app.py

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

learn = load_learner('export.pkl')

labels = learn.dls.vocab
def predict(img):
	pred,pred_idx,probs = learn.predict(img)
	return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Pet Breed Classifier"
description = "A pet breed classifier from Tanishq's tutorial"
examples = ['mainecoon.jpg','retriever.webp']
enable_queue=True
gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,examples=examples,enable_queue=enable_queue).launch()