diff --git a/gesture_recognition.py b/gesture_recognition.py
new file mode 100644
index 00000000..d3d3e862
--- /dev/null
+++ b/gesture_recognition.py
@@ -0,0 +1,141 @@
+import warnings
+import threading  #导入多线程模块
+import cv2
+import mediapipe as mp
+import numpy as np
+from tensorflow.keras.models import load_model
+
+# 禁用特定警告
+warnings.filterwarnings("ignore", category=UserWarning, message='SymbolDatabase.GetPrototype() is deprecated')
+
+# 初始化 MediaPipe 和 OpenCV
+hands = None
+mp_draw = mp.solutions.drawing_utils
+cap = None
+keep_running = False
+
+# 加载手势识别模型
+model_path = 'D:/hand/hand_gesture_model.h5'
+model = load_model(model_path)
+
+# 定义手势类别
+gesture_classes = ['00', '01', '02', '03', '04', '05', '06', '07', '08', '09']
+
+def start_recognition(callback=None):
+    global keep_running, cap, hands
+    if cap is None or not cap.isOpened():
+        cap = cv2.VideoCapture(0)
+    if hands is None:
+        hands = mp.solutions.hands.Hands(static_image_mode=False, max_num_hands=2,
+                                         model_complexity=1, min_detection_confidence=0.5,
+                                         min_tracking_confidence=0.5)
+    keep_running = True
+    threading.Thread(target=run_recognition, args=(callback,)).start()
+
+def run_recognition(callback=None):
+    global keep_running
+    last_gesture = None
+
+    while keep_running and cap.isOpened():
+        ret, img = cap.read()
+        if not ret:
+            break
+
+        img = cv2.flip(img, 1)
+        img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        results = hands.process(img_rgb)
+
+        total_raised_fingers = 0
+
+        if results.multi_hand_landmarks:
+            for handLms in results.multi_hand_landmarks:
+                mp_draw.draw_landmarks(img, handLms, mp.solutions.hands.HAND_CONNECTIONS)
+                _, raised_fingers = detect_gesture_and_fingers(handLms)
+                total_raised_fingers += raised_fingers
+
+        cv2.putText(img, f'Total Raised Fingers: {total_raised_fingers}', (10, 30),
+                    cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 0), 2, cv2.LINE_AA,)
+
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        if callback:
+            callback(img)
+
+    stop_recognition()
+#停止识别
+def stop_recognition():
+    global keep_running, cap
+    keep_running = False
+    if cap is not None and cap.isOpened():
+        cap.release()
+        cap = None
+    cv2.destroyAllWindows()
+
+
+
+#释放摄像头资源
+def release_camera():
+    global cap
+    if cap is not None and cap.isOpened():
+        cap.release()
+        cap = None
+
+def detect_gesture_and_fingers(hand_landmarks):
+    # 手势识别
+    gesture_image = get_hand_image(hand_landmarks)
+    gesture = predict_gesture(gesture_image)
+
+    # 手指竖起数量检测
+    raised_fingers = count_raised_fingers(hand_landmarks)
+
+    return gesture, raised_fingers
+
+def get_hand_image(hand_landmarks):
+    # 提取手部区域图像
+    # 示例实现，请根据你的需要进行调整
+    img = np.zeros((150, 150, 3), dtype=np.uint8)  # 示例图像
+    return img
+
+def predict_gesture(img):
+    img = cv2.resize(img, (150, 150))
+    img_array = np.expand_dims(img, axis=0) / 255.0
+    predictions = model.predict(img_array)
+    predicted_class = gesture_classes[np.argmax(predictions)]
+    return predicted_class
+
+def count_raised_fingers(hand_landmarks):
+    fingers_status = [0, 0, 0, 0, 0]
+
+    # 拇指
+    thumb_tip = hand_landmarks.landmark[mp.solutions.hands.HandLandmark.THUMB_TIP]
+    thumb_ip = hand_landmarks.landmark[mp.solutions.hands.HandLandmark.THUMB_IP]
+    thumb_mcp = hand_landmarks.landmark[mp.solutions.hands.HandLandmark.THUMB_MCP]
+    thumb_cmc = hand_landmarks.landmark[mp.solutions.hands.HandLandmark.THUMB_CMC]
+
+    # 计算拇指的角度
+    angle_thumb = calculate_angle(thumb_cmc, thumb_mcp, thumb_tip)
+    if angle_thumb > 160:  # 如果拇指的角度大于160度，认为拇指竖起
+        fingers_status[0] = 1
+
+    # 其他手指
+    for i, finger_tip_id in enumerate([mp.solutions.hands.HandLandmark.INDEX_FINGER_TIP,
+                                       mp.solutions.hands.HandLandmark.MIDDLE_FINGER_TIP,
+                                       mp.solutions.hands.HandLandmark.RING_FINGER_TIP,
+                                       mp.solutions.hands.HandLandmark.PINKY_TIP]):
+        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]
+
+        # 计算手指的角度
+        angle_finger = calculate_angle(finger_mcp, finger_pip, finger_tip)
+        if angle_finger > 160:  # 如果手指的角度大于160度，认为手指竖起
+            fingers_status[i + 1] = 1
+
+    return sum(fingers_status)
+
+def calculate_angle(point1, point2, point3):
+    # 计算三个点之间的角度
+    angle = np.arctan2(point3.y - point2.y, point3.x - point2.x) - np.arctan2(point1.y - point2.y, point1.x - point2.x)
+    angle = np.abs(angle)
+    if angle > np.pi:
+        angle = 2 * np.pi - angle
+    return angle * 180 / np.pi