app.py

___all___ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']

from fastai.vision.all import *
import gradio as gr

# Load the trained model
learn = load_learner('model.pkl')

# Define the categories based on your model's output
categories = learn.dls.vocab

# Define the function to classify images
def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

# Define the Gradio components
image = gr.Image(type='pil', label='Input Image')
label = gr.Label()
examples = ['example1.jpeg', 'example2.jpeg', 'example3.jpeg']  # Replace with your example images

# Create and launch the Gradio interface
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, title="Image Classifier", examples=examples)
intf.launch(inline=False)