python - python中的图像分割

Question

我有图像

我正在寻找 python 解决方案，根据图像中的轮廓将图像中的形状分解成更小的部分。

我研究了 OpenCV 中 Canny 和 findContours 的解决方案，但它们都不适合我。

编辑:

使用的代码:

使用 Canny 方法

import cv2 import numpy as np

img = cv2.imread('area_of_blob_maxcontrast_white.jpg') edges = cv2.Canny(img, 100, 200)
cv2.imwrite('area_of_blob_maxcontrast_white_edges.jpg',edges)

使用 findContours 方法

import numpy as np 
import argparse 
import cv2

image = cv2.imread('area_of_blob_maxcontrast_white.png')

lower = np.array([0, 0, 0]) upper = np.array([15, 15, 15]) shapeMask = cv2.inRange(image, lower, upper)

(_,cnts, _) = cv2.findContours(shapeMask.copy(), cv2.RETR_EXTERNAL,
                            cv2.CHAIN_APPROX_SIMPLE) print "I found %d black shapes" % (len(cnts)) cv2.imshow("Mask", shapeMask)

for c in cnts:
    # draw the contour and show it
    cv2.drawContours(image, [c], -1, (0, 255, 0), 2)
    cv2.imshow("Image", image)
    cv2.waitKey(0)

Answer 1

诀窍是让你模糊的单个像素边界稍微粗一点。我通过将具有两个相邻黑色像素(上方、下方、左侧或右侧)的任何白色像素更改为黑色来实现。 (不过我做起来非常慢。我很确定一定有一种更聪明的方法可以用 OpenCV 或 Numpy 来做。)

这是我的代码:

#!/usr/bin/env python 

import numpy as np
import cv2

THRESH = 240

orig = cv2.imread("map.png")
img = cv2.cvtColor(orig, cv2.COLOR_BGR2GRAY)

# Make the faint 1-pixel boundary bolder
rows, cols = img.shape
new_img = np.full_like(img, 255)    # pure white image
for y in range(rows):
    if not (y % 10):
        print ('Row = %d (%.2f%%)' % (y, 100.*y/rows))
    for x in range(cols):
        score  = 1 if y > 0 and img.item(y-1, x) < THRESH else 0
        score += 1 if x > 0 and img.item(y, x-1) < THRESH else 0
        score += 1 if y < rows-1 and img.item(y+1, x) < THRESH else 0
        score += 1 if x < cols-1 and img.item(y, x+1) < THRESH else 0
        if img.item(y, x) < THRESH or score >= 2:
            new_img[y, x] = 0       # black pixels show boundary

cv2.imwrite('thresh.png', new_img)

# Find all contours on the map
_th, contours, hierarchy = cv2.findContours(new_img,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
print "Number of contours detected = %d" % len(contours)

# Fill second level regions on the map
coln = 0
colors = [
    [127, 0, 255],
    [255, 0, 127],
    [255, 127, 0],
    [127, 255, 0],
    [0, 127, 255],
    [0, 255, 127],
]
hierarchy = hierarchy[0]
for i in range(len(contours)):
    area = cv2.contourArea(contours[i])
    if hierarchy[i][3] == 1:
        print (i, area)
        coln = (coln + 1) % len(colors)
        cv2.drawContours(orig, contours, i, colors[coln], -1)

cv2.imwrite("colored_map.png", orig)

输入图片:

输出图像:

这里我只为最外层轮廓的直接后代着色 (hierarchy[i][3] == 1)。但您可以更改它以排除湖泊。