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

#this func is from learner


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



# #posix path error handler from stack overflow
# import pathlib
# temp = pathlib.PosixPath
# pathlib.PosixPath = pathlib.WindowsPath

learn = load_learner("model.pkl")

categories = ('Dog','Cat')

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

image = gr.components.Image(shape = (192,192))
# image = gr.components
label = gr.components.Label()
examples = ['dog.jpg']

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