如何在opencv中操作使用minAreaRect（）绘制的边界框内的像素 - python

Question

我有一个带有几个绿色条的图像。但其中一个很特别，因为它与蓝色形状相连。我想在特殊的绿色条周围使用 minAreaRect() 绘制一个边界框。

到目前为止，我能够在所有绿色条周围使用 minAreaRect() 绘制边界框。但是为了过滤绿色条并只取特殊的条，我需要确定哪个框包含蓝色像素。

为了做到这一点，我想检查每个框内的每个像素，以检查哪个包含蓝色像素。有什么方法可以识别边界框内像素的像素坐标。还是有更好的方法？

import cv2 as cv
import numpy as np

# Load the aerial image and convert to HSV colourspace
image = cv.imread("1.png")
image1 = image
hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV)

# Define lower and uppper limits of the color blue
low_blue = np.array([94, 80, 2])
high_blue = np.array([126, 255, 255])

# Mask image to only select blues
mask1 = cv.inRange(hsv, low_blue, high_blue)

# Change image to green where we found blue
image[mask1 > 0] = (0, 130, 0)


blurred_frame = cv.GaussianBlur(image, (5, 5), 0)
hsv = cv.cvtColor(blurred_frame, cv.COLOR_BGR2HSV)
low_green = np.array([25, 52, 72])
high_green = np.array([102, 255, 255])
mask = cv.inRange(hsv, low_green, high_green)
_, contours, _ = cv.findContours(mask, cv.RETR_TREE, cv.CHAIN_APPROX_NONE)
image[mask1 > 0] = (255, 0, 0)

for contour in contours:

    rect = cv.minAreaRect(contour)
    box = cv.boxPoints(rect)
    box = np.int0(box)
    Cx = rect[0][0]
    Cy = rect[0][1]

    cv.drawContours(image, [box], 0, (0, 0, 255), 2)

cv.imshow("Frame", image)
cv.waitKey(0)
cv.destroyAllWindows()

这是输入图像

https://ibb.co/h9cv4DN

这是预期的输出（用紫色表示的边界框）

https://ibb.co/8Mq6Mwt

Answer 1

此答案查看图像中的所有绿色条。它检查绿色条是否也包含蓝色。

for contour in contours:

    rect = cv.minAreaRect(contour)
    box = cv.boxPoints(rect)
    box = np.int0(box)
    Cx = rect[0][0]
    Cy = rect[0][1]

    # Make a mask of this single green line
    mask = np.zeros_like(mask1)
    cv.drawContours(mask, [contour], 0, 255, cv.FILLED)
    sigle_green_line = cv.bitwise_and(image, image, mask = mask)
    sigle_green_line = cv.cvtColor(sigle_green_line, cv.COLOR_BGR2HSV)
    # Check how much blue is in the image
    blue_mask = cv.inRange(sigle_green_line, low_blue, high_blue)
    print(sum(sum(blue_mask)))
    # If the image is not all black (all zeros) the contour contains some blue
    if sum(sum(blue_mask)) > 0: print('This contour contains some blue')