import gradio as gr
from nbconvert import export
import numpy as np
from fastai.vision.all import *
import pathlib
import timm
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath

learner = load_learner("model.pkl")
categories = ('happy', 'upset')

def smileOrFrown(im):
    pred,idx,probs = learner.predict(im)
    actualPred = "happy"
    if (pred == "human face upset"):
        actualPred = "upset"
    
    return  actualPred + " " + str(dict(zip(categories, map(float, probs))))

demo = gr.Interface(
    smileOrFrown, 
    gr.Image(source="webcam", streaming=True), 
    "text",
    live=True
)
demo.launch()