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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) |