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

# --- Model Loading (Assumes model.pkl exists in the root) ---
try:
    learn = load_learner('model.pkl')
except Exception:
    print("Error loading model.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 ---
examples = ["birman.jpg", "pomerian.jpg", "british.jpg"]
title = "Pet Breed Classifier"
description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"

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()