app.py

import gradio as gr
from fastai.vision.all import *
from huggingface_hub import from_pretrained_fastai
import pathlib

# loading the model
windows_backup = pathlib.WindowsPath
pathlib.WindowsPath = pathlib.PosixPath
learn = from_pretrained_fastai("pka007/flowerclassifier_model")
pathlib.WindowsPath = windows_backup
labels = ['Jasmine', 'Marigold', 'Rose', 'sunflower', 'tulip']
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 = "Flower Classifier"
description = "A flower classifier trained on the images downloaded from the internet."
examples = ['sunflower.jpg','marigold.jpg']

intf = gr.Interface(fn=predict,inputs=gr.Image(type="pil"),outputs=gr.Label(),title=title,description=description,examples=examples)
intf.launch()