from fastai.vision.all import *
from fastai.text.all import *
from fastai.collab import *
from fastai.tabular.all import * 

# import pathlib
# temp = pathlib.PosixPath
# pathlib.PosixPath = pathlib.WindowsPath

import gradio as gr

learn = load_learner('model.pkl')   

categories = ('golden', 'not golden')

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


image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label(num_top_classes=2)
#examples = ["golden_retriever.jpg", "cat.jpg", "dog.jpg"]

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