如何在OpenCV Python中检测红色

Question

我正试图从我的网络摄像头拍摄的视频中检测红色。下面给出的代码示例取自OpenCV文档。代码如下:

import cv2
import numpy as np
cap = cv2.VideoCapture(0)
while(1):
    # Take each frame
    _, frame = cap.read()
    # Convert BGR to HSV
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    # define range of blue color in HSV
    lower_blue = np.array([110,50,50])
    upper_blue = np.array([130,255,255])
    # Threshold the HSV image to get only blue colors
    mask = cv2.inRange(hsv, lower_blue, upper_blue)
    # Bitwise-AND mask and original image
    res = cv2.bitwise_and(frame,frame, mask= mask)
    cv2.imshow('frame',frame)
    cv2.imshow('mask',mask)
    cv2.imshow('res',res)
    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break
cv2.destroyAllWindows()

lower_blue = np.array([110,50,50])具有较低范围的Blue HSV值，upper_blue = np.array([130,255,255])具有较高范围的Blue HSV值。我在网上找过红色的上限和下限，但是我找不到。这将是非常有帮助的，如果有人能告诉红色的HSV值为OpenCV (OpenCV H值范围从0 - 179)。非常感谢你的帮助(提前)。

我也试着运行以下命令来找到红色的范围，但我可能无法选择合适的值。我尝试的是(对于红色):

>>> green = np.uint8([[[0,255,0 ]]])
>>> hsv_green = cv2.cvtColor(green,cv2.COLOR_BGR2HSV)
>>> print hsv_green
[[[ 60 255 255]]]

这也是取自OpenCV文档。请告诉我或帮我找到OpenCV的红色范围

Answer 1

对红色运行相同的代码似乎有效:

>>> red = numpy.uint8([[[0,0,255]]])
>>> hsv_red = cv2.cvtColor(red,cv2.COLOR_BGR2HSV)
>>> print(hsv_red)
[[[  0 255 255]]]

然后你可以尝试不同的红色。注意，红色范围既包括略大于0的数字，也包括略小于179的数字(例如，red = numpy.uint8([[[0,31,255]]])的结果是[[[ 4 255 255]]]，而red = numpy.uint8([[[31,0,255]]])的结果是[[[176 255 255]]]。

Answer 2

下面是一个程序，通过选择6个数组参数来确定您需要的颜色。(工作在Opencv 3.2)。你选择你的图像或"颜色范围栏"输入图像，你移动光标，看看哪些数组值是你需要隔离你的颜色!色彩范围程序画面图

下面是代码:(可以很容易地适应视频输入)。image.jpg ->(图片)Color_bar.jpg ->(任何你想要显示窗口的图像，尝试任何方法)

import cv2
import numpy as np
from matplotlib import pyplot as plt
def nothing(x):
    pass
def main():
    window_name='color range parameter'
    cv2.namedWindow(window_name)
    # Create a black image, a window
    im = cv2.imread('image.jpg')
    cb = cv2.imread('color_bar.jpg')
    hsv = cv2.cvtColor(im,cv2.COLOR_BGR2HSV)
    print ('lower_color = np.array([a1,a2,a3])')
    print ('upper_color = np.array([b1,b2,b3])')

    # create trackbars for color change
    cv2.createTrackbar('a1',window_name,0,255,nothing)
    cv2.createTrackbar('a2',window_name,0,255,nothing)
    cv2.createTrackbar('a3',window_name,0,255,nothing)
    cv2.createTrackbar('b1',window_name,150,255,nothing)
    cv2.createTrackbar('b2',window_name,150,255,nothing)
    cv2.createTrackbar('b3',window_name,150,255,nothing)
    while(1):
        a1 = cv2.getTrackbarPos('a1',window_name)
        a2 = cv2.getTrackbarPos('a2',window_name)
        a3 = cv2.getTrackbarPos('a3',window_name)
        b1 = cv2.getTrackbarPos('b1',window_name)
        b2 = cv2.getTrackbarPos('b2',window_name)
        b3 = cv2.getTrackbarPos('b3',window_name)
        # hsv hue sat value
        lower_color = np.array([a1,a2,a3])
        upper_color = np.array([b1,b2,b3])
        mask = cv2.inRange(hsv, lower_color, upper_color)
        res = cv2.bitwise_and(im, im, mask = mask)
        cv2.imshow('mask',mask)
        cv2.imshow('res',res)
        cv2.imshow('im',im)
        cv2.imshow(window_name,cb)
        k = cv2.waitKey(1) & 0xFF
        if k == 27:         # wait for ESC key to exit
            break
        elif k == ord('s'): # wait for 's' key to save and exit
            cv2.imwrite('Img_screen_mask.jpg',mask)
            cv2.imwrite('Img_screen_res.jpg',res)
            break

    cv2.destroyAllWindows()

#Run Main
if __name__ == "__main__" :
    main()