【行空板扩展版】基于OpenCV人脸识别的“人脸跟随”系统 简单

import cv2
from pinpong.board import Board, Pin, Servo
import time

# 初始化级联分类器
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# 舵机初始位置
servo_x_pos = 45  # 横向舵机初始角度
servo_y_pos = 60  # 竖向舵机初始角度

Board().begin()
servo_x = Servo(Pin(Pin.P2))
servo_y = Servo(Pin(Pin.P0))

def send_servo_command(x_pos, y_pos):
    servo_x.write_angle(x_pos)
    servo_y.write_angle(y_pos)

send_servo_command(servo_x_pos, servo_y_pos)

# 打开摄像头
cap = cv2.VideoCapture(0)

screen_width, screen_height = 280, 320
cap.set(cv2.CAP_PROP_FRAME_WIDTH, screen_width)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, screen_height)

# 创建一个命名窗口并设置为无边框
cv2.namedWindow('Face Tracking', cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty('Face Tracking', cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)

if not cap.isOpened():
    print('无法打开摄像头')
    exit()

while True:
    ret, frame = cap.read()
    if not ret:
        print("无法读取帧")
        break

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.1, 4)

    frame_height, frame_width = frame.shape[:2]
    frame_center_x = frame_width // 2
    frame_center_y = frame_height // 2

    for (x, y, w, h) in faces:
        face_center_x = x + w // 2
        face_center_y = y + h // 2

        # 绘制矩形框
        cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)

        # 计算偏移量
        offset_x = face_center_x - frame_center_x
        offset_y = face_center_y - frame_center_y

        # 调整舵机角度（使舵机反向移动）
        if abs(offset_x) > frame_width // 10:  # 误差范围
            if offset_x > 0:
                servo_x_pos -= 1  # 减小角度向左转
            else:
                servo_x_pos += 1  # 增加角度向右转

        if abs(offset_y) > frame_height // 10:  # 误差范围
            if offset_y > 0:
                servo_y_pos += 1  # 增加角度向下转
            else:
                servo_y_pos -= 1  # 减小角度向上转

        # 限制舵机范围防止损坏
        servo_x_pos = max(0, min(180, servo_x_pos))
        servo_y_pos = max(0, min(180, servo_y_pos))

        send_servo_command(servo_x_pos, servo_y_pos)
        break

    cv2.imshow('Face Tracking', frame)

    # 按下 'q' 键退出
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

    #time.sleep(0.05)

# 清理资源
cap.release()
cv2.destroyAllWindows()