From e90d776f5302a60a77cbacbb98d31daa51b10db7 Mon Sep 17 00:00:00 2001
From: zikai <1621362626@qq.com>
Date: Mon, 14 Apr 2025 17:15:38 +1000
Subject: [PATCH] init
---
.idea/.gitignore | 8 +
.idea/44.iml | 10 +
.idea/dataSources.xml | 20 +
.idea/inspectionProfiles/Project_Default.xml | 31 ++
.../inspectionProfiles/profiles_settings.xml | 6 +
.idea/misc.xml | 6 +
.idea/modules.xml | 8 +
.idea/vcs.xml | 6 +
1.py | 49 +++
I3D.py | 52 +++
LBPTOP.db | Bin 0 -> 40960 bytes
LBPTOP.ipynb | 246 ++++++++++++
LBPTOP.py | 61 +++
analy.ipynb | 292 ++++++++++++++
i3d.db | Bin 0 -> 618496 bytes
i3d.ipynb | 279 ++++++++++++++
requirements.txt | Bin 0 -> 4688 bytes
slowFast.ipynb | 357 ++++++++++++++++++
slowFast.py | 159 ++++++++
slowfast.db | Bin 0 -> 679936 bytes
20 files changed, 1590 insertions(+)
create mode 100644 .idea/.gitignore
create mode 100644 .idea/44.iml
create mode 100644 .idea/dataSources.xml
create mode 100644 .idea/inspectionProfiles/Project_Default.xml
create mode 100644 .idea/inspectionProfiles/profiles_settings.xml
create mode 100644 .idea/misc.xml
create mode 100644 .idea/modules.xml
create mode 100644 .idea/vcs.xml
create mode 100644 1.py
create mode 100644 I3D.py
create mode 100644 LBPTOP.db
create mode 100644 LBPTOP.ipynb
create mode 100644 LBPTOP.py
create mode 100644 analy.ipynb
create mode 100644 i3d.db
create mode 100644 i3d.ipynb
create mode 100644 requirements.txt
create mode 100644 slowFast.ipynb
create mode 100644 slowFast.py
create mode 100644 slowfast.db
diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 0000000..35410ca
--- /dev/null
+++ b/.idea/.gitignore
@@ -0,0 +1,8 @@
+# 默认忽略的文件
+/shelf/
+/workspace.xml
+# 基于编辑器的 HTTP 客户端请求
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
diff --git a/.idea/44.iml b/.idea/44.iml
new file mode 100644
index 0000000..1a0be46
--- /dev/null
+++ b/.idea/44.iml
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/dataSources.xml b/.idea/dataSources.xml
new file mode 100644
index 0000000..c2bb027
--- /dev/null
+++ b/.idea/dataSources.xml
@@ -0,0 +1,20 @@
+
+
+
+
+ sqlite.xerial
+ true
+ org.sqlite.JDBC
+ jdbc:sqlite:D:\code\python\44\i3d.db
+ $ProjectFileDir$
+
+
+ file://$APPLICATION_CONFIG_DIR$/jdbc-drivers/Xerial SQLiteJDBC/3.45.1/org/xerial/sqlite-jdbc/3.45.1.0/sqlite-jdbc-3.45.1.0.jar
+
+
+ file://$APPLICATION_CONFIG_DIR$/jdbc-drivers/Xerial SQLiteJDBC/3.45.1/org/slf4j/slf4j-api/1.7.36/slf4j-api-1.7.36.jar
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/Project_Default.xml b/.idea/inspectionProfiles/Project_Default.xml
new file mode 100644
index 0000000..837d06b
--- /dev/null
+++ b/.idea/inspectionProfiles/Project_Default.xml
@@ -0,0 +1,31 @@
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000..105ce2d
--- /dev/null
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
new file mode 100644
index 0000000..afd2615
--- /dev/null
+++ b/.idea/misc.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
new file mode 100644
index 0000000..e4cde36
--- /dev/null
+++ b/.idea/modules.xml
@@ -0,0 +1,8 @@
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 0000000..94a25f7
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/1.py b/1.py
new file mode 100644
index 0000000..fc19040
--- /dev/null
+++ b/1.py
@@ -0,0 +1,49 @@
+import os
+import subprocess
+import tempfile
+import shutil
+
+# 根目录
+input_dir = r"D:\DESKTOP\2025\44\a1\dataset" # 替换为你的视频根目录
+video_exts = {".avi", ".mov", ".mkv", ".flv", ".webm", ".wmv", ".mp4",".m4s"}
+
+def convert_and_replace(filepath):
+ ext = os.path.splitext(filepath)[1].lower()
+ if ext not in video_exts:
+ return
+
+ print(f"处理文件: {filepath}")
+
+ # 创建临时输出文件
+ temp_fd, temp_path = tempfile.mkstemp(suffix=".mp4")
+ os.close(temp_fd) # 不使用 open 的文件描述符
+
+ # ffmpeg 转换命令（保留前30秒，360p，输出mp4）
+ cmd = [
+ "ffmpeg",
+ "-y",
+ "-i", filepath,
+ "-t", "30",
+ "-vf", "scale=-2:480",
+ "-c:v", "libx264", # 改为 libx265 可使用 H.265
+ "-preset", "slow",
+ "-crf", "18",
+ "-c:a", "aac",
+ "-b:a", "64k",
+ temp_path
+ ]
+
+ try:
+ subprocess.run(cmd, check=True)
+ shutil.move(temp_path, filepath)
+ print(f"已替换: {filepath}")
+ except subprocess.CalledProcessError as e:
+ print(f"失败: {filepath}\n{e}")
+ if os.path.exists(temp_path):
+ os.remove(temp_path)
+
+# 递归遍历处理
+for root, _, files in os.walk(input_dir):
+ for name in files:
+ file_path = os.path.join(root, name)
+ convert_and_replace(file_path)
\ No newline at end of file
diff --git a/I3D.py b/I3D.py
new file mode 100644
index 0000000..c9cf6a1
--- /dev/null
+++ b/I3D.py
@@ -0,0 +1,52 @@
+import torch
+import torch.nn.functional as F
+import torchvision.transforms as transforms
+from pytorchvideo.models.hub import i3d_r50
+import cv2
+import numpy as np
+from PIL import Image
+
+model = i3d_r50(pretrained=True).eval()
+feature_extractor = torch.nn.Sequential(*model.blocks[:-1])
+
+def preprocess_video(video_path, num_frames=32, size=224):
+ cap = cv2.VideoCapture(video_path)
+ frames = []
+ transform = transforms.Compose([
+ transforms.Resize((size, size)),
+ transforms.ToTensor(),
+ transforms.Normalize(mean=[0.45, 0.45, 0.45], std=[0.225, 0.225, 0.225])
+ ])
+
+ total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+ frame_indices = np.linspace(0, total_frames - 1, num_frames).astype(int)
+
+ for i in frame_indices:
+ cap.set(cv2.CAP_PROP_POS_FRAMES, i)
+ ret, frame = cap.read()
+ if not ret:
+ break
+ frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+ frame = Image.fromarray(frame)
+ frame = transform(frame)
+ frames.append(frame)
+
+ cap.release()
+ video_tensor = torch.stack(frames).permute(1, 0, 2, 3).unsqueeze(0)
+ return video_tensor
+
+def extract_features(video_tensor):
+ with torch.no_grad():
+ features = feature_extractor(video_tensor)
+ features = F.adaptive_avg_pool3d(features, 1)
+ features = features.flatten()
+ return features.numpy()
+
+def video_features(video_path):
+ video_tensor = preprocess_video(video_path)
+ features = extract_features(video_tensor)
+ return features
+
+video_path = r'D:\DESKTOP\2025\44\a1\dataset\org\0.mp4'
+video_f = video_features(video_path)
+print(f"视频features: {video_f.shape}")
diff --git a/LBPTOP.db b/LBPTOP.db
new file mode 100644
index 0000000000000000000000000000000000000000..98b479d19c2bf08e5b5d3faca26bd0d272b79bfa
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diff --git a/LBPTOP.ipynb b/LBPTOP.ipynb
new file mode 100644
index 0000000..ef83897
--- /dev/null
+++ b/LBPTOP.ipynb
@@ -0,0 +1,246 @@
+{
+ "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
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.6"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/LBPTOP.py b/LBPTOP.py
new file mode 100644
index 0000000..465c0aa
--- /dev/null
+++ b/LBPTOP.py
@@ -0,0 +1,61 @@
+import cv2
+import numpy as np
+from skimage.feature import local_binary_pattern
+
+
+def extract_lbp_top(video_path, radius=2, n_points=8, method='uniform', block_size=10):
+ cap = cv2.VideoCapture(video_path)
+ frames = []
+
+ # 读取所有帧
+ while True:
+ ret, frame = cap.read()
+ if not ret:
+ break
+ gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+ frames.append(gray)
+ cap.release()
+
+ frames = np.array(frames)
+ T, H, W = frames.shape # 时间、空间维度
+
+ # 使用滑动窗口计算 XT, YT 平面
+ hist_xy = np.zeros((n_points + 2,))
+ hist_xt = np.zeros((n_points + 2,))
+ hist_yt = np.zeros((n_points + 2,))
+
+ # LBP on XY plane
+ for t in range(0, T, block_size):
+ if t >= T:
+ break
+ lbp = local_binary_pattern(frames[t], n_points, radius, method)
+ hist, _ = np.histogram(lbp.ravel(), bins=np.arange(0, n_points + 3), density=True)
+ hist_xy += hist
+
+ # LBP on XT plane
+ for y in range(0, H, block_size):
+ if y >= H:
+ break
+ xt_plane = frames[:, y, :]
+ lbp = local_binary_pattern(xt_plane, n_points, radius, method)
+ hist, _ = np.histogram(lbp.ravel(), bins=np.arange(0, n_points + 3), density=True)
+ hist_xt += hist
+
+ # LBP on YT plane
+ for x in range(0, W, block_size):
+ if x >= W:
+ break
+ yt_plane = frames[:, :, x]
+ lbp = local_binary_pattern(yt_plane, n_points, radius, method)
+ hist, _ = np.histogram(lbp.ravel(), bins=np.arange(0, n_points + 3), density=True)
+ hist_yt += hist
+
+ # 拼接三个平面的直方图作为最终特征向量
+ feature_vector = np.concatenate([hist_xy, hist_xt, hist_yt])
+ feature_vector /= np.linalg.norm(feature_vector) # 归一化
+
+ return feature_vector
+
+video_path = r'D:\DESKTOP\2025\44\a1\dataset\org\1.mp4'
+features = extract_lbp_top(video_path)
+print(f"特征向量维度: {features.shape}")
\ No newline at end of file
diff --git a/analy.ipynb b/analy.ipynb
new file mode 100644
index 0000000..55695df
--- /dev/null
+++ b/analy.ipynb
@@ -0,0 +1,292 @@
+{
+ "cells": [
+ {
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2025-04-14T06:58:32.199713Z",
+ "start_time": "2025-04-14T06:58:32.134049Z"
+ }
+ },
+ "cell_type": "code",
+ "source": [
+ "import sqlite3\n",
+ "import numpy as np\n",
+ "import io\n",
+ "from numpy.linalg import norm\n",
+ "from collections import defaultdict"
+ ],
+ "id": "6917288db44004ea",
+ "outputs": [],
+ "execution_count": 1
+ },
+ {
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2025-04-14T06:58:34.129528Z",
+ "start_time": "2025-04-14T06:58:34.126022Z"
+ }
+ },
+ "cell_type": "code",
+ "source": [
+ "currdb = \"i3d.db\"\n",
+ "#currdb = \"LBPTOP.db\"\n",
+ "currdb = \"slowfast.db\""
+ ],
+ "id": "dd9b84fa98c77e5a",
+ "outputs": [],
+ "execution_count": 2
+ },
+ {
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2025-04-14T06:58:36.801611Z",
+ "start_time": "2025-04-14T06:58:36.798114Z"
+ }
+ },
+ "cell_type": "code",
+ "source": [
+ "# 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)"
+ ],
+ "id": "fa2ab158cbe0aa98",
+ "outputs": [],
+ "execution_count": 3
+ },
+ {
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2025-04-14T07:01:06.063185Z",
+ "start_time": "2025-04-14T07:01:06.060008Z"
+ }
+ },
+ "cell_type": "code",
+ "source": [
+ "\n",
+ "sqlite3.register_adapter(np.ndarray, adapt_array)\n",
+ "sqlite3.register_converter(\"BLOB\", convert_array)\n",
+ "\n",
+ "# 连接SQLite数据库\n",
+ "conn = sqlite3.connect(currdb, detect_types=sqlite3.PARSE_DECLTYPES)\n",
+ "cursor = conn.cursor()"
+ ],
+ "id": "629eb156f332c0bc",
+ "outputs": [],
+ "execution_count": 12
+ },
+ {
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2025-04-14T07:01:06.372809Z",
+ "start_time": "2025-04-14T07:01:06.362911Z"
+ }
+ },
+ "cell_type": "code",
+ "source": [
+ "# 读取数据库所有数据\n",
+ "cursor.execute(\"SELECT id, array, group_path, full_path FROM data\")\n",
+ "all_data = cursor.fetchall()"
+ ],
+ "id": "ba7902156f1b6117",
+ "outputs": [],
+ "execution_count": 13
+ },
+ {
+ "metadata": {
+ "collapsed": true,
+ "ExecuteTime": {
+ "end_time": "2025-04-14T07:01:06.786016Z",
+ "start_time": "2025-04-14T07:01:06.779812Z"
+ }
+ },
+ "cell_type": "code",
+ "source": [
+ "# 整理特征\n",
+ "data_by_group = defaultdict(list)\n",
+ "for vid, arr, group, path in all_data:\n",
+ " data_by_group[group].append({'id': vid, 'feature': arr, 'path': path})\n",
+ "\n",
+ "# 相似度函数 (余弦相似度)\n",
+ "def cosine_similarity(a, b):\n",
+ " return np.dot(a, b) / (norm(a) * norm(b))\n",
+ "\n",
+ "# 计算指标函数\n",
+ "def compute_metrics(org_feats, query_feats, sim_feats, K=5):\n",
+ " precision_top1 = []\n",
+ " recall_at_k = []\n",
+ " AP_list = []\n",
+ "\n",
+ " # 构建搜索库 (原始视频 + 相似视频)\n",
+ " search_db = org_feats + sim_feats\n",
+ "\n",
+ " for query in query_feats:\n",
+ " similarities = []\n",
+ " query_feature = query['feature']\n",
+ "\n",
+ " # 计算query与所有库视频的相似度\n",
+ " for target in search_db:\n",
+ " sim = cosine_similarity(query_feature, target['feature'])\n",
+ " label = 1 if target in org_feats else 0 # 1代表匹配，0代表不匹配\n",
+ " similarities.append((sim, label))\n",
+ "\n",
+ " # 相似度降序排序\n",
+ " similarities.sort(key=lambda x: x[0], reverse=True)\n",
+ " labels_sorted = [label for _, label in similarities]\n",
+ "\n",
+ " # Top-1 precision\n",
+ " precision_top1.append(labels_sorted[0])\n",
+ "\n",
+ " # Recall@K\n",
+ " recall = sum(labels_sorted[:K]) / len(org_feats)\n",
+ " recall_at_k.append(recall)\n",
+ "\n",
+ " # Average Precision (AP)\n",
+ " hits, sum_precisions = 0, 0\n",
+ " for idx, label in enumerate(labels_sorted, start=1):\n",
+ " if label == 1:\n",
+ " hits += 1\n",
+ " sum_precisions += hits / idx\n",
+ " AP = sum_precisions / len(org_feats) if len(org_feats) else 0\n",
+ " AP_list.append(AP)\n",
+ "\n",
+ " # 返回指标均值\n",
+ " return {\n",
+ " 'Top-1 Precision': np.mean(precision_top1),\n",
+ " f'Recall@{K}': np.mean(recall_at_k),\n",
+ " 'MAP': np.mean(AP_list)\n",
+ " }"
+ ],
+ "id": "initial_id",
+ "outputs": [],
+ "execution_count": 14
+ },
+ {
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2025-04-14T07:01:07.745386Z",
+ "start_time": "2025-04-14T07:01:07.740942Z"
+ }
+ },
+ "cell_type": "code",
+ "source": "data_by_group['org'][0]['feature'].shape",
+ "id": "55e57dc7ec56b732",
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(2304,)"
+ ]
+ },
+ "execution_count": 15,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "execution_count": 15
+ },
+ {
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2025-04-14T06:00:12.392784Z",
+ "start_time": "2025-04-14T06:00:12.382725Z"
+ }
+ },
+ "cell_type": "code",
+ "source": [
+ "# 主函数，计算所有变形组的指标\n",
+ "def evaluate_all_variants(K=5):\n",
+ " org_feats = data_by_group['org']\n",
+ " sim_feats = data_by_group['sim']\n",
+ "\n",
+ " results = {}\n",
+ "\n",
+ " # 排除 'org' 和 'sim'，其余都是变形组\n",
+ " variant_groups = [group for group in data_by_group if group not in ['org', 'sim']]\n",
+ "\n",
+ " for variant in variant_groups:\n",
+ " variant_feats = data_by_group[variant]\n",
+ " metrics = compute_metrics(org_feats, variant_feats, sim_feats, K)\n",
+ " results[variant] = metrics\n",
+ "\n",
+ " return results\n",
+ "\n",
+ "# 执行评估\n",
+ "results = evaluate_all_variants(K=3)\n",
+ "\n",
+ "# 输出结果\n",
+ "for variant, metrics in results.items():\n",
+ " print(f\"变形组: {variant}\")\n",
+ " for metric_name, value in metrics.items():\n",
+ " print(f\" {metric_name}: {value:.4f}\")\n",
+ " print(\"-\" * 40)\n",
+ "\n",
+ "# 关闭数据库连接\n",
+ "conn.close()"
+ ],
+ "id": "d9a0103dbc3f1bef",
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "变形组: 动态水印2\n",
+ " Top-1 Precision: 1.0000\n",
+ " Recall@3: 0.1500\n",
+ " MAP: 0.5815\n",
+ "----------------------------------------\n",
+ "变形组: 水印1+2\n",
+ " Top-1 Precision: 0.8000\n",
+ " Recall@3: 0.1600\n",
+ " MAP: 0.5751\n",
+ "----------------------------------------\n",
+ "变形组: 水印1+2+滤镜\n",
+ " Top-1 Precision: 0.8000\n",
+ " Recall@3: 0.1500\n",
+ " MAP: 0.5685\n",
+ "----------------------------------------\n",
+ "变形组: 滤镜\n",
+ " Top-1 Precision: 0.9000\n",
+ " Recall@3: 0.1800\n",
+ " MAP: 0.6100\n",
+ "----------------------------------------\n",
+ "变形组: 静态水印1\n",
+ " Top-1 Precision: 0.9000\n",
+ " Recall@3: 0.1700\n",
+ " MAP: 0.6058\n",
+ "----------------------------------------\n"
+ ]
+ }
+ ],
+ "execution_count": 25
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.6"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
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