#!/usr/bin/env python # coding: utf-8 # # Dog v Cat # In[5]: #/export from fastai.vision.all import * import gradio as gr def is_cat(x): return x[0].isupper() # In[6]: im = PILImage.create('dog1.jpg') im.thumbnail((192, 192)) im # In[8]: #/export import pathlib temp = pathlib.PosixPath pathlib.PosixPath = pathlib.WindowsPath learn = load_learner('model.pkl') # In[11]: learn.predict(im) # In[12]: #/export categories = ('Dog', 'Cat') def classify_images(img): pred,idx,probs = learn.predict(img) return dict(zip(categories, map(float, probs))) # In[13]: classify_images(im) # In[14]: #/export image = gr.inputs.Image(shape = (192,192)) label = gr.outputs.Label() examples = ['dog1.jpg', 'cat1.jpg'] intf = gr.Interface(fn = classify_images, inputs = image, outputs = label, examples = examples) intf.launch(inline = False, share = True)