for line in file.readlines()] # Load the model from fastai.vision.all import * import gradio as gr learn = load_learner('model.pkl') # Define the classification function def classify_image(img): preds, idx, probs = learn.predict(img) return dict(zip(categories, map(float, probs))) # Gradio components image = gr.components.Image() label = gr.components.Label(num_top_classes=3) # Create and launch the interface intf = gr.Interface(fn=classify_image, inputs=image, outputs=label) intf.launch(inline=False, share=True)