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import gradio as gr | |
from fastai.vision.all import * | |
import skimage | |
learn = load_learner('howdy_mody.pkl') | |
labels = learn.dls.vocab | |
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 = "Modi, 2014ka, 2021ka" | |
description = "Its fun project to predict whether modi image is from 2014 time period or from 2021, based on his beard size" | |
article="<p style='text-align: center'><a href='https://mldurga.github.io/easydl/fastbook/2021/08/04/Fastbook-chapter2.html' target='_blank'>Blog post</a></p>" | |
interpretation='default' | |
#examples = ['Neutral2.jpeg','smoke1.jpeg','smoke2.jpeg','fire1.png'] | |
enable_queue=True | |
gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,interpretation=interpretation,enable_queue=enable_queue).launch() |