Python ndimage:将现有的 ndarray 转换为灰度
Python ndimage: Converting an existing ndarray into greyscale
在我尝试使用 scipy
的 python 2.7 探索期间,我制作了以下简单脚本:
#!/usr/bin/env python
# coding=utf-8
# -*- Mode: python; c-basic-offset: 4 -*-
from scipy import ndimage
import numpy as np
from scipy import misc
import argparse
import Image
def getArguments():
parser = argparse.ArgumentParser(description="An simple Image processor")
parser.add_argument('image_file', metavar="FILENAME", type=str,
help="The image file that will be read In order to be processed")
return parser.parse_args()
def getImagePathFromArguments():
'''
:return: string
'''
args = getArguments()
return args.image_file
def loadImage(image):
'''
:param image: The path of the Image
:return:
'''
return misc.imread(image)
def grayscale(imgData):
#Greyscale action done here
pass
def blur(imgData):
'''
:param nparray imgData:
:return:
'''
return ndimage.gaussian_filter(imgData, 1)
def saveImage(path, imgData):
im = Image.fromarray(imgData)
im.save(path)
def main():
imagePath = getImagePathFromArguments()
print "Loading Image from %s" % (imagePath,)
image = loadImage(imagePath)
while True:
print "Select \n"
print "1. Greyscale"
print "2. Bluring"
option = int(raw_input("Please do your option: "))
if (option != 1 and option != 2):
print "Wrong Option"
else:
processedData=0
if option == 1:
processedData = grayscale(image)
elif option == 2:
print "Bluring Image"
processedData = blur(image)
saveImagePath = raw_input("Where to you want to store the image?")
saveImage(saveImagePath, processedData)
break
if __name__ == "__main__":
main()
对图像进行模糊和灰度等简单处理。我设法从已加载的图像中进行模糊处理,但灰度如何?
我找到的最接近的是 How can I convert an RGB image into grayscale in Python? 但是他们没有提供使用 ndimage 的解决方案。
ndimage 也可以在打开过程中进行转换,而不是使用已经打开的图像。
我还尝试实现 greyscale
方法 http://ebanshi.cc/questions/108516/convert-rgb-image-to-grayscale-in-python:
def grayscale(imgData):
r=imgData[:,:,0]
g=imgData[:,:,1]
b=imgData[:,:,2]
return r * 299. / 1000 + g * 587. / 1000 + b * 114. / 1000
但是我得到以下错误:
Traceback (most recent call last):
File "/home/pcmagas/Kwdikas/python/Basic/scripy/scipy_image_examples.py", line 83, in
main()
File "/home/pcmagas/Kwdikas/python/Basic/scripy/scipy_image_examples.py", line 78, in main
saveImage(saveImagePath, processedData)
File "/home/pcmagas/Kwdikas/python/Basic/scripy/scipy_image_examples.py", line 52, in saveImage
im.save(path)
File "/usr/lib/python2.7/dist-packages/PIL/Image.py", line 1675, in save
save_handler(self, fp, filename)
File "/usr/lib/python2.7/dist-packages/PIL/PngImagePlugin.py", line 682, in _save
raise IOError("cannot write mode %s as PNG" % mode)
IOError: cannot write mode F as PNG
有什么想法吗?
最后我需要创建自己的函数。没那么难:
def grayscale(imgData):
r=imgData[:,:,0]
g=imgData[:,:,1]
b=imgData[:,:,2]
return r/3 + g /3 + b/3
Dimitris 您的解决方案不起作用,因为您正尝试使用无效模式保存文件。 F 用于 32 位浮点像素,当您调用 saveImage
时,图像数据仍处于 F 模式。您可以通过在 saveImage
函数中添加行: print im.mode
来自行检查。
有关 PIL 库中的所有模式,请参阅 http://pillow.readthedocs.io/en/3.4.x/handbook/concepts.html#modes
要解决这个问题,您只需在保存前调用 convert('RGB')
将图像数据再次转换为 RGB 模式。
http://pillow.readthedocs.io/en/3.4.x/reference/Image.html#PIL.Image.Image.convert
在我尝试使用 scipy
的 python 2.7 探索期间,我制作了以下简单脚本:
#!/usr/bin/env python
# coding=utf-8
# -*- Mode: python; c-basic-offset: 4 -*-
from scipy import ndimage
import numpy as np
from scipy import misc
import argparse
import Image
def getArguments():
parser = argparse.ArgumentParser(description="An simple Image processor")
parser.add_argument('image_file', metavar="FILENAME", type=str,
help="The image file that will be read In order to be processed")
return parser.parse_args()
def getImagePathFromArguments():
'''
:return: string
'''
args = getArguments()
return args.image_file
def loadImage(image):
'''
:param image: The path of the Image
:return:
'''
return misc.imread(image)
def grayscale(imgData):
#Greyscale action done here
pass
def blur(imgData):
'''
:param nparray imgData:
:return:
'''
return ndimage.gaussian_filter(imgData, 1)
def saveImage(path, imgData):
im = Image.fromarray(imgData)
im.save(path)
def main():
imagePath = getImagePathFromArguments()
print "Loading Image from %s" % (imagePath,)
image = loadImage(imagePath)
while True:
print "Select \n"
print "1. Greyscale"
print "2. Bluring"
option = int(raw_input("Please do your option: "))
if (option != 1 and option != 2):
print "Wrong Option"
else:
processedData=0
if option == 1:
processedData = grayscale(image)
elif option == 2:
print "Bluring Image"
processedData = blur(image)
saveImagePath = raw_input("Where to you want to store the image?")
saveImage(saveImagePath, processedData)
break
if __name__ == "__main__":
main()
对图像进行模糊和灰度等简单处理。我设法从已加载的图像中进行模糊处理,但灰度如何?
我找到的最接近的是 How can I convert an RGB image into grayscale in Python? 但是他们没有提供使用 ndimage 的解决方案。
ndimage 也可以在打开过程中进行转换,而不是使用已经打开的图像。
我还尝试实现 greyscale
方法 http://ebanshi.cc/questions/108516/convert-rgb-image-to-grayscale-in-python:
def grayscale(imgData):
r=imgData[:,:,0]
g=imgData[:,:,1]
b=imgData[:,:,2]
return r * 299. / 1000 + g * 587. / 1000 + b * 114. / 1000
但是我得到以下错误:
Traceback (most recent call last): File "/home/pcmagas/Kwdikas/python/Basic/scripy/scipy_image_examples.py", line 83, in main() File "/home/pcmagas/Kwdikas/python/Basic/scripy/scipy_image_examples.py", line 78, in main saveImage(saveImagePath, processedData) File "/home/pcmagas/Kwdikas/python/Basic/scripy/scipy_image_examples.py", line 52, in saveImage im.save(path) File "/usr/lib/python2.7/dist-packages/PIL/Image.py", line 1675, in save save_handler(self, fp, filename) File "/usr/lib/python2.7/dist-packages/PIL/PngImagePlugin.py", line 682, in _save raise IOError("cannot write mode %s as PNG" % mode) IOError: cannot write mode F as PNG
有什么想法吗?
最后我需要创建自己的函数。没那么难:
def grayscale(imgData):
r=imgData[:,:,0]
g=imgData[:,:,1]
b=imgData[:,:,2]
return r/3 + g /3 + b/3
Dimitris 您的解决方案不起作用,因为您正尝试使用无效模式保存文件。 F 用于 32 位浮点像素,当您调用 saveImage
时,图像数据仍处于 F 模式。您可以通过在 saveImage
函数中添加行: print im.mode
来自行检查。
有关 PIL 库中的所有模式,请参阅 http://pillow.readthedocs.io/en/3.4.x/handbook/concepts.html#modes
要解决这个问题,您只需在保存前调用 convert('RGB')
将图像数据再次转换为 RGB 模式。
http://pillow.readthedocs.io/en/3.4.x/reference/Image.html#PIL.Image.Image.convert