skimage将RGB转换为HSV时如何获得正确的颜色。理解顺化

问题描述 投票:1回答:1

我尝试使用skimage将RGB转换为HSV并获得我不期望的行为。这是一些我希望只生成蓝色的示例代码。这很重要,因为我希望拍摄真实的图像,并通过参考色调来确定整个图像中每种颜色的存在量。

import numpy as np
import skimage as ski
import matplotlib.pyplot as plt

#define my own color in RGB, should be B
tested = np.ones(shape=(100,100,3))*200
tested[:,:,0] =0
tested[:,:,1] =0

hsv_test_img_arr=ski.color.rgb2hsv(tested)

hue_img = hsv_test_img_arr[:, :, 0]
sat_img = hsv_test_img_arr[:, :, 1]
value_img = hsv_test_img_arr[:, :, 2]

fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(8, 2))

ax1.imshow(hue_img, cmap='hsv')
ax1.set_title('hue channel')
ax1.axis('off')

ax2.imshow(value_img)
ax2.set_title('value channel')
ax2.axis('off')

ax3.imshow(sat_img)
ax3.set_title('sat channel')
ax3.axis('off')


output

python image matplotlib rgb scikit-image
1个回答
2
投票

您忘记了正确地规范化数据。所有通道中的值介于0和1之间。因此,您需要将此信息提供给imshow

imshow(..., vmin=0, vmax=1)

完整代码:

import numpy as np
import skimage as ski
import matplotlib.pyplot as plt

#define my own color in RGB, should be B
tested = np.ones(shape=(100,100,3))*200
tested[:,:,0] =0
tested[:,:,1] =0

hsv_test_img_arr=ski.color.rgb2hsv(tested)

hue_img = hsv_test_img_arr[:, :, 0]
sat_img = hsv_test_img_arr[:, :, 1]
value_img = hsv_test_img_arr[:, :, 2]

fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(8, 2))

im1 = ax1.imshow(hue_img, cmap='hsv', vmin=0, vmax=1)
ax1.set_title('hue channel')
ax1.axis('off')
fig.colorbar(im1, ax=ax1)

im2 = ax2.imshow(value_img, cmap="gray", vmin=0, vmax=1)
ax2.set_title('value channel')
ax2.axis('off')
fig.colorbar(im2, ax=ax2)

im3 = ax3.imshow(sat_img, cmap="gray", vmin=0, vmax=1)
ax3.set_title('sat channel')
ax3.axis('off')
fig.colorbar(im3, ax=ax3)

plt.show()

enter image description here

拍摄真实图像会使这更有用。

import skimage as ski
import matplotlib.pyplot as plt

img = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/World%2C_administrative_divisions_-_de_-_colored_%28all_countries%29.svg/640px-World%2C_administrative_divisions_-_de_-_colored_%28all_countries%29.svg.png"
tested = plt.imread(img)[:,:,:3]

hsv_test_img_arr=ski.color.rgb2hsv(tested)

hue_img = hsv_test_img_arr[:, :, 0]
sat_img = hsv_test_img_arr[:, :, 1]
value_img = hsv_test_img_arr[:, :, 2]

fig, ((ax0, ax1), (ax2, ax3)) = plt.subplots(ncols=2, nrows=2, figsize=(8, 6))

im0 = ax0.imshow(tested)
ax0.set_title('original')
ax0.axis('off')

im1 = ax1.imshow(hue_img, cmap='hsv', vmin=0, vmax=1)
ax1.set_title('hue channel')
ax1.axis('off')
fig.colorbar(im1, ax=ax1)

im2 = ax2.imshow(value_img, cmap="gray", vmin=0, vmax=1)
ax2.set_title('value channel')
ax2.axis('off')
fig.colorbar(im2, ax=ax2)

im3 = ax3.imshow(sat_img, cmap="gray", vmin=0, vmax=1)
ax3.set_title('sat channel')
ax3.axis('off')
fig.colorbar(im3, ax=ax3)

plt.show()

enter image description here

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