m20_core_web/cam_web.py

import cv2
import numpy as np
from flask import Flask, render_template, request, jsonify, send_file
from flask_socketio import SocketIO, emit
import io
import base64
import time
import threading
import logging
import os
import json
import sqlite3
from datetime import datetime
import zipfile
import tempfile

# # 导入视觉处理相关的模块
# from llm_req import VisionAPIClient, DetectionResult

from cap_trigger import ImageClient



# --- 配置 ---
SAVE_PATH_LEFT = "./static/received/left"
SAVE_PATH_RIGHT = "./static/received/right"
SAVE_PATH_LEFT_MARKED = "./static/received/left_marked"  # 标注图片保存路径
SAVE_PATH_RIGHT_MARKED = "./static/received/right_marked"  # 标注图片保存路径
FLASK_HOST = "0.0.0.0"
FLASK_PORT = 5000
MAX_LIVE_FRAMES = 2 # 保留最新的几帧用于实时显示
DATABASE_PATH = "received_images.db" # SQLite 数据库文件路径
# --- 配置 ---

# 设置日志
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# --- 数据库初始化 ---
def init_db():
    """初始化 SQLite 数据库和表"""
    conn = sqlite3.connect(DATABASE_PATH)
    cursor = conn.cursor()
    # 创建表，存储图片信息，添加标注图片字段
    # --- Updated CREATE TABLE statement ---
    cursor.execute('''
        CREATE TABLE IF NOT EXISTS images (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            left_filename TEXT NOT NULL,
            right_filename TEXT NOT NULL,
            left_marked_filename TEXT,
            right_marked_filename TEXT,
            timestamp REAL NOT NULL,
            metadata TEXT,
            comment TEXT,
            created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
            manual_detections_left TEXT,
            manual_detections_right TEXT,
            is_manual_labeled_left INTEGER DEFAULT 0,
            is_manual_labeled_right INTEGER DEFAULT 0,
            left_position INTEGER DEFAULT 0, -- Added column
            right_position INTEGER DEFAULT 0 -- Added column
        )
    ''')
    # --- End Update ---
    conn.commit()
    conn.close()
    logger.info(f"Database {DATABASE_PATH} initialized.")

# --- 全局变量 ---
# 用于存储最新的左右帧，用于实时显示
latest_left_frame = None
latest_right_frame = None
latest_timestamp = None
frame_lock = threading.Lock() # 保护全局帧变量

# --- Flask & SocketIO 应用 ---
app = Flask(__name__)
# 为生产环境配置 SECRET_KEY
app.config['SECRET_KEY'] = 'your-secret-key-change-this'
# 配置异步模式，如果需要异步处理可以调整
socketio = SocketIO(app, cors_allowed_origins="*") # 允许所有来源，生产环境请具体配置

# 初始化图像客户端
image_client = ImageClient("tcp://175.24.228.220:7701", client_id="local")

# 初始化数据库
init_db()

def draw_detections_on_image(image: np.ndarray, detections: list, left_position: int = None, right_position: int = None) -> np.ndarray:
    """在图像上绘制检测框和位置信息"""
    # 复制原图以避免修改原始图像
    marked_image = image.copy()
    
    # 定义颜色映射
    color_map = {
        1: (0, 255, 0),    # 绿色 - 弹药箱
        2: (255, 0, 0),    # 蓝色 - 士兵
        3: (0, 0, 255),    # 红色 - 枪支
        4: (255, 255, 0)   # 青色 - 数字牌
    }
    
    # 获取图像尺寸
    h, w = image.shape[:2]
    
    if left_position is not None:
        position_text = f"POS/CAM_L: {left_position if left_position != 0 else 'NAN'}"
    elif right_position is not None:
        position_text = f"POS/CAM_R: {right_position if right_position != 0 else 'NAN'}"
    else:
        position_text = ""
    
    if position_text:
        # 设置字体参数
        font = cv2.FONT_HERSHEY_SIMPLEX
        font_scale = 1.0
        font_thickness = 2
        text_size = cv2.getTextSize(position_text, font, font_scale, font_thickness)[0]
        
        # 计算文本背景位置
        text_x = 10
        text_y = 30
        
        # 绘制白色背景矩形
        cv2.rectangle(marked_image, 
                     (text_x - 5, text_y - text_size[1] - 5), 
                     (text_x + text_size[0] + 5, text_y + 5), 
                     (255, 255, 255), -1)
        
        # 绘制黑色文字
        cv2.putText(marked_image, position_text, (text_x, text_y), 
                   font, font_scale, (0, 0, 0), font_thickness)
    
    # 绘制每个检测框
    for detection in detections:
        # 获取检测信息
        obj_id = detection.get("id", 0)
        label = detection.get("label", "")
        bbox = detection.get("bbox", [])
        
        if len(bbox) == 4:
            # 将归一化的坐标转换为实际像素坐标
            x_min = int(bbox[0] * w / 999)
            y_min = int(bbox[1] * h / 999)
            x_max = int(bbox[2] * w / 999)
            y_max = int(bbox[3] * h / 999)
            
            # 获取颜色
            color = color_map.get(obj_id, (255, 255, 255))  # 默认白色
            
            # 绘制边界框
            cv2.rectangle(marked_image, (x_min, y_min), (x_max, y_max), color, 2)
            
            # 添加标签
            label_text = f"{label} ({obj_id})"
            cv2.putText(marked_image, label_text, (x_min, y_min + 10), 
                       cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
    
    return marked_image

# --- Flask 路由 ---

@app.route('/')
def index():
    """主页，加载实时图像页面"""
    return render_template('index.html')

@app.route('/list') # 新增路由用于显示图片列表
def list_images():
    """加载图片列表页面"""
    return render_template('list_images.html')

@app.route('/api/images', methods=['GET'])
def get_images_api():
    """API: 获取图片列表 (JSON 格式)"""
    conn = sqlite3.connect(DATABASE_PATH)
    cursor = conn.cursor()
    # 按时间倒序排列，包含标注图片字段和人工标注字段
    # --- Updated query to directly select the new columns ---
    # No more try/except needed for these specific columns if init_db creates them
    cursor.execute("""
        SELECT id, left_filename, right_filename, left_marked_filename, right_marked_filename, 
               timestamp, metadata, comment, created_at, manual_detections_left, manual_detections_right,
               is_manual_labeled_left, is_manual_labeled_right,
               left_position, right_position
        FROM images 
        ORDER BY timestamp DESC
    """)
    # --- End Update ---
    
    rows = cursor.fetchall()
    conn.close()
    # print(rows)

    images = []
    for row in rows:
        # Note: Adjusting indices based on the new SELECT order
        images.append({
            "id": row[0],
            "left_filename": row[1],
            "right_filename": row[2],
            "left_marked_filename": row[3] or "",
            "right_marked_filename": row[4] or "",
            "timestamp": row[5],
            "metadata": row[6],
            "comment": row[7] or "",
            "created_at": row[8],
            "manual_detections_left": row[9] or "[]", # Renamed for clarity
            "manual_detections_right": row[10] or "[]", # Renamed for clarity
            "is_manual_labeled_left": bool(row[11]) if row[11] is not None else False, # Renamed for clarity
            "is_manual_labeled_right": bool(row[12]) if row[12] is not None else False, # Renamed for clarity
            "left_position": row[13], # Updated index
            "right_position": row[14] # Updated index
        })

    # print(images)

    return jsonify(images)

@app.route('/api/images', methods=['DELETE'])
def delete_image_api():
    """API: 删除单张图片记录及其文件"""
    image_id = request.json.get('id')
    if not image_id:
        return jsonify({"error": "Image ID is required"}), 400

    conn = sqlite3.connect(DATABASE_PATH)
    cursor = conn.cursor()
    # 查询文件名，包含标注图片
    cursor.execute("SELECT left_filename, right_filename, left_marked_filename, right_marked_filename FROM images WHERE id = ?", (image_id,))
    row = cursor.fetchone()
    if not row:
        conn.close()
        return jsonify({"error": "Image not found"}), 404

    left_filename, right_filename, left_marked_filename, right_marked_filename = row
    # 删除数据库记录
    cursor.execute("DELETE FROM images WHERE id = ?", (image_id,))
    conn.commit()
    conn.close()

    # 删除对应的文件，包括标注图片
    left_path = os.path.join(SAVE_PATH_LEFT, left_filename)
    right_path = os.path.join(SAVE_PATH_RIGHT, right_filename)
    left_marked_path = os.path.join(SAVE_PATH_LEFT_MARKED, left_marked_filename) if left_marked_filename else None
    right_marked_path = os.path.join(SAVE_PATH_RIGHT_MARKED, right_marked_filename) if right_marked_filename else None
    
    try:
        if os.path.exists(left_path):
            os.remove(left_path)
            logger.info(f"Deleted file: {left_path}")
        if os.path.exists(right_path):
            os.remove(right_path)
            logger.info(f"Deleted file: {right_path}")
        if left_marked_path and os.path.exists(left_marked_path):
            os.remove(left_marked_path)
            logger.info(f"Deleted file: {left_marked_path}")
        if right_marked_path and os.path.exists(right_marked_path):
            os.remove(right_marked_path)
            logger.info(f"Deleted file: {right_marked_path}")
    except OSError as e:
        logger.error(f"Error deleting files: {e}")
        # 即使删除文件失败，数据库记录也已删除，返回成功
        pass

    return jsonify({"message": f"Image {image_id} deleted successfully"})

@app.route('/api/images/export', methods=['POST'])
def export_images_api():
    """API: 打包导出选中的图片，优先导出标注图片"""
    selected_ids = request.json.get('ids', [])
    if not selected_ids:
        return jsonify({"error": "No image IDs selected"}), 400

    conn = sqlite3.connect(DATABASE_PATH)
    cursor = conn.cursor()
    placeholders = ','.join('?' * len(selected_ids))
    # 查询包含标注图片的文件名
    cursor.execute(f"SELECT left_filename, right_filename, left_marked_filename, right_marked_filename FROM images WHERE id IN ({placeholders})", selected_ids)
    rows = cursor.fetchall()
    conn.close()

    if not rows:
        return jsonify({"error": "No matching images found"}), 404

    # 创建临时 ZIP 文件
    temp_zip_fd, temp_zip_path = tempfile.mkstemp(suffix='.zip')
    os.close(temp_zip_fd) # 关闭文件描述符，让 zipfile 模块管理

    try:
        with zipfile.ZipFile(temp_zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
            for left_fn, right_fn, left_marked_fn, right_marked_fn in rows:
                # 优先使用标注图片，如果没有则使用原图
                left_export_fn = left_marked_fn if left_marked_fn else left_fn
                right_export_fn = right_marked_fn if right_marked_fn else right_fn
                
                # 确定文件路径
                left_export_path = os.path.join(SAVE_PATH_LEFT_MARKED if left_marked_fn else SAVE_PATH_LEFT, left_export_fn)
                right_export_path = os.path.join(SAVE_PATH_RIGHT_MARKED if right_marked_fn else SAVE_PATH_RIGHT, right_export_fn)
                
                # 添加到 ZIP 文件
                if os.path.exists(left_export_path):
                    zipf.write(left_export_path, os.path.join('left', left_export_fn))
                if os.path.exists(right_export_path):
                    zipf.write(right_export_path, os.path.join('right', right_export_fn))

        logger.info(f"Exported {len(rows)} image pairs to {temp_zip_path}")
        # 返回 ZIP 文件给客户端
        return send_file(temp_zip_path, as_attachment=True, download_name='exported_images.zip')

    except Exception as e:
        logger.error(f"Error creating export ZIP: {e}")
        if os.path.exists(temp_zip_path):
            os.remove(temp_zip_path)
        return jsonify({"error": str(e)}), 500


@app.route('/upload', methods=['POST'])
def upload_images():
    """接收左右摄像头图片，保存并推送更新，同时生成标注图片"""
    try:
        # 从 multipart/form-data 中获取文件
        left_file = request.files.get('left_image')
        right_file = request.files.get('right_image')
        metadata_str = request.form.get('metadata') # 如果需要处理元数据
        comment = request.form.get('comment', '')  # 获取 comment 字段

        if not left_file or not right_file:
            logger.warning("Received request without required image files.")
            return jsonify({"error": "Missing left_image or right_image"}), 400

        # 读取图片数据
        left_img_bytes = left_file.read()
        right_img_bytes = right_file.read()

        # 解码图片用于后续处理 (如显示、保存)
        nparr_left = np.frombuffer(left_img_bytes, np.uint8)
        nparr_right = np.frombuffer(right_img_bytes, np.uint8)
        img_left = cv2.imdecode(nparr_left, cv2.IMREAD_COLOR)
        img_right = cv2.imdecode(nparr_right, cv2.IMREAD_COLOR)

        if img_left is None or img_right is None:
            logger.error("Failed to decode received images.")
            return jsonify({"error": "Could not decode images"}), 400

        # 解析元数据 (如果提供)
        metadata = {}
        if metadata_str:
            try:
                metadata = json.loads(metadata_str)
            except json.JSONDecodeError as e:
                logger.warning(f"Could not parse metadata: {e}")

        timestamp_str = str(metadata.get("timestamp", str(int(time.time()))))
        timestamp_str_safe = timestamp_str.replace(".", "_") # 避免文件名中的点号问题

        # 生成文件名
        left_filename = f"left_{timestamp_str_safe}.jpg"
        right_filename = f"right_{timestamp_str_safe}.jpg"
        left_marked_filename = f"left_marked_{timestamp_str_safe}.jpg"  # 标注图片文件名
        right_marked_filename = f"right_marked_{timestamp_str_safe}.jpg"  # 标注图片文件名

        # 保存原图到本地
        left_path = os.path.join(SAVE_PATH_LEFT, left_filename)
        right_path = os.path.join(SAVE_PATH_RIGHT, right_filename)

        # 确保目录存在
        os.makedirs(SAVE_PATH_LEFT, exist_ok=True)
        os.makedirs(SAVE_PATH_RIGHT, exist_ok=True)
        os.makedirs(SAVE_PATH_LEFT_MARKED, exist_ok=True)  # 创建标注图片目录
        os.makedirs(SAVE_PATH_RIGHT_MARKED, exist_ok=True)  # 创建标注图片目录

        cv2.imwrite(left_path, img_left)
        cv2.imwrite(right_path, img_right)
        logger.info(f"Saved original images: {left_path}, {right_path}")

        # 使用 VisionAPIClient 处理图片并生成标注图片
        left_marked_path = None
        right_marked_path = None
        
        try:
            # with VisionAPIClient() as client:
            #     # 处理左图
            #     left_task_id = client.submit_task(image_id=1, image=img_left)
            #     # 处理右图
            #     right_task_id = client.submit_task(image_id=2, image=img_right)
                
            #     # 等待任务完成
            #     client.task_queue.join()
                
            #     # 获取处理结果
            #     left_result = client.get_result(left_task_id)
            #     right_result = client.get_result(right_task_id)
                
            #     # 生成标注图片
            #     if left_result and left_result.success:
            #         marked_left_img = draw_detections_on_image(img_left, left_result.detections)
            #         left_marked_path = os.path.join(SAVE_PATH_LEFT_MARKED, left_marked_filename)
            #         cv2.imwrite(left_marked_path, marked_left_img)
            #         logger.info(f"Saved marked left image: {left_marked_path}")
                
            #     if right_result and right_result.success:
            #         marked_right_img = draw_detections_on_image(img_right, right_result.detections)
            #         right_marked_path = os.path.join(SAVE_PATH_RIGHT_MARKED, right_marked_filename)
            #         cv2.imwrite(right_marked_path, marked_right_img)
            #         logger.info(f"Saved marked right image: {right_marked_path}")

            # Debug 直接原图覆盖
            left_marked_path = os.path.join(SAVE_PATH_LEFT_MARKED, left_marked_filename)
            cv2.imwrite(left_marked_path, img_left)
            logger.info(f"Saved marked left image: {left_marked_path}")

            right_marked_path = os.path.join(SAVE_PATH_RIGHT_MARKED, right_marked_filename)
            cv2.imwrite(right_marked_path, img_right)
            logger.info(f"Saved marked right image: {right_marked_path}")
        
        except Exception as e:
            logger.error(f"Error processing images with VisionAPIClient: {e}")
            # 即使处理失败，也继续保存原图

        # 将图片信息写入数据库，包含标注图片字段
        conn = sqlite3.connect(DATABASE_PATH)
        cursor = conn.cursor()
        cursor.execute('''
            INSERT INTO images (left_filename, right_filename, left_marked_filename, right_marked_filename, timestamp, metadata, comment)
            VALUES (?, ?, ?, ?, ?, ?, ?)
        ''', (left_filename, right_filename, 
              left_marked_filename if left_marked_path else None, 
              right_marked_filename if right_marked_path else None,
              float(timestamp_str), json.dumps(metadata), comment))
        conn.commit()
        image_id = cursor.lastrowid # 获取新插入记录的 ID
        conn.close()
        logger.info(f"Recorded image pair (ID: {image_id}) in database.")

        # 将 OpenCV 图像编码为 base64 字符串，用于 WebSocket 传输
        _, left_encoded = cv2.imencode('.jpg', img_left)
        _, right_encoded = cv2.imencode('.jpg', img_right)
        left_b64 = base64.b64encode(left_encoded).decode('utf-8')
        right_b64 = base64.b64encode(right_encoded).decode('utf-8')

        # 更新用于实时显示的全局变量 (如果需要)
        with frame_lock:
            global latest_left_frame, latest_right_frame, latest_timestamp
            latest_left_frame = img_left
            latest_right_frame = img_right
            latest_timestamp = timestamp_str

        socketio.emit('update_image', {
            'left_image': left_b64,
            'right_image': right_b64,
            'timestamp': timestamp_str
        })

        return jsonify({"message": "Images received, saved, and pushed via WebSocket", "timestamp": timestamp_str, "id": image_id})

    except Exception as e:
        logger.error(f"Error processing upload: {e}")
        return jsonify({"error": str(e)}), 500

@app.route('/api/images/comment', methods=['PUT'])
def update_image_comment():
    """API: 更新图片的 comment"""
    data = request.json
    image_id = data.get('id')
    comment = data.get('comment', '')
    
    if not image_id:
        return jsonify({"error": "Image ID is required"}), 400

    conn = sqlite3.connect(DATABASE_PATH)
    cursor = conn.cursor()
    # 更新 comment 字段
    cursor.execute("UPDATE images SET comment = ? WHERE id = ?", (comment, image_id))
    conn.commit()
    conn.close()
    
    return jsonify({"message": f"Comment for image {image_id} updated successfully"})

@app.route('/api/images/position', methods=['PUT'])
def update_image_position():
    """API: 更新图片的位置编号"""
    data = request.json
    image_id = data.get('id')
    left_position = data.get('left_position', 0)
    right_position = data.get('right_position', 0)
    
    if not image_id:
        return jsonify({"error": "Image ID is required"}), 400

    logger.info(f"Updating position for image {image_id}: {left_position}, {right_position}")

    conn = sqlite3.connect(DATABASE_PATH)
    cursor = conn.cursor()

    # --- Removed ALTER TABLE logic as columns are now in init_db ---
    # try:
    #     cursor.execute("""
    #         ALTER TABLE images ADD COLUMN left_position INTEGER DEFAULT 0
    #     """)
    # except sqlite3.OperationalError:
    #     pass
    # 
    # try:
    #     cursor.execute("""
    #         ALTER TABLE images ADD COLUMN right_position INTEGER DEFAULT 0
    #     """)
    # except sqlite3.OperationalError:
    #     pass
    # --- End Removal ---
    
    # 更新位置字段
    cursor.execute("UPDATE images SET left_position = ?, right_position = ? WHERE id = ?", 
                   (left_position, right_position, image_id))
    conn.commit()
    conn.close()
    
    return jsonify({"message": f"Position for image {image_id} updated successfully"})

@app.route('/status')
def status():
    with frame_lock:
        has_frames = latest_left_frame is not None and latest_right_frame is not None
        timestamp = latest_timestamp if has_frames else "N/A"
    return jsonify({"has_frames": has_frames, "latest_timestamp": timestamp})

@app.route('/api/images/manual-detections', methods=['PUT'])
def update_manual_detections():
    """API: 更新图片的人工标注检测框结果，支持左右图像分别标注"""
    data = request.json
    image_id = data.get('id')
    side = data.get('side', 'left')  # 获取 side 参数，默认为左侧
    detections = data.get('detections')
    
    if not image_id or detections is None:
        return jsonify({"error": "Image ID and detections are required"}), 400
    
    # 验证检测数据格式
    if not isinstance(detections, list):
        return jsonify({"error": "Detections must be a list"}), 400
    
    for detection in detections:
        if not isinstance(detection, dict):
            return jsonify({"error": "Each detection must be a dictionary"}), 400
        
        required_keys = ['id', 'label', 'bbox']
        for key in required_keys:
            if key not in detection:
                return jsonify({"error": f"Missing required key '{key}' in detection"}), 400
        
        # 验证 ID
        if not isinstance(detection['id'], int) or detection['id'] not in [1, 2, 3, 4]:
            return jsonify({"error": f"Invalid ID in detection: {detection['id']}"}), 400
        
        # 验证标签
        valid_labels = ['caisson', 'soldier', 'gun', 'number']
        if detection['label'] not in valid_labels:
            return jsonify({"error": f"Invalid label in detection: {detection['label']}"}), 400
        
        # 验证边界框
        bbox = detection['bbox']
        if not isinstance(bbox, list) or len(bbox) != 4:
            return jsonify({"error": f"Invalid bbox format in detection"}), 400
        
        for coord in bbox:
            if not isinstance(coord, int) or not (0 <= coord <= 999):
                return jsonify({"error": f"Invalid bbox coordinate: {coord}"}), 400
    
    conn = sqlite3.connect(DATABASE_PATH)
    cursor = conn.cursor()
    
    cursor.execute("SELECT id FROM images WHERE id = ?", (image_id,))
    if not cursor.fetchone():
        conn.close()
        return jsonify({"error": "Image not found"}), 404
    
    # --- Removed ALTER TABLE logic as columns are now in init_db ---
    # try:
    #     cursor.execute("""
    #         ALTER TABLE images ADD COLUMN manual_detections_left TEXT
    #     """)
    # except sqlite3.OperationalError:
    #     pass
    # 
    # try:
    #     cursor.execute("""
    #         ALTER TABLE images ADD COLUMN manual_detections_right TEXT
    #     """)
    # except sqlite3.OperationalError:
    #     pass
    # 
    # try:
    #     cursor.execute("""
    #         ALTER TABLE images ADD COLUMN is_manual_labeled_left INTEGER DEFAULT 0
    #     """)
    # except sqlite3.OperationalError:
    #     pass
    # 
    # try:
    #     cursor.execute("""
    #         ALTER TABLE images ADD COLUMN is_manual_labeled_right INTEGER DEFAULT 0
    #     """)
    # except sqlite3.OperationalError:
    #     pass
    # --- End Removal ---
    
    # 根据 side 参数更新对应的人工标注结果
    if side == 'left':
        cursor.execute("""
            UPDATE images 
            SET manual_detections_left = ?, is_manual_labeled_left = 1
            WHERE id = ?
        """, (json.dumps(detections), image_id))
    else:  # side == 'right'
        cursor.execute("""
            UPDATE images 
            SET manual_detections_right = ?, is_manual_labeled_right = 1
            WHERE id = ?
        """, (json.dumps(detections), image_id))
    
    conn.commit()
    conn.close()
    
    # 重新生成标注图片
    try:
        regenerate_marked_images(image_id, detections, side)
        return jsonify({"message": f"Manual detections for image {image_id} ({side}) updated successfully and marked images regenerated"})
    except Exception as e:
        return jsonify({"message": f"Manual detections for image {image_id} ({side}) updated successfully but failed to regenerate marked images: {str(e)}"}), 500

def regenerate_marked_images(image_id, detections, side):
    """重新生成标注图片，支持左右图像分别处理"""
    conn = sqlite3.connect(DATABASE_PATH)
    cursor = conn.cursor()
    cursor.execute("""
        SELECT left_filename, right_filename, left_marked_filename, right_marked_filename, left_position, right_position
        FROM images 
        WHERE id = ?
    """, (image_id,))
    row = cursor.fetchone()
    conn.close()
    
    if not row:
        raise Exception("Image not found")
    
    left_filename, right_filename, left_marked_filename, right_marked_filename, left_position, right_position = row
    
    # 根据指定的 side 重新生成对应的标注图片
    if side == 'left' and left_marked_filename:
        left_path = os.path.join(SAVE_PATH_LEFT, left_filename)
        left_marked_path = os.path.join(SAVE_PATH_LEFT_MARKED, left_marked_filename)
        
        if os.path.exists(left_path):
            img_left = cv2.imread(left_path)
            if img_left is not None:
                marked_left_img = draw_detections_on_image(img_left, detections, left_position=left_position, right_position=None)
                cv2.imwrite(left_marked_path, marked_left_img)
    
    elif side == 'right' and right_marked_filename:
        right_path = os.path.join(SAVE_PATH_RIGHT, right_filename)
        right_marked_path = os.path.join(SAVE_PATH_RIGHT_MARKED, right_marked_filename)
        
        if os.path.exists(right_path):
            img_right = cv2.imread(right_path)
            if img_right is not None:
                marked_right_img = draw_detections_on_image(img_right, detections, left_position=None, right_position=right_position)
                cv2.imwrite(right_marked_path, marked_right_img)

@app.route('/manual-annotation')
def manual_annotation():
    """标注页面"""
    return render_template('manual_annotation.html')

@app.route('/view')
def simple_view():
    """查看图片列表页面"""
    return render_template('view.html')

# --- SocketIO 事件处理程序 ---
@socketio.event
def connect():
    """客户端连接事件"""
    logger.info("Client connected")

@socketio.event
def disconnect():
    """客户端断开连接事件"""
    logger.info("Client disconnected")

@socketio.event
def capture_button(data):
    """
    SocketIO 事件处理器，当客户端发送 'button_pressed' 事件时触发
    """
    try:
        image_client.request_sync()
        logger.info("Request sent to server.")
    except Exception as e:
        logger.error(f"Error sending request: {e}")


if __name__ == '__main__':
    logger.info(f"Starting Flask-SocketIO server on {FLASK_HOST}:{FLASK_PORT}")
    socketio.run(app, host=FLASK_HOST, port=FLASK_PORT, debug=False, allow_unsafe_werkzeug=True)