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

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


categories = ('Dog', 'Cat')
learn = load_learner('model.pkl')
def classify_image(img):
    pred , idx , probs = learn.predict(img)
    return dict(zip(categories , map(float,probs)))

image = gr.Image()
label = gr.Label()
examples = ['dog.jpg', 'cat.jpg', 'dumo.jpg']
demo = gr.Interface(fn=classify_image, inputs=image, outputs= label)
demo.launch(inline = False)

m = learn.model
ps = list(m.parameters())

ps[1]