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

try:
    learn = load_learner('model.pkl') 
except Exception as e:
    print(f"Error loading model.pkl: {e}")
    raise

labels = learn.dls.vocab

def predict(img):
    img = PILImage.create(img)
    pred, pred_idx, probs = learn.predict(img) 
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Sports Classifier"
description = "A sports classifier trained on the images from Google. Created as a demo for Gradio and HuggingFace Spaces."
article="<p style='text-align: center'><a href='www.linkedin.com/in/shivamkswarnkar' target='_blank'>Linkedin Profile</a></p>"
examples = ["badminton.jpg", "cricket.jpg", "swimming.jpg"] 

demo = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs=gr.Label(num_top_classes=3),
    title=title,
    description=description,
    examples=examples
)

if __name__ == "__main__":
    demo.launch()