app.py

from pathlib import Path
from time import sleep
from time import time

from fastai.vision.all import *
from fastai.vision.widgets import *
from fastbook import *
from fastcore.parallel import *
from fastdownload import download_url
from fastai.learner import load_learner

import gradio as gr
from huggingface_hub import from_pretrained_fastai, notebook_login, push_to_hub_fastai
import timm
from torchvision.models import resnet18
import os

learn = load_learner('model.pkl')

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))}

demo=gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(num_top_classes=2)).launch(share=True)


if __name__ == "__main__":
    demo.launch()