我有一个从scipy.measure.label获得的标记矩阵。现在,我需要获得每个特征的外轮廓。我尝试了cv2.findContours,但轮廓找不到标签。我认为应该有一个简单的算法来做到这一点,但不幸的是,找不到。
答案 0 :(得分:0)
对不起,我混淆了行和列(为什么它们在opencv中的顺序相反?) 这是代码:
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import cv2
import scipy
import numpy as np
from skimage import filters, feature, io
from skimage.color import rgb2grey
def find_bounds(im):
edges1 = filters.scharr(im)
gt=filters.threshold_otsu(edges1)
edges1 = edges1>gt
return scipy.ndimage.measurements.label(edges1)
def object_filter(img, considered):
def func(t): return 255 if t==considered else 0
func=np.vectorize(func)
return func(img).astype('uint8')
im=io.imread('gesture.jpg')
im=rgb2grey(im)
labels, num_of_labels=find_bounds(im)
contours,_ = cv2.findContours(object_filter(labels, 1),2,1)
cnt = contours[0]
hull = cv2.convexHull(cnt,returnPoints = False)
contour_matrix=np.zeros(im.shape, 'uint8')
for t in cnt:
print t, labels[t[0][1]][t[0][0]]
contour_matrix[t[0][1]][t[0][0]]=1
print '====================='
print contour_matrix