静态手势识别如何创建

import cv2
import numpy as np

def detect_gesture(frame):
    # 转换为灰度图像
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    # 应用高斯模糊去噪
    blurred = cv2.GaussianBlur(gray, (11, 11), 0)
    # 进行边缘检测
    edges = cv2.Canny(blurred, 50, 150)
    
    # 查找轮廓
    contours, _ = cv2.findContours(edges.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    
    if len(contours) > 0:
        # 找到最大的轮廓
        max_contour = max(contours, key=cv2.contourArea)
        # 计算轮廓的凸包
        hull = cv2.convexHull(max_contour)
        # 绘制凸包
        cv2.drawContours(frame, [hull], 0, (0, 255, 0), 2)
        
        # 进一步处理以识别具体手势...
    
    return frame

# 主程序
cap = cv2.VideoCapture(0)
while True:
    ret, frame = cap.read()
    if not ret:
        break
    
    result_frame = detect_gesture(frame)
    
    cv2.imshow('Gesture Recognition', result_frame)
    
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()