50行Python代码实现视频中物体颜色识别和跟踪（必须以红色为例）

import numpy as np
import cv2
font = cv2.FONT_HERSHEY_SIMPLEX
lower_green = np.array([35, 110, 106]) # 绿色范围低阈值
upper_green = np.array([77, 255, 255]) # 绿色范围高阈值
lower_red = np.array([0, 127, 128]) # 红色范围低阈值
upper_red = np.array([10, 255, 255]) # 红色范围高阈值
#需要更多颜色，可以去百度一下HSV阈值！
# cap = cv2.VideoCapture('1.mp4') # 打开视频文件
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() # 读取一帧
 
 if ret == False: # 读取帧失败
  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) 
 # 根据颜色范围删选
 mask_green = cv2.medianBlur(mask_green, 7) # 中值滤波
 mask_red = cv2.medianBlur(mask_red, 7) # 中值滤波
 mask = cv2.bitwise_or(mask_green, mask_red)
 mask_green, contours, hierarchy = cv2.findContours(mask_green, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
 mask_red, contours2, hierarchy2 = cv2.findContours(mask_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

 for cnt in contours:
  (x, y, w, h) = cv2.boundingRect(cnt)
  cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 255), 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, 255, 255), 2)
  cv2.putText(frame, "Red", (x2, y2 - 5), font, 0.7, (0, 0, 255), 2)
 num = num + 1
 cv2.imshow("dection", frame)
 cv2.imwrite("imgs/%d.jpg"%num, frame)
 if cv2.waitKey(20) & 0xFF == 27:
  break
cv2.waitKey(0)
cv2.destroyAllWindows()