app.py

# 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)