手指数识别Python

以下是基于MediaPipe手部关键点检测实现手指数识别的Python代码：

import cv2
import mediapipe as mp

mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands

# 初始化MediaPipe Hands模型
hands = mp_hands.Hands(
    static_image_mode=False,
    max_num_hands=2,
    min_detection_confidence=0.5,
    min_tracking_confidence=0.5)

# 定义手指关键点编号
finger_tip_ids = [4, 8, 12, 16, 20]

# 打开摄像头
cap = cv2.VideoCapture(0)

while cap.isOpened():
    success, image = cap.read()
    if not success:
        print("Ignoring empty camera frame.")
        continue

    # 将图像从BGR转换为RGB
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

    # 处理图像并检测手部关键点
    results = hands.process(image)

    # 将图像从RGB转换为BGR
    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)

    # 绘制手部关键点和连接线
    if results.multi_hand_landmarks:
        for hand_landmarks in results.multi_hand_landmarks:
            mp_drawing.draw_landmarks(
                image, hand_landmarks, mp_hands.HAND_CONNECTIONS)

            # 计算五根手指的角度
            finger_angles = []
            for finger_tip_id in finger_tip_ids:
                finger_tip = hand_landmarks.landmark[finger_tip_id]
                finger_pip = hand_landmarks.landmark[finger_tip_id - 2]
                finger_mcp = hand_landmarks.landmark[finger_tip_id - 3]
                finger_angle = mp_hands.angle(
                    finger_tip, finger_pip, finger_mcp)
                finger_angles.append(finger_angle)

            # 判断手势
            if finger_angles[0] < 30 and all(angle > 160 for angle in finger_angles[1:]):
                cv2.putText(image, "Thumb up", (20, 50),
                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
            elif all(angle < 90 for angle in finger_angles):
                cv2.putText(image, "Fist", (20, 50),
                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
            elif all(angle > 130 for angle in finger_angles):
                cv2.putText(image, "Five", (20, 50),
                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
            elif finger_angles[0] > 160 and all(angle < 100 for angle in finger_angles[1:]):
                cv2.putText(image, "Thumbs down", (20, 50),
                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
            else:
                cv2.putText(image, "Other", (20, 50),
                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

    # 显示图像
    cv2.imshow('Hand Gesture Recognition', image)

    # 按下q键退出
    if cv2.waitKey(5) & 0xFF == ord('q'):
        break

# 释放资源
hands.close()
cap.release()
cv2.destroyAllWindows()

该代码使用MediaPipe库实现手部21个关键点实时检测，并根据手部关键点坐标计算五根手指的角度，通过手指角度判断手势，例程中包含数字0~9的手势。