[Small case: 2] OpenCV color tracking

1. Function API

It has been mentioned in the previous articles, so I won’t introduce too much:
OpenCV Quick Start 4: TrackBar Control (Slider)
OpenCV Quick Start 5: Color Space Conversion

Two: Code demonstration

Threshold size determination:

import cv2
import numpy as np

def mcallback(x):
    pass

cv2.namedWindow("Tracking")
#绿色的HSV：可能不是很准
#l_g = np.array([35, 43, 46]) # 下限
#u_g = np.array([77,255,255]) # 上限
cv2.createTrackbar("LH", "Tracking", 0, 255, mcallback)
cv2.createTrackbar("LS", "Tracking", 0, 255, mcallback)
cv2.createTrackbar("LV", "Tracking", 147, 255, mcallback)
cv2.createTrackbar("UH", "Tracking", 100, 255, mcallback)
cv2.createTrackbar("US", "Tracking", 45, 255, mcallback)
cv2.createTrackbar("UV", "Tracking", 255, 255, mcallback)


cap = cv2.VideoCapture(0)
while True:
    ret, frame = cap.read()
    # img = cv2.imread(r"C:\Users\DMr\Pictures\text\book.jpg")
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    l_h = cv2.getTrackbarPos("LH", "Tracking")
    l_s = cv2.getTrackbarPos("LS", "Tracking")
    l_v = cv2.getTrackbarPos("LV", "Tracking")

    u_h = cv2.getTrackbarPos("UH", "Tracking")
    u_s = cv2.getTrackbarPos("US", "Tracking")
    u_v = cv2.getTrackbarPos("UV", "Tracking")

    l_g = np.array([l_h, l_s, l_v])  
    u_g = np.array([u_h, u_s, u_v])

    mask = cv2.inRange(hsv, l_g, u_g)

    res = cv2.bitwise_and(frame, frame, mask=mask)  

    cv2.imshow("img", frame)
    cv2.imshow("mask", mask)
    cv2.imshow("res", res)
    key = cv2.waitKey(10)
    if(key & 0xff == ord('q')):
        break

cv2.destroyAllWindows()

Color Tracking:

import numpy as np
import cv2

font = cv2.FONT_HERSHEY_SIMPLEX

lower_green = np.array([40, 56, 108])  # 绿色低阈值
upper_green = np.array([85, 156, 235])  # 绿色高阈值
lower_red = np.array([7, 132, 154])  # ju色低阈值
upper_red = np.array([17, 226, 245])  # ju色高阈值
lower_blue = np.array([85, 68, 71])  # 蓝色低阈值
upper_blue = np.array([141, 186, 255])  # 蓝色高阈值
lower_yellow = np.array([12, 59, 168])  # 黄色低阈值
upper_yellow = np.array([35, 141, 255])  # 黄色高阈值
lower_white = np.array([75, 0, 158])  # bai色低阈值
upper_white = np.array([118, 64, 247])  # 白色高阈值

cap = cv2.VideoCapture(0)  # 打开USB摄像头
if (cap.isOpened()):  # 视频打开成功
    flag = 1
else:
    flag = 0
num = 0
if (flag):
    while (True):
        ret, frame = cap.read()
        if ret == False:
            break

        hsv_img = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        mask_green = cv2.inRange(hsv_img, lower_green, upper_green)  # 根据颜色范围删选
        mask_red = cv2.inRange(hsv_img, lower_red, upper_red)
        mask_blue = cv2.inRange(hsv_img, lower_blue, upper_blue)
        mask_yellow = cv2.inRange(hsv_img, lower_yellow, upper_yellow)
        mask_white = cv2.inRange(hsv_img, lower_white, upper_white)

        mask_green = cv2.medianBlur(mask_green, 7)  # 中值滤波
        mask_red = cv2.medianBlur(mask_red, 7)
        mask_blue = cv2.medianBlur(mask_blue, 7)
        mask_yellow = cv2.medianBlur(mask_yellow, 7)
        mask_white = cv2.medianBlur(mask_white, 7)

        mask = cv2.bitwise_or(mask_green, mask_red, mask_blue, mask_yellow)  # 检测轮廓
        mask_green, contours, hierarchy = cv2.findContours(mask_green, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        contours = sorted(contours, key=cv2.contourArea, reverse=True)[:2] # 取面积最大的2个
        mask_red, contours2, hierarchy2 = cv2.findContours(mask_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        contours2= sorted(contours2, key=cv2.contourArea, reverse=True)[:1]
        mask_blue, contours3, hierarchy3 = cv2.findContours(mask_blue, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        contours3 = sorted(contours3, key=cv2.contourArea, reverse=True)[:2]
        mask_yellow, contours4, hierarchy4 = cv2.findContours(mask_yellow, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        #contours4 = sorted(contours4, key=cv2.contourArea, reverse=True)[:1]
        mask_white, contours5, hierarchy5 = cv2.findContours(mask_white, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        contours5 = sorted(contours5, key=cv2.contourArea, reverse=True)[:1]

        for cnt in contours:
            (x, y, w, h) = cv2.boundingRect(cnt)
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
            cv2.putText(frame, "Green", (x, y - 5), font, 0.7, (0, 255, 0), 2)

        for cnt2 in contours2:
            (x2, y2, w2, h2) = cv2.boundingRect(cnt2)
            cv2.rectangle(frame, (x2, y2), (x2 + w2, y2 + h2), (0, 115, 255), 2)
            cv2.putText(frame, "Orange", (x2, y2 - 5), font, 0.7, (0, 115, 255), 2)

        for cnt3 in contours3:
            (x3, y3, w3, h3) = cv2.boundingRect(cnt3)
            cv2.rectangle(frame, (x3, y3), (x3 + w3, y3 + h3), (255, 0, 0), 2)
            cv2.putText(frame, "Blue", (x3, y3 - 5), font, 0.7, (255, 0, 0), 2)

        for cnt4 in contours4:
            (x4, y4, w4, h4) = cv2.boundingRect(cnt4)
            cv2.rectangle(frame, (x4, y4), (x4 + w4, y4 + h4), (0, 255, 255), 2)
            cv2.putText(frame, "Yellow", (x4, y4 - 5), font, 0.7, (0, 255, 255), 2)

        for cnt5 in contours5:
            (x5, y5, w5, h5) = cv2.boundingRect(cnt5)
            cv2.rectangle(frame, (x5, y5), (x5 + w5, y5 + h5), (255, 255, 255), 2)
            cv2.putText(frame, "White", (x5, y5 - 5), font, 0.7, (255, 255, 255), 2)


        cv2.imshow("color_det", frame)

        if cv2.waitKey(20) & 0xFF == ord("q"):
            break
cv2.waitKey(0)
cv2.destroyAllWindows()

The effect is as follows

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