本文介绍了使用scikit-image在HSV中进行颜色旋转的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

目标是将纯红色图像转换为色轮的任何色调。

The aim is to convert a pure red image into any hue of the color wheel.


  • 首先将单色图像转换为彩色图像。 RGB红色图像,例如:

  • 然后转换为HSV

  • 通过添加应该与车轮颜色匹配的
    角度值来修改色相分量

  • 然后绘制hsv图像返回转换为rgb颜色空间。

  • A monochrome image is first converted into a RGB red image, ex:
  • then converted into HSV
  • The hue component is modified by adding an angle value supposed tomatch the wheel color
  • then the hsv image is back converted into the rgb color space.

问题是只能获得绿色或蓝色图像(n ):

The problem is that only green or blue image can be obtained (no yellow for an angle~30° for example):

在某些ipython单元中执行的代码依赖于scikit- image 0.10dev:

The code performed in some ipython cells relies on scikit-image 0.10dev:

from skimage import io
from skimage import color
from scipy import ndimage as nd
import numpy as np
from matplotlib import pyplot as plt
import os
cy55 = io.imread('/home/jeanpat/MFISH/PSI/P07/01/Cy5/P070109C.tif')

zero = np.zeros(cy55.shape,dtype=np.uint8)
rgb0 = np.dstack([cy55, zero,zero])

hue_rotations = [18, 36,72,90,108]
images = {}
images[0] = rgb0
hsv0 = color.rgb2hsv(rgb0)
print hsv0[:,:,0].dtype
for hue in hue_rotations:
    hsv = np.copy(hsv0)
    hsv[:,:,0] = hsv[:,:,0]+ hue
    rgb = color.hsv2rgb(hsv)
    images[hue] = rgb
i = 1
plt.figure(num=None, figsize=(15, 5),  facecolor='w', edgecolor='k')
for hue in np.sort(images.keys()):
    plt.subplot(1,6,i,xticks=[],yticks=[])
    plt.title('hue='+str(hue))
    plt.imshow(images[hue])
    i = i +1
plt.show()


推荐答案

我在邮件列表中回答了这个问题,但是我将解决方案复制到此处,以便更轻松地查找(格式为pre

I answered this on the mailing list, but I'll copy the solution here so that it's easier to find (and the formatting is prettier).

基本上,色调的表示方式(0--1而不是0--180),uint8与float数据类型以及可能是如何将灰度图像转换为RGB的问题。用法的快速示例如下:

Basically, there are some differences in how hue is represented (0--1 instead of 0--180), uint8 vs float data-types, and maybe some issues with how the grayscale image is converted to RGB. A quick example of usage might look like:

import numpy as np
import matplotlib.pyplot as plt
from skimage import color
from skimage import data


def colorize(image, hue):
    """Return image tinted by the given hue based on a grayscale image."""
    hsv = color.rgb2hsv(color.gray2rgb(image))
    hsv[:, :, 0] = hue
    hsv[:, :, 1] = 1  # Turn up the saturation; we want the color to pop!
    return color.hsv2rgb(hsv)


image = data.camera()[::2, ::2]

hue_rotations = np.linspace(0, 1, 6)  # 0--1 is equivalent to 0--180
colorful_images = [colorize(image, hue) for hue in hue_rotations]

fig, axes = plt.subplots(nrows=2, ncols=3)

for ax, array in zip(axes.flat, colorful_images):
    ax.imshow(array, vmin=0, vmax=1)
    ax.set_axis_off()

plt.show()

给出:

这篇关于使用scikit-image在HSV中进行颜色旋转的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

09-14 00:08
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