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

import pathlib
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath

learn = load_learner('Pickle_SD_Model.pkl') 

labels = learn.dls.vocab

set_label = gr.outputs.Textbox(label="Predicted Class")

set_prob = gr.outputs.Label(num_top_classes=4, label="Predicted Probability Per Class")


def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Tomato Disease Classifier"
description = "Classify Tomato Disease from leaf"
interpretation='default'

enable_queue=True

gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(256,256)), outputs=gr.outputs.Label(num_top_classes=4) ).launch(share=True)