__all__ = ["learn", "classify_image","categoris","image","label","examples","intf"]

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

plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
learn =load_learner("model.pkl")

categoris = ("bnana","orange","pineapple")

def classify_image(im):
    pred,index,probs = learn.predict(im)
    return dict(zip(categoris,map(float,probs)))


title = "Fruits detector"
description = "A fruits classifier trained on the scrapped photos of pineapple,orange and bnanas. Created as a demo for Gradio and HuggingFace Spaces."

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ["bnana photo.jpg"]

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