双12静态手势识别推荐

import cv2
import numpy as np

# 加载预训练的手势识别模型
model = load_gesture_model()

def preprocess_image(frame):
    # 图像预处理步骤，如灰度化、缩放、归一化等
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    resized = cv2.resize(gray, (64, 64))
    normalized = resized / 255.0
    return np.expand_dims(normalized, axis=-1)

def recognize_gesture(frame):
    processed_frame = preprocess_image(frame)
    prediction = model.predict(processed_frame)
    gesture_label = decode_prediction(prediction)  # 解码预测结果为具体手势标签
    return gesture_label

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break
    
    gesture = recognize_gesture(frame)
    
    # 在帧上绘制识别结果
    cv2.putText(frame, f"Gesture: {gesture}", (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()