Upload folder using huggingface_hub

.gitignore

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+AVE/
+AVE_Audio/

.hfignore

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+AVE/
+AVE_Audio/

ReadMe.txt

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+AVE.zip: videos in AVE dataset. One video may contain different audio-visual events, so the total number of videos is not 4143.
+
+annotations.txt: annotations of AVE dataset. For each sample, you can find its event catergory, YouTube ID, 
+                 Quality (all good, means that it contains an AVE), start time of an audio-visual event, end 
+				 time of an audio-visual event.
+
+train/val/test-Set.txt: training/validation/testing set used in our ECCV paper.
+ 
+
+If you used our AVE dataset, please consider cite our paper:
+@inproceedings{TianECCV2018,
+	 title={Audio-Visual Event Localization in Unconstrained Videos},
+     author={Tian, Yapeng and Shi, Jing and Li, Bochen and Duan, Zhiyao and Xu, Chenliang},
+	 editor="Ferrari, Vittorio and Hebert, Martial and Sminchisescu, Cristian and Weiss, Yair",
+	 booktitle="Computer Vision -- ECCV 2018",
+	 year="2018",
+	 publisher="Springer",
+}

check_thinksound_latent.py

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+import torch
+from pathlib import Path
+
+# 要遍历的目录
+dir_path = Path("AVE_Dataset/test/video")  # 也可以改成 audio
+
+# 遍历所有 .pth 文件（按文件名排序）
+for file_path in sorted(dir_path.glob("*.pth")):
+    data = torch.load(file_path, map_location="cpu")
+    if len(data['timing_plan']) > 1:
+        pass
+    print(f"Loaded {file_path}, keys: {list(data.keys())}")
+
+file_path = "AVE_Dataset/train/video/0vWh6Knoer8.pth"
+# file_path = "AVE_Dataset/train/audio/09o2OwlUCGI.pth"
+data = torch.load(file_path, map_location="cpu")
+
+print(type(data))
+# 如果是张量
+if isinstance(data, torch.Tensor):
+    print(data.shape)
+    print(data)
+# 如果是字典
+elif isinstance(data, dict):
+    for k, v in data.items():
+        print(f"{k}: {type(v)}, shape={getattr(v, 'shape', None)}")
+# 如果是列表
+elif isinstance(data, list):
+    print(f"List length: {len(data)}")
+    for i, item in enumerate(data[:3]):  # 只看前三个
+        print(f"[{i}] {type(item)}, shape={getattr(item, 'shape', None)}")
+        

extract_audio.py

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+from pathlib import Path
+from tqdm import tqdm
+import subprocess
+
+txt_path = Path("testSet.txt")      # 你的 txt 文件路径
+video_dir = Path("AVE")          # 视频所在目录
+audio_dir = Path("AVE_Audio")    # 输出音频目录
+audio_dir.mkdir(parents=True, exist_ok=True)
+
+# 读取 ID 或目录名（txt 每行：类别&id&...）
+with open(txt_path, "r", encoding="utf-8") as f:
+    ids = [line.strip().split("&")[1] for line in f if line.strip()]
+
+for vid in tqdm(ids):
+    mp4_path = video_dir / f"{vid}.mp4"
+    wav_path = audio_dir / f"{vid}.wav"
+
+    if not mp4_path.exists():
+        print(f"⚠️ {mp4_path} 不存在，跳过")
+        continue
+
+    cmd = [
+        "ffmpeg", "-y",
+        "-i", str(mp4_path),
+        "-vn",
+        "-acodec", "pcm_s16le",
+        "-ar", "16000",
+        "-ac", "1",
+        str(wav_path)
+    ]
+    subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+
+print("✅ 转换完成")

generate_label.py

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+import os
+from pathlib import Path
+
+# 要处理的根目录
+root_dirs = ["train/video", "train/audio", "val/video", "test/video"]
+
+for path in root_dirs:
+    p = Path(path)
+    if not p.exists():
+        print(f"❌ 路径不存在: {p}")
+        continue
+
+    # 获取所有 .pth 文件的文件名（不含路径）
+    filenames = sorted([f.name for f in p.glob("*.pth")])
+
+    # 输出文件路径：train/video → train/video.txt
+    output_txt = p.parent / f"{p.name}.txt"
+    with open(output_txt, "w") as f:
+        for name in filenames:
+            f.write(name + "\n")
+
+    print(f"✅ 生成文件: {output_txt}，共 {len(filenames)} 个条目")

gt_cache/imagebind_video.pth

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+size 17988366

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gt_cache/synchformer_video.pth

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gt_cache/vggish_features.pth

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init_ave.sh

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+#!/bin/bash
+
+set -e  # 脚本中遇到错误就退出
+echo "当前执行路径：$(pwd)"
+echo "🔧 开始环境配置..."
+
+# 安装必要工具
+sudo apt-get update
+echo "📦 检查 dos2unix 和 vim 是否已安装..."
+
+# 检查 dos2unix
+if command -v dos2unix >/dev/null 2>&1; then
+    echo "✅ dos2unix 已安装，跳过安装。"
+else
+    echo "📦 安装 dos2unix..."
+    sudo apt-get install -y dos2unix
+fi
+
+# 检查 vim
+if command -v vim >/dev/null 2>&1; then
+    echo "✅ vim 已安装，跳过安装。"
+else
+    echo "📦 安装 vim..."
+    sudo apt-get install -y vim
+fi
+# 检查 bsdtar
+if command -v bsdtar >/dev/null 2>&1; then
+    echo "✅ bsdtar 已安装，跳过安装。"
+else
+    echo "📦 安装 bsdtar（libarchive-tools）..."
+    sudo apt-get install -y libarchive-tools
+fi
+# 检查 libglib2.0-0
+if dpkg -s libglib2.0-0 >/dev/null 2>&1; then
+    echo "✅ libglib2.0-0 已安装，跳过安装。"
+else
+    echo "📦 安装 libglib2.0-0..."
+    sudo apt-get update
+    sudo apt-get install -y libglib2.0-0
+fi
+
+# 转换脚本格式
+dos2unix init_env.sh
+
+# 安装 Git LFS
+echo "📦 检查 Git LFS 是否已安装..."
+if git lfs version >/dev/null 2>&1; then
+    echo "✅ Git LFS 已安装，跳过安装步骤。"
+else
+    echo "📦 未检测到 Git LFS，开始安装..."
+    curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
+    sudo apt-get install -y git-lfs
+    git lfs install
+    echo "✅ Git LFS 安装完成。"
+fi
+
+
+
+python extract_audio.py
+python generate_label.py
+
+exit 0
+
+cd ../..
+pip install gdown
+gdown 1FjKwe79e0u96vdjIVwfRQ1V6SoDHe7kK
+unzip AVE_Dataset.zip
+

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