双11静态手势识别推荐

import cv2
import numpy as np
from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D, Flatten, Dense

# 加载预训练模型
model = Sequential([
    Conv2D(32, (3, 3), activation='relu', input_shape=(64, 64, 3)),
    MaxPooling2D((2, 2)),
    Conv2D(64, (3, 3), activation='relu'),
    MaxPooling2D((2, 2)),
    Flatten(),
    Dense(64, activation='relu'),
    Dense(10, activation='softmax')
])
model.load_weights('gesture_recognition_model.h5')

# 手势类别标签
labels = ['none', 'swipe-left', 'swipe-right', 'swipe-up', 'swipe-down', 'pinch', 'grab']

cap = cv2.VideoCapture(0)

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

    # 预处理图像
    resized_frame = cv2.resize(frame, (64, 64))
    normalized_frame = resized_frame / 255.0
    input_frame = np.expand_dims(normalized_frame, axis=0)

    # 预测手势
    predictions = model.predict(input_frame)
    gesture_label = labels[np.argmax(predictions)]

    # 显示结果
    cv2.putText(frame, gesture_label, (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()