changes

app.py

@@ -1,7 +1,123 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# ## Dogs v Cats
+
+# In[32]:
+
+
+#/default_exp app
+
+
+# In[1]:
+
+
+get_ipython().system('pip install gradio')
+
+
+# In[2]:
+
+
+#/export
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def is_cat(x): return x[0].isupper()
+
+
+# In[3]:
+
+
+im = PILImage.create('dog.jpg')
+im.thumbnail((192,192))
+im
+
+
+# In[5]:
+
+
+#/export
+learn = load_learner('model.pkl')
+
+
+# In[6]:
+
+
+learn.predict(im)
+
+
+# In[7]:
+
+
+#/export
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+
+# In[8]:
+
+
+classify_image(im)
+
+
+# In[10]:
+
+
+#/export
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)
+
+
+# In[11]:
+
+
+m = learn.model
+
+
+# In[12]:
+
+
+ps = list(m.parameters())
+
+
+# In[13]:
+
+
+ps[1]
+
+
+# # Exporting
+
+# In[15]:
+
+
+get_ipython().system('pip install nbdev')
+
+
+# In[ ]:
+
+
+
+
+
+# In[34]:
+
+
+import nbdev
+#nbdev.export.nb_export('Dogs v Cats.ipynb', 'app')
+nbdev.export.nb_export('Dogs v Cats.ipynb', './')
+print('Export successful')
+
+
+# In[ ]:
+
+
+
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()