File size: 1,032 Bytes
87e5c74
aadd294
 
6e135e3
1407cdc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d5702ed
1407cdc
d5702ed
1407cdc
d5702ed
1407cdc
 
d5702ed
1407cdc
 
d5702ed
d1a43e5
1407cdc
 
 
d5702ed
1407cdc
 
 
 
d5702ed
1407cdc
 
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
import platform
import pathlib
plt = platform.system()
pathlib.WindowsPath = pathlib.PosixPath

#import subprocess
#import sys

#def install(package):
#    subprocess.check_call([sys.executable, "-m", "pip", "install", package])

#install('fastbook')


# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.

# %% auto 0
__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'interface', 'classify_image']

# %% app.ipynb 1
#from fastbook import *

from fastai.vision.all import *
from fastai.vision.widgets import ImageClassifierCleaner

import gradio as gr

# %% app.ipynb 2
learn = load_learner('./model.pkl')

# %% app.ipynb 3
categories=('bird','forest')

def classify_image(img):
    pred,indx,probs=learn.predict(img)
    return dict(zip(categories,map(float,probs)))


# %% app.ipynb 4
image=gr.inputs.Image(shape=(192,192))
label=gr.outputs.Label()
examples=['a.jpg', 'b.jpg','c.jpg','d.jpg']

interface=gr.Interface(fn=classify_image, inputs=image ,outputs=label,examples=examples)
interface.launch(inline=False)