From: https://www.kaggle.com/chrisevans/kernelfea8793d3e
Author: ChrisEvans
# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load in
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory
import os
print(os.listdir("../input"))
# Any results you write to the current directory are saved as output.
cd train_val2019
!ls Birds/202/0046f8c09d5d6acaa78baeffb2ba5c43.jpg
from matplotlib.image import imread
import numpy as np
data = imread('Birds/202/0046f8c09d5d6acaa78baeffb2ba5c43.jpg')
data
from PIL import Image
img = Image.fromarray(data, 'RGB')
img