围绕一系列轮廓绘制边界盒

Question

我试图在一系列轮廓上放置一个界限，如以下内容。顶部轮廓和底部轮廓 image1 我写了以下基本代码，这是结果 image2

import cv2
import numpy as np

img = cv2.imread('light2.png')
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, (0, 0, 46), (179, 255, 255))

kernel = np.ones((5,5),np.uint8)
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)

contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

try: hierarchy = hierarchy[0]
except: hierarchy = []

height, width, _ = img.shape
min_x, min_y = width, height
max_x = max_y = 0

for contour, hier in zip(contours, hierarchy):
  (x, y, w, h) = cv2.boundingRect(contour)
  min_x, max_x = min(x, min_x), max(x+w, max_x)
  min_y, max_y = min(y, min_y), max(y+h, max_y)
  if w > 80 and h > 80:
      cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)

if max_x - min_x > 0 and max_y - min_y > 0:
    cv2.rectangle(img, (min_x, min_y), (max_x, max_y), (255, 0, 0), 2)

我很挣扎着逻辑当环境中还有其他轮廓时，例如 image3 。并且仍然只想在顶部和底部轮廓检测周围放一个边界盒（类似 image4 ）。但是使用当前代码，它将像这样的边界框放置 image5 。任何帮助都将受到赞赏。

Answer 1

您需要使用拥有的工具来解释计算机所需的内容。我建议使用阈值 - ＆gt; ConnectedComponents - ＆gt; 过滤错误的Bbox - ＆gt; 查找具有相同x位置和≈区域（未实现）的2个bbox - ＆gt; Union Bboxes

代码示例：

import cv2
import numpy as np


def drawStats(img: np.array, arr: np.array):
    for i in range(arr.shape[0]):
        w = arr[i, cv2.CC_STAT_WIDTH]
        h = arr[i, cv2.CC_STAT_HEIGHT]
        l = arr[i, cv2.CC_STAT_LEFT]
        t = arr[i, cv2.CC_STAT_TOP]
        cv2.rectangle(img, (l, t), (l+w,t+h), (20, 0, 255), 3)

def filterStats(arr: np.array) -> np.array:
    result = []
    for i in range(arr.shape[0]):
        w = arr[i, cv2.CC_STAT_WIDTH]
        h = arr[i, cv2.CC_STAT_HEIGHT]
        if w > h * 4:
            result.append(arr[i])
        
    result = np.array(result)
    return result

img = cv2.imread("/Users/alex/Downloads/exo7R.jpg", cv2.IMREAD_GRAYSCALE)
_, img2 = cv2.threshold(img, 230, 255, cv2.THRESH_BINARY)

comp = cv2.connectedComponentsWithStats(img2, connectivity=8)
debugImg = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
stats = filterStats(comp[2])
drawStats(debugImg, stats)

cv2.imshow("threshold", img2)
cv2.imshow("found components", debugImg)
cv2.waitKey()