{
 "cells": [
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-14T04:06:31.135934Z",
     "start_time": "2025-04-14T04:06:30.845929Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "from skimage.feature import local_binary_pattern\n"
   ],
   "id": "9157e102c51206bb",
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-14T04:06:31.144988Z",
     "start_time": "2025-04-14T04:06:31.138940Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def extract_lbp_top(video_path, radius=2, n_points=8, method='uniform', block_size=10):\n",
    "    cap = cv2.VideoCapture(video_path)\n",
    "    frames = []\n",
    "\n",
    "    # 读取所有帧\n",
    "    while True:\n",
    "        ret, frame = cap.read()\n",
    "        if not ret:\n",
    "            break\n",
    "        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n",
    "        frames.append(gray)\n",
    "    cap.release()\n",
    "\n",
    "    frames = np.array(frames)\n",
    "    T, H, W = frames.shape  # 时间、空间维度\n",
    "\n",
    "    # 使用滑动窗口计算 XT, YT 平面\n",
    "    hist_xy = np.zeros((n_points + 2,))\n",
    "    hist_xt = np.zeros((n_points + 2,))\n",
    "    hist_yt = np.zeros((n_points + 2,))\n",
    "\n",
    "    # LBP on XY plane\n",
    "    for t in range(0, T, block_size):\n",
    "        if t >= T:\n",
    "            break\n",
    "        lbp = local_binary_pattern(frames[t], n_points, radius, method)\n",
    "        hist, _ = np.histogram(lbp.ravel(), bins=np.arange(0, n_points + 3), density=True)\n",
    "        hist_xy += hist\n",
    "\n",
    "    # LBP on XT plane\n",
    "    for y in range(0, H, block_size):\n",
    "        if y >= H:\n",
    "            break\n",
    "        xt_plane = frames[:, y, :]\n",
    "        lbp = local_binary_pattern(xt_plane, n_points, radius, method)\n",
    "        hist, _ = np.histogram(lbp.ravel(), bins=np.arange(0, n_points + 3), density=True)\n",
    "        hist_xt += hist\n",
    "\n",
    "    # LBP on YT plane\n",
    "    for x in range(0, W, block_size):\n",
    "        if x >= W:\n",
    "            break\n",
    "        yt_plane = frames[:, :, x]\n",
    "        lbp = local_binary_pattern(yt_plane, n_points, radius, method)\n",
    "        hist, _ = np.histogram(lbp.ravel(), bins=np.arange(0, n_points + 3), density=True)\n",
    "        hist_yt += hist\n",
    "\n",
    "    # 拼接三个平面的直方图作为最终特征向量\n",
    "    feature_vector = np.concatenate([hist_xy, hist_xt, hist_yt])\n",
    "    feature_vector /= np.linalg.norm(feature_vector)  # 归一化\n",
    "\n",
    "    return feature_vector"
   ],
   "id": "d9d5bd6f6a9e114a",
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-14T04:06:31.297545Z",
     "start_time": "2025-04-14T04:06:31.294247Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def getFeature(video_path = r\"D:\\DESKTOP\\2025\\44\\a1\\dataset\\org\\1.mp4\"):\n",
    "\n",
    "    feature = extract_lbp_top(video_path)\n",
    "    # print(\"Video feature shape (for copyright):\", feature.shape)\n",
    "    return feature"
   ],
   "id": "404b8b3562026f1f",
   "outputs": [],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-14T04:06:32.509232Z",
     "start_time": "2025-04-14T04:06:31.302931Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import sqlite3\n",
    "import io\n",
    "import os\n",
    "import tqdm\n",
    "\n",
    "# 注册适配器与转换器：numpy数组 <-> BLOB\n",
    "def adapt_array(arr):\n",
    "    out = io.BytesIO()\n",
    "    np.save(out, arr)\n",
    "    out.seek(0)\n",
    "    return sqlite3.Binary(out.read())\n",
    "\n",
    "def convert_array(text):\n",
    "    out = io.BytesIO(text)\n",
    "    out.seek(0)\n",
    "    return np.load(out)\n",
    "\n",
    "# 注册自定义类型处理\n",
    "sqlite3.register_adapter(np.ndarray, adapt_array)\n",
    "sqlite3.register_converter(\"array\", convert_array)\n",
    "\n",
    "# 创建数据库连接（带类型检测）\n",
    "conn = sqlite3.connect(\"LBPTOP.db\", detect_types=sqlite3.PARSE_DECLTYPES)\n",
    "cursor = conn.cursor()\n",
    "\n",
    "# 创建表\n",
    "cursor.execute(\"\"\"\n",
    "CREATE TABLE IF NOT EXISTS data (\n",
    "    id INTEGER PRIMARY KEY,\n",
    "    array BLOB,\n",
    "    group_path TEXT,\n",
    "    full_path TEXT\n",
    ")\n",
    "\"\"\")\n",
    "\n",
    "\n",
    "def add_to_db(array_to_store,group_path,full_path):\n",
    "    cursor.execute(\"INSERT INTO data (array,group_path,full_path) VALUES (?,?,?)\", (array_to_store,group_path,full_path,))\n",
    "    conn.commit()\n",
    "\n",
    "# # 读取数组\n",
    "# cursor.execute(\"SELECT array FROM data WHERE id=1\")\n",
    "# fetched_array = cursor.fetchone()[0]\n",
    "#\n",
    "# print(\"原始数组:\\n\", array_to_store)\n",
    "# print(\"读取的数组:\\n\", fetched_array)\n",
    "\n",
    "folder_path = r\"D:\\DESKTOP\\2025\\44\\a1\\dataset\"\n",
    "\n",
    "all_files = []\n",
    "names = [str(x)+\".mp4\" for x in range(10)]\n",
    "print(names)\n",
    "\n",
    "\n",
    "# 遍历文件夹\n",
    "for group_path in os.listdir(folder_path):\n",
    "    full_path = os.path.join(folder_path, group_path)\n",
    "    if os.path.isdir(full_path):\n",
    "        # 遍历子文件夹\n",
    "        for video_path in os.listdir(full_path):\n",
    "            if os.path.basename(video_path) in names:\n",
    "                video_full_path = os.path.join(full_path, video_path)\n",
    "                if os.path.isfile(video_full_path):\n",
    "                    # 处理视频文件\n",
    "                    all_files.append((group_path,video_full_path))\n",
    "print(len(all_files))\n"
   ],
   "id": "4dc69bad309cb6b1",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['0.mp4', '1.mp4', '2.mp4', '3.mp4', '4.mp4', '5.mp4', '6.mp4', '7.mp4', '8.mp4', '9.mp4']\n",
      "70\n"
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-14T04:20:52.302187Z",
     "start_time": "2025-04-14T04:06:32.521053Z"
    }
   },
   "cell_type": "code",
   "source": [
    "for group_path, video_full_path in tqdm.tqdm(all_files):\n",
    "    # 读取视频特征\n",
    "    feature = getFeature(video_full_path)\n",
    "    # 将特征存储到数据库\n",
    "    add_to_db(feature,group_path,video_full_path)\n",
    "    # print(f\"已处理并存储: {video_full_path}\")\n",
    "\n",
    "conn.close()\n"
   ],
   "id": "3cd83672f6901125",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 70/70 [14:19<00:00, 12.28s/it]\n"
     ]
    }
   ],
   "execution_count": 5
  }
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