Update dog_vs_cat.py

dog_vs_cat.py

@@ -0,0 +1,58 @@
+# -*- coding: utf-8 -*-
+"""Dog Vs Cat.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1_3DbuTTvb83jCX-oa6nmg4bMAAyuPNdo
+"""
+
+!pip install gradio
+!pip install fastbook
+!pip install -U duckduckgo_search
+!pip install --upgrade duckduckgo-search
+
+"""# Dogs vs Cats"""
+
+from fastbook import *
+from fastai.vision.all import *
+import gradio as gr
+
+def is_cat(x) : return x[0].isupper
+
+urls = search_images_ddg('dog', max_images=1)
+dest = 'images/dogs.jpg'
+download_url(dest = dest, url=urls[0], show_progress=False)
+
+urls = search_images_ddg('cat', max_images=1)
+dest = 'images/cats.jpg'
+download_url(dest = dest, url=urls[0], show_progress=False)
+
+urls = search_images_ddg('animal', max_images=1)
+dest = 'images/dunno.jpg'
+download_url(dest = dest, url=urls[0], show_progress=False)
+
+im = PILImage.create('images/dogs.jpg')
+im.thumbnail((192,192))
+im
+
+learn = load_learner('model.pkl')
+learn.predict(im)
+
+categories = ('Dog','Cat')
+
+def classify_images(img):
+  pred, idx, probs = learn.predict(img)
+  return dict(zip(categories, map(float,probs)))
+
+classify_images(im)
+
+intf = gr.Interface(
+    fn=classify_images,
+    inputs=gr.Image(),
+    outputs=gr.Label(),
+    examples=['images/dogs.jpg', 'images/cats.jpg', 'images/dunno.jpg']
+)
+
+intf.launch()
+