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

learn=load_learner('model.pkl')

categories=('not psilocybe','psilocybe')

def classify(img):
    pred,idx,probs=learn.predict(img)
    return dict(zip(categories, map(float,probs)))


title = "Psilocybe classifier"
description = "Please do not consume unknown mushrooms based on this app. With a more accurate model this could complement a harm minimization approach."
image = gr.Image()
label= gr.Label()
examples=['psilocybe.jpg']
intf=gr.Interface(fn=classify,inputs=image,outputs=label,title=title, description=description, examples=examples)
intf.launch(inline=False)