静态手势识别怎么搭建

import cv2
import numpy as np

# 加载预训练模型（假设使用CNN模型）
model = cv2.dnn.readNetFromTensorflow('gesture_recognition_model.pb')

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # 预处理图像
    blob = cv2.dnn.blobFromImage(frame, 1.0, (224, 224), (104.0, 177.0, 123.0))
    model.setInput(blob)
    predictions = model.forward()

    # 获取预测结果
    gesture_index = np.argmax(predictions)
    gestures = ['none', 'thumbs_up', 'peace', 'stop']  # 示例手势列表
    gesture_name = gestures[gesture_index]

    # 显示结果
    cv2.putText(frame, gesture_name, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
    cv2.imshow('Gesture Recognition', frame)

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

cap.release()
cv2.destroyAllWindows()