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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)