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


def is_cat(x): return x[0].isupper() 

learn = load_learner("model.pkl")


im = PILImage.create('dog.jpg')
im.thumbnail((192,192))
im



learn.predict(im)


categories = ("dog","cat")
def classify_image(img):
    pred,idx,probs=learn.predict(img)
    return dict(zip(categories,map(float,probs)))


classify_image(im)

image = gr.inputs.Image(shape=(192,192))
label= gr.outputs.Label()
examples = ['dog.jpg','cat.jpg','example.jpg']

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