app.py

import gradio as gr
from typing import Any
from fastai.vision.all import load_learner

learn = load_learner("assets/model.pkl")

CATEGORIES = ("azurite", "copper", "malachite")


def classify(input_image: Any) -> gr.Label:
    pred, idx, probs = learn.predict(input_image)
    return input_image, dict(zip(CATEGORIES, map(float, probs)))


demo = gr.Interface(
    fn=classify,
    inputs=gr.Image(
        label="Upload mineral",
        sources=["upload", "webcam"],
        height=224,
        width=224,
        type="pil",
    ),
    outputs=[
        gr.Image(label="Processed Image"),
        gr.Label(label="Result"),
    ],
    title="What ore is this?",
    examples=[
        "assets/malachite.jpeg",
        "assets/azurite.jpeg",
        "assets/copper.jpeg",
    ],
)
demo.launch()