import torch
model = torch.hub.load('model.pkl')
import requests
from PIL import Image
from torchvision import transforms

# Download human-readable labels for ImageNet.


learn=load_learner('model.pkl')
categories=('Dogs','Cats')
def classify_img(img):
    pred,idx,probs=learn.predict(img)
    return dict(zip(categories,map(float,probs)))
  
import gradio as gr
image =gr.inputs.Image(shape=(192,192))
label =gr.outputs.Label()
examples=['dog.jpg']

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