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', 'green_banana.jpg', 'banana_with_brown_spots.jpg', 'black_banana.jpg', 'banana.jpg']
interpretation='default'
enable_queue=True

gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(shape=(512, 512)),
        gr.Image(source="webcam", shape=(512, 512), label="Capture from Webcam")
        ],
    outputs=gr.outputs.Label(num_top_classes=4),
    title=title,
    description=description,
    examples=examples,
    interpretation=interpretation,
    enable_queue=enable_queue
).launch()