app.py

#!/usr/bin/env python
# coding: utf-8

# In[1]:


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


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def breed_name(x):
    return ''.join([char for char in x if not char.isdigit()][:-5])
learn = load_learner('pet_breeds.pkl')


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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))}


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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)


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