python - 切片超像素的平均颜色

Question

我想使用切片超像素分割图像，然后用所述超像素的平均颜色替换超像素的原始颜色。

import numpy as np
import matplotlib.pyplot as plt
from skimage import io
from skimage.segmentation import slic, mark_boundaries
from skimage.data import astronaut
from skimage.measure import regionprops

img = astronaut()
segments = slic(img, n_segments=512, compactness=10,
            multichannel=True,
            enforce_connectivity=True,
            convert2lab=True)
regions = regionprops(segments, intensity_image=img)

我得到错误ValueError: Label and intensity image must have thesame shape. Segments shape is (512,512) 和 img shape in (512,512,3)。regionprops在我的情况下正确使用什么？

Answer 1

我遵循了已接受答案的第一个建议。我的代码的工作版本：

import matplotlib.pyplot as plt
from skimage.segmentation import slic
from skimage.data import astronaut
from skimage.measure import regionprops

def paint_region_with_avg_intensity(rp, mi, channel):
    for i in range(rp.shape[0]):
        img[rp[i][0]][rp[i][1]][channel] = mi

img = astronaut()
segments = slic(img, n_segments=512, compactness=10,
            multichannel=True,
            enforce_connectivity=True,
            convert2lab=True)

for i in range(3):
    regions = regionprops(segments, intensity_image=img[:,:,i])
    for r in regions:
        paint_region_with_avg_intensity(r.coords, int(r.mean_intensity), i)

plt.imshow(img)
plt.show()

Answer 2

根据文档，regionprops只能量化灰度值图像，不适用于颜色。

一个简单的解决方案是分别测量每个通道的平均强度，并结合结果：

out = np.empty_like(img)
for ii in range(3):
   regions = regionprops(segments, intensity_image=img[:,:,ii])
   # paint, and write to out[:,:,ii]

使用PyDIP这可以很简单地完成（免责声明：我是作者）：

import PyDIP as dip

segments = segments.astype('uint32')  # 64-bit types not accepted by PyDIP
msr = dip.MeasurementTool.Measure(segments, img, ['Mean'])
out = dip.ObjectToMeasurement(segments, msr['Mean'])
out.Show()