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

learn = load_learner('model.pkl')
labels = ['brown_spots', 'green', 'spoiled', 'yellow']


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 = "Banana Quality Classifier"
description = "A banana classifier that can classify bananas into 4 categories based on their quality"
examples = ['yellow_banana.jpg', 'banana.jpg', 'yellow_banana_2.jpg', 'green_banana.jpg', 'green_banana_2.jpg', 'banana_with_brown_spots.jpg', 
            'brown_spots_2.jpeg', 'black_banana.jpg', 'black_banana_2.jpeg','black_banana_3.jpeg']

gr.Interface(
    fn=predict,
    inputs=gr.Image(sources=["upload", "webcam", "clipboard"]),
    outputs=gr.Label(num_top_classes=4),
    title=title,
    description=description,
    examples=examples
).launch()