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#!/usr/bin/env python
# coding: utf-8
# In[1]:
import gradio as gr
from fastai.vision.all import *
# In[3]:
def breed_name(x):
return ''.join([char for char in x if not char.isdigit()][:-5])
learn = load_learner('pet_breeds.pkl')
# In[4]:
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))}
# In[5]:
gr.Interface(fn=predict,
inputs=gr.components.Image(height=512, width=512),
outputs=gr.components.Label(num_top_classes=3),
title='What breed is it ?',
description='A pet breeds classifier',
article="<p style='text-align: center'><a href='https://www.tanishq.ai/blog/posts/2021-11-16-gradio-huggingface.html' target='_blank'>Reference</a></p>",
examples=['keeshond.jpeg', 'maine_coon.jpeg']
).launch(share=True)
# In[ ]:
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