在给定 y 值的轮廓上查找点

Question

我有各种由 cv2.findContours(cv2.CHAINE_APPROX_NONE) 提取的轮廓。之后我还提取了极值点。现在我想找到轮廓中与最左边/最右边相对的点。可以说，轮廓中与最左/最右点具有相同 y 坐标的点。由于大多数函数很难读取坐标的格式，因此诀窍可能是重新排序。

知道怎么解决吗？

    ###contour extraction
    cnts = cv2.findContours(img_thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    cnts = cnts[0]
    (cnts, _) = contours.sort_contours(cnts)

    cnt_number = 0

    for cnt in cnts:
        if cv2.contourArea(cnt) > 500:
        contour_lenght = cv2.arcLength(cnt, True)
        approx = cv2.approxPolyDP(cnt, 0.005 * contour_lenght, True)
        obj_cor = len(approx)

        if obj_cor > 4:
            cv2.drawContours(blank_image, cnt, -1, (0, 0, 0), 2)
            leftmost = tuple(cnt[cnt[:, :, 0].argmin()][0])
            rightmost = tuple(cnt[cnt[:, :, 0].argmax()][0])

还想进行线轮廓交点（就像 math.coffee 在这里 Line intersecting contour in openCv 建议的那样），但不确定如何...

            ###bounding box
            x, y, w, h = cv2.boundingRect(approx)
            ###end of line from leftmost
            left_y = leftmost[1]
            left_x = leftmost[0] + w
            left_line_endpoint = (left_x, left_y)
            ###line intersect function suggested by mathematical.coffee
            numpy.logical_and(...)

Answer 1

如果我正确理解了你的想法，这将是这样的（请原谅我对线性代数的糟糕掌握）

import cv2
import numpy as np

def intersection(l0, l1):   # (origin, drection), (origin, drection) -> point in scene coords
    l0 = np.float32(l0)
    l1 = np.float32(l1)

    dOrg = l1[0] -l0[0]
    g1ort = np.float32([-l1[1][1], l1[1][0]])
    g0 = np.float32([l0[1][0], l0[1][1]])

    if abs(np.dot(g0, g1ort)) < 1e-32:
        return None
    else:
        t0 = np.dot(dOrg, g1ort)/np.dot(g0, g1ort)
        return l0[0] +l0[1]*t0

img = np.zeros((450, 450, 3), dtype=np.uint8)

# badpoints = [[10,100], [180,250], [380,160], [220,360], [180,360], [70,210]]
points = [[200,100], [180,250], [380,160], [220,360], [180,360], [70,210]]
cont = [np.int32(points).reshape(len(points), 1, 2)]  # convert it into this weird format cv so wants
cv2.drawContours(img, cont, -1, (0,0xff,0), 3)

leftmost = points[np.argmin(np.array(points)[:,0])]
hor_line = [leftmost, [100, 0]]
cont_lines = np.float32(list(zip(points, points[1:]+[points[0]])))  # make segment list (scene coords)
cont_lines = [[segment[0], segment[1]-segment[0]] for segment in cont_lines]    # convert to parametric
intersections = [intersection(hor_line, line) for line in cont_lines]   # cache intersection results for each segt

for pt in intersections:
    if pt is not None:
        cv2.circle(img, tuple(np.int32(pt)), 7, (0,0,255), 3)

rightmost = None
for isect, segt in zip(intersections, cont_lines):
    if isect is not None:
        gline = segt[1]
        dOrg = isect -segt[0]
        t = np.dot(gline, dOrg)/np.dot(gline, gline)
        if 0 <= t <= 1:  # check that only those intersection points that lie in boundaries of segments are used
            if rightmost is None:
                rightmost = isect
            elif rightmost[0] < isect[0]:
                rightmost = isect

cv2.circle(img, tuple(np.int32(rightmost)), 11, (255,0,0), 3)

cv2.imshow('test', img)
cv2.waitKey(0)

考虑将points 数组替换为badpoints。这将导致最左边的点也是最上面的，因此它的右边没有匹配的线段相交