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Version 1

Create own dataset from Google Images

In [47]:
from fastai.vision import *
from fastai.widgets import *

Create directory and upload url files into your server

In [24]:
folder='chimpanzee'
file = 'urls_chimpanzee.csv'
In [28]:
folder = 'gorilla'
file = 'urls_gorilla.csv'
In [31]:
folder = 'orangutan'
file = 'urls_orangutan.csv'
In [34]:
folder = 'capuchin'
file = 'urls_capuchin.csv'
In [11]:
path = Path('data/monkeys')
In [35]:

dest = path/folder
dest.mkdir(parents=True, exist_ok=True)
In [22]:
path.ls()
Out[22]:
[PosixPath('data/monkeys/gorilla'),
 PosixPath('data/monkeys/capuchin'),
 PosixPath('data/monkeys/orangutan'),
 PosixPath('data/monkeys/chimpanzee')]
In [19]:
##!mv data/monkeys/urls_orangutan.csv data/monkeys/orangutan/

Download images

In [3]:
classes = ['chimpanzee', 'gorilla', 'orangutan', 'capuchin']
In [36]:
download_images(path/file, dest)
Error x-raw-image:///641230a1731f76166ded3f030d7a39ca3ff9510dab963385bab37a3ef6ffc7c8 No connection adapters were found for 'x-raw-image:///641230a1731f76166ded3f030d7a39ca3ff9510dab963385bab37a3ef6ffc7c8' Error x-raw-image:///430f85138d533065d1d8d1fbfda3126d13fa96a7af3f52294a8f7c0a1d08017b No connection adapters were found for 'x-raw-image:///430f85138d533065d1d8d1fbfda3126d13fa96a7af3f52294a8f7c0a1d08017b' Error x-raw-image:///acbe54feaf63b61cfb04fce19eebf4726c8a91e55df02248dd32eedac40c653f No connection adapters were found for 'x-raw-image:///acbe54feaf63b61cfb04fce19eebf4726c8a91e55df02248dd32eedac40c653f' Error https://cdn.vox-cdn.com/thumbor/6_HUTpo6OX5YG2K--tZIq3MA938=/2x0:599x336/1600x900/cdn.vox-cdn.com/uploads/chorus_image/image/51400323/monkey2.0.gif HTTPSConnectionPool(host='cdn.vox-cdn.com', port=443): Read timed out. (read timeout=4) Error x-raw-image:///6ac0172e376b4206fc18064bca7c675591677da28f473066f45f318edf0dc34d No connection adapters were found for 'x-raw-image:///6ac0172e376b4206fc18064bca7c675591677da28f473066f45f318edf0dc34d' Error http://planetofthemonkeys.com/wp-content/uploads/2013/08/kappori-capuchin.jpg HTTPConnectionPool(host='planetofthemonkeys.com', port=80): Max retries exceeded with url: /wp-content/uploads/2013/08/kappori-capuchin.jpg (Caused by ConnectTimeoutError(<urllib3.connection.HTTPConnection object at 0x7fc248886080>, 'Connection to planetofthemonkeys.com timed out. (connect timeout=4)'))
Verify the images
In [37]:
for c in classes:
    print(c)
    verify_images(path/c)
chimpanzee
cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000384.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000644.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000743.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000477.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000123.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000717.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000382.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000106.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000136.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000737.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000670.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000461.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000661.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000142.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000732.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000310.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000627.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000044.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000679.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000292.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000688.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000261.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000214.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000727.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000531.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000103.jpg'> Corrupt EXIF data. Expecting to read 4 bytes but only got 0. cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000130.png'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000397.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000744.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000128.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000651.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000566.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000498.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000203.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000721.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000422.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000414.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000399.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000182.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000006.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000217.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000667.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000611.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000592.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000215.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000607.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000720.gif'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000356.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000752.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000325.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000750.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000572.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000047.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000316.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000195.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000634.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000699.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000403.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000653.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000668.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000324.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000610.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000511.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000683.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000588.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000536.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000418.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000401.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000706.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000236.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000749.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000628.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000068.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000153.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000708.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000702.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000025.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000122.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000739.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000313.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000251.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000562.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000264.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000108.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000020.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000156.png'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000073.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/chimpanzee/00000449.jpg'> gorilla
cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000205.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000371.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000537.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000105.png'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000089.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000645.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000214.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000531.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000429.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000043.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000473.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:931: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images 'to RGBA images')
cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000250.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000487.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000631.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000160.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000651.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000127.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000484.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000540.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000297.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000607.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000594.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000030.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000347.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000560.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000239.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000684.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000668.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000097.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000324.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000593.png'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000320.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000692.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000471.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000442.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000334.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000224.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000479.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000458.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000647.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000245.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000321.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000037.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000313.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000641.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000485.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000488.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000219.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000686.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/gorilla/00000374.jpg'> orangutan
cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000477.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000383.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000046.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000237.jpeg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000589.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000678.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000434.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000671.jpg'> data/monkeys/orangutan/00000727.JPG: Removing corrupt EXIF data cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000041.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000531.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000075.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000565.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000637.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000512.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000448.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000626.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000240.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000369.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000119.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000611.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000077.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000431.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000572.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000452.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000244.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000247.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000337.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000511.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000364.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000536.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000525.png'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000600.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000122.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000302.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000462.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000323.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000319.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000066.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/orangutan/00000449.jpg'> capuchin cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000441.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple'
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000393.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000043.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000125.JPG'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000469.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000072.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000527.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000338.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000508.png'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000569.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000258.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000277.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000622.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000427.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000606.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000255.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000466.jpg'>
/home/ubuntu/anaconda3/lib/python3.6/site-packages/PIL/Image.py:984: UserWarning: Couldn't allocate palette entry for transparency "for transparency")
int() argument must be a string, a bytes-like object or a number, not 'tuple' cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000212.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000246.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000321.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000503.jpg'> cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000092.jpg'> Corrupt EXIF data. Expecting to read 4 bytes but only got 0. cannot identify image file <_io.BufferedReader name='data/monkeys/capuchin/00000374.jpg'>

View data

In [4]:
np.random.seed(42) # Set random seed to fixed beforehand to ensure we
# get the same validation set always
In [3]:
!ls data/
monkeys
In [8]:
!ls data/monkeys/gorilla/
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00000553.jpg 00000695.jpg 00000132.jpg 00000272.jpg 00000411.jpg 00000554.jpg 00000696.jpg 00000133.jpg 00000273.jpg 00000412.jpg 00000555.jpg 00000697.jpg 00000134.jpg 00000274.jpg 00000413.jpg 00000556.jpg 00000698.jpg 00000135.jpg 00000275.jpg 00000414.jpg 00000557.jpg 00000699.jpg 00000136.jpg 00000276.jpg 00000415.jpg 00000558.jpg 00000700.jpg 00000137.jpg 00000277.jpg 00000416.jpg 00000559.jpg 00000701.ashx 00000138.jpg 00000278.jpg 00000417.jpg 00000561.jpg 00000702.jpg
In [12]:
path = 'data/monkeys'
In [15]:
# Always create a validation set 
# uses the default batch size of 32
data = ImageDataBunch.from_folder(path, train=".", valid_pct=0.2,
        ds_tfms=get_transforms(), size=224).normalize(imagenet_stats)
In [16]:
data.classes
Out[16]:
['capuchin', 'chimpanzee', 'gorilla', 'orangutan']
In [17]:
data.show_batch(rows=3, figsize=(7,8))
Notebook Image
In [22]:
data.classes, data.c, len(data.train_ds), len(data.valid_ds)
Out[22]:
(['capuchin', 'chimpanzee', 'gorilla', 'orangutan'], 4, 2088, 521)

Train model

In [24]:
learn = cnn_learner(data, models.resnet34, metrics=[error_rate, accuracy])
In [26]:
learn.fit_one_cycle(6)
In [27]:
learn.save('stage-1')
In [28]:
learn.unfreeze()
In [29]:
learn.lr_find()
LR Finder is complete, type {learner_name}.recorder.plot() to see the graph.
In [31]:
learn.recorder.plot()
Notebook Image
In [32]:
learn.fit_one_cycle(2, max_lr=slice(1e-5, 1e-4))
In [33]:
learn.save('stage-2')

Interpretation

In [35]:
interp = ClassificationInterpretation.from_learner(learn)
In [36]:
interp.plot_confusion_matrix()
Notebook Image
In [37]:
interp.most_confused()
Out[37]:
[('gorilla', 'chimpanzee', 6),
 ('chimpanzee', 'gorilla', 5),
 ('capuchin', 'chimpanzee', 3),
 ('orangutan', 'chimpanzee', 3),
 ('chimpanzee', 'capuchin', 2),
 ('orangutan', 'capuchin', 2),
 ('gorilla', 'orangutan', 1)]
In [44]:
len(top_loss_paths)
Out[44]:
521
In [34]:
doc(ClassificationInterpretation)
In [23]:
doc(cnn_learner)
In [18]:
doc(ImageDataBunch)
In [21]:
doc(DataBunch)

Cleaning up the bad data

In [40]:
losses,idxs = interp.top_losses()
In [45]:
top_loss_paths = data.valid_ds.x[idxs]
In [51]:
ds, idxs = DatasetFormatter.from_toplosses(learn, ds_type=DatasetType.Train)
In [55]:
ImageCleaner(ds, idxs, path)
HBox(children=(VBox(children=(Image(value=b'\xff\xd8\xff\xe0\x00\x10JFIF\x00\x01\x01\x01\x00d\x00d\x00\x00\xff…
Button(button_style='primary', description='Next Batch', layout=Layout(width='auto'), style=ButtonStyle())
In [59]:
!ls ./data/monkeys
capuchin cleaned.csv models urls_capuchin.csv urls_gorilla.csv chimpanzee gorilla orangutan urls_chimpanzee.csv urls_orangutan.csv
In [70]:
db = ImageList.from_csv(path, 'cleaned.csv', folder='.').split_none().label_from_df().transform(get_transforms(), size=224).databunch()
In [71]:
learn_cln = cnn_learner(db, models.resnet34, metrics=['error_rate','accuracy'])
In [72]:
learn_cln.load('stage-2')
Out[72]:
Learner(data=ImageDataBunch;

Train: LabelList (1956 items)
x: ImageList
Image (3, 224, 224),Image (3, 224, 224),Image (3, 224, 224),Image (3, 224, 224),Image (3, 224, 224)
y: CategoryList
gorilla,gorilla,gorilla,gorilla,gorilla
Path: data/monkeys;

Valid: LabelList (0 items)
x: ImageList

y: CategoryList

Path: data/monkeys;

Test: None, model=Sequential(
  (0): Sequential(
    (0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (2): ReLU(inplace)
    (3): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)
    (4): Sequential(
      (0): BasicBlock(
        (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (1): BasicBlock(
        (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (2): BasicBlock(
        (conv1): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (5): Sequential(
      (0): BasicBlock(
        (conv1): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (downsample): Sequential(
          (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)
          (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
      (1): BasicBlock(
        (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (2): BasicBlock(
        (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (3): BasicBlock(
        (conv1): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (6): Sequential(
      (0): BasicBlock(
        (conv1): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (downsample): Sequential(
          (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)
          (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
      (1): BasicBlock(
        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (2): BasicBlock(
        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (3): BasicBlock(
        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (4): BasicBlock(
        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (5): BasicBlock(
        (conv1): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (7): Sequential(
      (0): BasicBlock(
        (conv1): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (downsample): Sequential(
          (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)
          (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        )
      )
      (1): BasicBlock(
        (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (2): BasicBlock(
        (conv1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(inplace)
        (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
        (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
  )
  (1): Sequential(
    (0): AdaptiveConcatPool2d(
      (ap): AdaptiveAvgPool2d(output_size=1)
      (mp): AdaptiveMaxPool2d(output_size=1)
    )
    (1): Flatten()
    (2): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (3): Dropout(p=0.25)
    (4): Linear(in_features=1024, out_features=512, bias=True)
    (5): ReLU(inplace)
    (6): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (7): Dropout(p=0.5)
    (8): Linear(in_features=512, out_features=4, bias=True)
  )
), opt_func=functools.partial(<class 'torch.optim.adam.Adam'>, betas=(0.9, 0.99)), loss_func=FlattenedLoss of CrossEntropyLoss(), metrics=['error_rate', 'accuracy'], true_wd=True, bn_wd=True, wd=0.01, train_bn=True, path=PosixPath('data/monkeys'), model_dir='models', callback_fns=[functools.partial(<class 'fastai.basic_train.Recorder'>, add_time=True, silent=False)], callbacks=[], layer_groups=[Sequential(
  (0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False)
  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (2): ReLU(inplace)
  (3): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False)
  (4): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (5): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (6): ReLU(inplace)
  (7): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (8): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (9): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (10): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (11): ReLU(inplace)
  (12): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (13): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (14): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (15): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (16): ReLU(inplace)
  (17): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (18): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (19): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
  (20): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (21): ReLU(inplace)
  (22): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (23): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (24): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)
  (25): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (26): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (27): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (28): ReLU(inplace)
  (29): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (30): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (31): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (32): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (33): ReLU(inplace)
  (34): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (35): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (36): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (37): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (38): ReLU(inplace)
  (39): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (40): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
), Sequential(
  (0): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (2): ReLU(inplace)
  (3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (4): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (5): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)
  (6): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (7): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (8): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (9): ReLU(inplace)
  (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (11): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (12): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (13): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (14): ReLU(inplace)
  (15): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (16): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (17): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (18): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (19): ReLU(inplace)
  (20): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (21): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (22): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (23): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (24): ReLU(inplace)
  (25): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (26): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (27): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (28): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (29): ReLU(inplace)
  (30): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (31): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (32): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
  (33): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (34): ReLU(inplace)
  (35): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (36): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (37): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)
  (38): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (39): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (40): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (41): ReLU(inplace)
  (42): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (43): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (44): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (45): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (46): ReLU(inplace)
  (47): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
  (48): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
), Sequential(
  (0): AdaptiveAvgPool2d(output_size=1)
  (1): AdaptiveMaxPool2d(output_size=1)
  (2): Flatten()
  (3): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (4): Dropout(p=0.25)
  (5): Linear(in_features=1024, out_features=512, bias=True)
  (6): ReLU(inplace)
  (7): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (8): Dropout(p=0.5)
  (9): Linear(in_features=512, out_features=4, bias=True)
)], add_time=True, silent=None)
In [75]:
ds, idxs = DatasetFormatter.from_toplosses(learn_cln)
In [69]:
ImageCleaner(ds, idxs, path)
HBox(children=(VBox(children=(Image(value=b'\xff\xd8\xff\xe0\x00\x10JFIF\x00\x01\x01\x01\x00d\x00d\x00\x00\xff…
Button(button_style='primary', description='Next Batch', layout=Layout(width='auto'), style=ButtonStyle())
In [87]:
path = Path('data/monkeys')
In [90]:
!ls data/monkeys/chimpanzee
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In [119]:
img = open_image(path/'gorilla'/'00000025.jpg'); img
Out[119]: