#!/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="

Reference

", examples=['keeshond.jpeg', 'maine_coon.jpeg'] ).launch(share=True) # In[ ]: