skimage 如何在将 RGB 转换为 HSV 时获得正确的颜色。了解色相

Question

我尝试使用 skimage 将 RGB 转换为 HSV 并得到了我不期望的行为。这是一些我希望只产生蓝色的示例代码。这很重要，因为（稍后）我想拍摄真实图像并通过参考色调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')

Answer 1

您忘记正确规范化数据。所有通道中的值都在 0 到 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()

虽然拍摄真实图像会更有用。

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()

skimage 如何在将 RGB 转换为 HSV 时获得正确的颜色。了解色相

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