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

# --- Model Loading (Assumes model.pkl exists in the root) ---
try:
    learn = load_learner('export.pkl')
except Exception:
    print("Error loading export.pkl. Check file path/existence.")
    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))}

# --- Interface Setup ---
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>"
enable_queue=True
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,
             article=article,
             examples=examples)

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