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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()
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