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python - 使用 skimage 从分割图像中查找和调​​整像素数据

问题描述

import matplotlib.pyplot as plt
import matplotlib.patches as mpatches

from skimage import data
from skimage.filters import threshold_otsu
from skimage.segmentation import clear_border
from skimage.measure import label, regionprops
from skimage.morphology import closing, square
from skimage.color import label2rgb


image = data.coins()[50:-50, 50:-50]

# apply threshold
thresh = threshold_otsu(image)
bw = closing(image > thresh, square(3))

# remove artifacts connected to image border
cleared = clear_border(bw)

# label image regions
label_image = label(cleared)
# to make the background transparent, pass the value of `bg_label`,
# and leave `bg_color` as `None` and `kind` as `overlay`
image_label_overlay = label2rgb(label_image, image=image, bg_label=0)

fig, ax = plt.subplots(figsize=(10, 6))
ax.imshow(image_label_overlay)

for region in regionprops(label_image):
    # take regions with large enough areas
    if region.area >= 100:
        # draw rectangle around segmented coins
        minr, minc, maxr, maxc = region.bbox
        rect = mpatches.Rectangle((minc, minr), maxc - minc, maxr - minr,
                                  fill=False, edgecolor='red', linewidth=2)
        ax.add_patch(rect)

ax.set_axis_off()
plt.tight_layout()
plt.show()

大家好，

我正在尝试使用此代码对像素数据进行分段、调整大小并将其加载到数组中。我想我应该使用 region.image 虽然我不确定如何调整它的大小（所有单独的图像都具有相同的大小）并将所有单独的图像加载到一个数组中。我正在尝试获取与 MNIST 数据中的数据相同的数据。

提前感谢您的帮助。

标签： pythonscikit-learnscikit-imagemnist

解决方案

你可以使用resize方法skimage来调整你的段

from skimage.transform import resize

# initialize segments list
segments = []
for region in regionprops(label_image):
    # take regions with large enough areas
    if region.area >= 100:
        # draw rectangle around segmented coins
        minr, minc, maxr, maxc = region.bbox
        # crop the segment
        segment = image_label_overlay[minr:maxr,minc:maxc,:]
        # resize to 28x28 (MNIST is 28x28)
        segment = resize(segment, (28, 28))
        segments.append(segment)
# convert to numpy array
segments = np.array(segments)

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