变形 RGB 黑色 OR 白色的

缩放到黑色和白色

转换为灰色的阴影，然后缩放到白色或黑色 /取决于更近的事实/.

原版的：


结果：


枕头销售

安装

pillow

, 如果你还没有这样做：

$ pip install pillow

https://github.com/python-imaging/Pillow
/或者 PIL/ 可以帮助您有效地工作图像。

from PIL import Image



col = Image.open/"cat-tied-icon.png"/

gray = col.convert/'L'/

bw = gray.point/lambda x: 0 if x<128 else 255, '1'/

bw.save/"result_bw.png"/

另外，你可以使用
https://github.com/python-imaging/Pillow
从
http://www.numpy.org/
.

枕头 + Numpy 位面具方法

您需要安装 numpy:

$ pip install numpy

Numpy 需要一个阵列的副本工作，但结果是相同的。

from PIL import Image

import numpy as np



col = Image.open/"cat-tied-icon.png"/

gray = col.convert/'L'/



# Let numpy do the heavy lifting for converting pixels to pure black or white

bw = np.asarray/gray/.copy//



# Pixel range is 0...255, 256/2 = 128

bw[bw < 128] = 0 # Black

bw[bw >= 128] = 255 # White



# Now we put it back in Pillow/PIL land

imfile = Image.fromarray/bw/

imfile.save/"result_bw.png"/

黑色和白色使用枕头，有振荡

使用
https://github.com/python-imaging/Pillow
, 您可以将其直接转换为黑色和白色。 看起来它似乎有灰色的色调，但你的大脑正在欺骗你！ /彼此相邻的黑白看起来像灰色/

from PIL import Image 

image_file = Image.open/"cat-tied-icon.png"/ # open colour image

image_file = image_file.convert/'1'/ # convert image to black and white

image_file.save/'/tmp/result.png'/

原版的：


转换：


黑色和白色与枕头，毫不犹豫

from PIL import Image 

image_file = Image.open/"cat-tied-icon.png"/ # open color image

image_file = image_file.convert/'1', dither=Image.NONE/ # convert image to black and white

image_file.save/'/tmp/result.png'/

我建议将其转换为灰色的阴影，然后只需将阈值应用于它。 /一半，中等或 meadian, 如果你想要这样/.

from PIL import Image



col = Image.open/'myimage.jpg'/

gry = col.convert/'L'/

grarray = np.asarray/gry/

bw = /grarray > grarray.mean///*255

imshow/bw/

img_rgb = cv2.imread/'image.jpg'/

img_gray = cv2.cvtColor/img_rgb, cv2.COLOR_BGR2GRAY/

/threshi, img_bw/ = cv2.threshold/img_gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU/

枕头，有振荡

使用
https://github.com/python-imaging/Pillow
, 您可以将其直接转换为黑色和白色。 看起来它似乎有灰色的色调，但你的大脑正在欺骗你！ /彼此相邻的黑白看起来像灰色/

from PIL import Image 

image_file = Image.open/"cat-tied-icon.png"/ # open colour image

image_file = image_file.convert/'1'/ # convert image to black and white

image_file.save/'/tmp/result.png'/

原版的：


转换：

你可以使用

colorsys

/在标准库中/ 转换 rgb 在
http://en.wikipedia.org/wiki/HSL_and_HSV
并使用亮度值来确定 black/white:

import colorsys

# convert rgb values from 0-255 to %

r = 120/255.0

g = 29/255.0

b = 200/255.0

h, l, s = colorsys.rgb_to_hls/r, g, b/

if l >= .5:

 # color is lighter

 result_rgb = /255, 255, 255/

elif l < .5:

 # color is darker

 result_rgb = /0,0,0/

使用 opencv, 你可以轻松转换 rgb 在二进制图像中

import cv2

%matplotlib inline 

import matplotlib.pyplot as plt

from skimage import io

from PIL import Image

import numpy as np



img = io.imread/'http://www.bogotobogo.com/Matlab/images/MATLAB_DEMO_IMAGES/football.jpg'/

img = cv2.cvtColor/img, cv2.IMREAD_COLOR/

imR=img[:,:,0] #only taking gray channel

print/img.shape/

plt.imshow/imR, cmap=plt.get_cmap/'gray'//



#Gray Image

plt.imshow/imR/

plt.title/'my picture'/

plt.show//



#Histogram Analyze



imgg=imR

hist = cv2.calcHist/[imgg],[0],None,[256],[0,256]/

plt.hist/imgg.ravel//,256,[0,256]/



# show the plotting graph of an image



plt.show//



#Black And White

height,width=imgg.shape

for i in range/0,height/:

 for j in range/0,width/:

 if/imgg[i][j]>60/:

 imgg[i][j]=255

 else:

 imgg[i][j]=0



plt.imshow/imgg/

以下是用于创建二进制图像的代码 opencv-python :

img = cv2.imread/'in.jpg',2/



ret, bw_img = cv2.threshold/img,127,255,cv2.THRESH_BINARY/



cv2.imshow/"Output - Binary Image",bw_img/

如果您不想使用方法 cv 对于细分并理解您在做什么，请考虑图像 RGB 作为矩阵。

image = mpimg.imread/'image_example.png'/ # your image

R,G,B = image[:,:,0], image[:,:,1], image[:,:,2] # the 3 RGB channels

thresh = [100, 200, 50] # example of triple threshold



# First, create an array of 0's as default value

binary_output = np.zeros_like/R/

# then screen all pixels and change the array based on RGB threshold.

binary_output[/R < thresh[0]/ & /G > thresh[1]/ & /B < thresh[2]/] = 255

结果，获得了数组 0 和 255, 基于三重条件。