File size: 883 Bytes
4c5099e
 
 
 
 
 
 
 
 
 
 
 
 
 
6ed7516
4c5099e
 
 
 
 
 
 
4a4b92c
 
4c5099e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4a4b92c
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
#!/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 is_cat(x): return x[0].isupper()


# In[3]:




# In[5]:


#/export
learn = load_learner('model.pkl')


# In[6]:



# 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]:




# 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]:




# In[12]:




# In[13]:




# # Exporting

# In[15]:




# In[ ]:





# In[34]:




# In[ ]: