OpenCV-Python实战（16）——人脸追踪详解

import cv2
import dlib
def draw_text_info():

# 绘制文本的位置
menu_pos_1 = (10, 20)
menu_pos_2 = (10, 40)
menu_pos_3 = (10, 60)
# 菜单项
info_1 = "Use left click of the mouse to select the object to track"
info_2 = "Use '1' to start tracking, '2' to reset tracking and 'q' to exit"
# 绘制菜单信息
cv2.putText(frame, "Use '1' to re-initialize tracking", menu_pos_1, cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255))
cv2.putText(frame, info_2, menu_pos_2, cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255))
if tracking_state:
    cv2.putText(frame, "tracking", menu_pos_3, cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0))
else:
    cv2.putText(frame, "not tracking", menu_pos_3, cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255))

用于保存要跟踪的对象坐标的结构

points = []
def mouse_event_handler(event, x, y, flags, param):

# 对全局变量的引用
global points
# 添加要跟踪的对象的左上角坐标
if event == cv2.EVENT_LBUTTONDOWN:
    points = [(x, y)]
# 添加要跟踪的对象的右下角坐标：
elif event == cv2.EVENT_LBUTTONUP:
    points.append((x, y))

创建视频捕获对象

capture = cv2.VideoCapture(0)

窗口名

window_name = "Object tracking using dlib correlation filter algorithm"

创建窗口

cv2.namedWindow(window_name)

绑定鼠标事件

cv2.setMouseCallback(window_name, mouse_event_handler)

初始化跟踪器

tracker = dlib.correlation_tracker()
tracking_state = False
while True:

# 捕获视频帧
ret, frame = capture.read()
# 绘制菜单项
draw_text_info()
# 设置并绘制一个矩形，跟踪矩形框内的对象
if len(points) == 2:
    cv2.rectangle(frame, points[0], points[1], (0, 0, 255), 3)
    dlib_rectangle = dlib.rectangle(points[0][0], points[0][1], points[1][0], points[1][1])
if tracking_face is True:
    # 更新跟踪器并打印测量跟踪器的置信度
    print(tracker.update(frame))
    # 获取被跟踪对象的位置
    pos = tracker.get_position()
    # 绘制被跟踪对象的位置
    cv2.rectangle(frame, (int(pos.left()), int(pos.top())), (int(pos.right()), int(pos.bottom())), (0, 255, 0), 3)
# 捕获键盘事件
key = 0xFF & cv2.waitKey(1)
# 按下 1 键，[能源期货](https://www.gendan5.com/cf/ef.html)开始追踪
if key == ord("1"):
    if len(points) == 2:
        # Start tracking:
        tracker.start_track(frame, dlib_rectangle)
        tracking_state = True
        points = []
# 按下 2 键，停止跟踪
if key == ord("2"):
    points = []
    tracking_state = False
# 按下 q 键，返回
if key == ord('q'):
    break
# 展示结果图像
cv2.imshow(window_name, frame)

释放资源

capture.release()
cv2.destroyAllWindows()