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Browse files- cat1.jpg +0 -0
- dog1.jpg +0 -0
- dogs_vs_cats_test.py +78 -0
cat1.jpg
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dog1.jpg
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dogs_vs_cats_test.py
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#!/usr/bin/env python
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# coding: utf-8
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# # Dog v Cat
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# In[5]:
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#/export
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from fastai.vision.all import *
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import gradio as gr
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def is_cat(x): return x[0].isupper()
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# In[6]:
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im = PILImage.create('dog1.jpg')
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im.thumbnail((192, 192))
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im
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# In[8]:
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#/export
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import pathlib
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temp = pathlib.PosixPath
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pathlib.PosixPath = pathlib.WindowsPath
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learn = load_learner('model.pkl')
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# In[11]:
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learn.predict(im)
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# In[12]:
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#/export
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categories = ('Dog', 'Cat')
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def classify_images(img):
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pred,idx,probs = learn.predict(img)
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return dict(zip(categories, map(float, probs)))
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# In[13]:
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classify_images(im)
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# In[14]:
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#/export
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image = gr.inputs.Image(shape = (192,192))
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label = gr.outputs.Label()
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examples = ['dog1.jpg', 'cat1.jpg']
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intf = gr.Interface(fn = classify_images, inputs = image, outputs = label, examples = examples)
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intf.launch(inline = False)
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# ## export -
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# In[28]:
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import nbdev
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nbdev.export.nb_export('dogs_vs_cats_test.ipynb', 'app')
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print('Export successful')
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