app.py

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

learn = load_learner("dog_detector.pkl")

def classify_image(img):
	pred,idx,probs = learn.predict(img)
	return dict(zip(learn.dls.vocab, map(float,probs)))

#im = PILImage.create("1.jpg")
#print (classify_image(im))

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['golden.jpg', 'lab.jpg', 'corgi.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False, share=False)