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video-metadata-inspector

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Video Metadata Inspector

视频元数据检查工具

Extract and analyze comprehensive metadata from video files including duration, resolution, codec, frame rate, and technical specifications.
从视频文件中提取并分析全面的元数据，包括时长、分辨率、编解码器、帧率以及技术规格。

Purpose

用途

Video metadata inspection for:
  • Format verification and compatibility checking
  • Quality assessment and validation
  • Transcoding planning and optimization
  • Video library cataloging
  • Technical specification reports
视频元数据检查可用于：
  • 格式验证与兼容性检查
  • 质量评估与验证
  • 转码规划与优化
  • 视频库编目
  • 技术规格报告

Features

功能特性

  • Basic Info: Duration, resolution, frame rate, file size
  • Codec Details: Video/audio codec, profile, bitrate
  • Technical Specs: Aspect ratio, pixel format, sample rate
  • Metadata: Title, artist, creation date, tags
  • Batch Analysis: Process multiple files in one operation
  • Export Formats: JSON, CSV, human-readable text
  • 基础信息：时长、分辨率、帧率、文件大小
  • 编解码器详情：视频/音频编解码器、配置文件、比特率
  • 技术规格：宽高比、像素格式、采样率
  • 元数据：标题、创作者、创建日期、标签
  • 批量分析：一次操作处理多个文件
  • 导出格式：JSON、CSV、易读文本格式

Quick Start

快速开始

python
from video_metadata_inspector import VideoMetadataInspector
python
from video_metadata_inspector import VideoMetadataInspector

Inspect single video

Inspect single video

inspector = VideoMetadataInspector() inspector.load('video.mp4') metadata = inspector.get_metadata() print(f"Duration: {metadata['duration_seconds']:.2f}s") print(f"Resolution: {metadata['width']}x{metadata['height']}") print(f"FPS: {metadata['fps']}")
inspector = VideoMetadataInspector() inspector.load('video.mp4') metadata = inspector.get_metadata() print(f"Duration: {metadata['duration_seconds']:.2f}s") print(f"Resolution: {metadata['width']}x{metadata['height']}") print(f"FPS: {metadata['fps']}")

Export full report

Export full report

inspector.export_report('report.json', format='json')
inspector.export_report('report.json', format='json')

Batch inspect directory

Batch inspect directory

inspector.batch_inspect( input_files=['video1.mp4', 'video2.mkv'], output='metadata.csv', format='csv' )
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inspector.batch_inspect( input_files=['video1.mp4', 'video2.mkv'], output='metadata.csv', format='csv' )
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CLI Usage

CLI 使用方法

bash
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bash
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Basic metadata

Basic metadata

python video_metadata_inspector.py input.mp4
python video_metadata_inspector.py input.mp4

Full technical details

Full technical details

python video_metadata_inspector.py input.mp4 --verbose
python video_metadata_inspector.py input.mp4 --verbose

Export to JSON

Export to JSON

python video_metadata_inspector.py input.mp4 --output metadata.json --format json
python video_metadata_inspector.py input.mp4 --output metadata.json --format json

Batch inspect directory

Batch inspect directory

python video_metadata_inspector.py *.mp4 --output metadata.csv --format csv
python video_metadata_inspector.py *.mp4 --output metadata.csv --format csv

Compare multiple videos

Compare multiple videos

python video_metadata_inspector.py video1.mp4 video2.mp4 --compare
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python video_metadata_inspector.py video1.mp4 video2.mp4 --compare
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API Reference

API 参考

VideoMetadataInspector

VideoMetadataInspector

python
class VideoMetadataInspector:
    def load(self, filepath: str) -> 'VideoMetadataInspector'
    def get_metadata(self) -> Dict[str, Any]
    def get_basic_info(self) -> Dict[str, Any]
    def get_video_info(self) -> Dict[str, Any]
    def get_audio_info(self) -> Dict[str, Any]
    def get_format_info(self) -> Dict[str, Any]
    def export_report(self, output: str, format: str = 'json') -> str
    def batch_inspect(self, input_files: List[str], output: str = None,
                     format: str = 'csv') -> pd.DataFrame
    def compare_videos(self, video_files: List[str]) -> pd.DataFrame
python
class VideoMetadataInspector:
    def load(self, filepath: str) -> 'VideoMetadataInspector'
    def get_metadata(self) -> Dict[str, Any]
    def get_basic_info(self) -> Dict[str, Any]
    def get_video_info(self) -> Dict[str, Any]
    def get_audio_info(self) -> Dict[str, Any]
    def get_format_info(self) -> Dict[str, Any]
    def export_report(self, output: str, format: str = 'json') -> str
    def batch_inspect(self, input_files: List[str], output: str = None,
                     format: str = 'csv') -> pd.DataFrame
    def compare_videos(self, video_files: List[str]) -> pd.DataFrame

Metadata Categories

元数据分类

Basic Information

基础信息

  • Duration (seconds, formatted)
  • Resolution (width × height)
  • Frame rate (FPS)
  • File size
  • Aspect ratio
  • 时长（秒，格式化显示）
  • 分辨率（宽 × 高）
  • 帧率（FPS）
  • 文件大小
  • 宽高比

Video Stream

视频流

  • Video codec (H.264, H.265, VP9, etc.)
  • Codec profile and level
  • Bitrate (kbps)
  • Pixel format (yuv420p, etc.)
  • Color space and range
  • 视频编解码器（H.264、H.265、VP9等）
  • 编解码器配置文件与级别
  • 比特率（kbps）
  • 像素格式（yuv420p等）
  • 色彩空间与范围

Audio Stream

音频流

  • Audio codec (AAC, MP3, Opus, etc.)
  • Sample rate (Hz)
  • Channels (mono, stereo, 5.1, etc.)
  • Audio bitrate (kbps)
  • 音频编解码器（AAC、MP3、Opus等）
  • 采样率（Hz）
  • 声道数（单声道、立体声、5.1声道等）
  • 音频比特率（kbps）

Container Format

容器格式

  • Container type (MP4, MKV, AVI, etc.)
  • Creation date
  • Metadata tags (title, artist, description)
  • Number of streams
  • 容器类型（MP4、MKV、AVI等）
  • 创建日期
  • 元数据标签（标题、创作者、描述）
  • 流的数量

Use Cases

使用场景

Format Verification:
python
inspector.load('video.mp4')
info = inspector.get_video_info()
if info['codec'] == 'h264' and info['width'] >= 1920:
    print("✓ Meets requirements: 1080p H.264")
Transcoding Planning:
python
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格式验证：
python
inspector.load('video.mp4')
info = inspector.get_video_info()
if info['codec'] == 'h264' and info['width'] >= 1920:
    print("✓ Meets requirements: 1080p H.264")
转码规划：
python
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Check if transcoding needed

Check if transcoding needed

metadata = inspector.get_metadata() if metadata['video_codec'] != 'h265' or metadata['bitrate_kbps'] > 5000: print("Transcode recommended")

**Quality Assessment:**
```python
metadata = inspector.get_metadata() if metadata['video_codec'] != 'h265' or metadata['bitrate_kbps'] > 5000: print("Transcode recommended")

**质量评估：**
```python

Analyze video quality metrics

Analyze video quality metrics

info = inspector.get_metadata() quality_score = ( (info['width'] * info['height']) / 2073600 * 50 + # Resolution score min(info['fps'] / 60, 1) * 25 + # Frame rate score min(info['bitrate_kbps'] / 10000, 1) * 25 # Bitrate score )
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info = inspector.get_metadata() quality_score = ( (info['width'] * info['height']) / 2073600 * 50 + # Resolution score min(info['fps'] / 60, 1) * 25 + # Frame rate score min(info['bitrate_kbps'] / 10000, 1) * 25 # Bitrate score )
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Common Checks

常见检查

Is video 4K?
python
metadata['width'] >= 3840 and metadata['height'] >= 2160
Is video HDR?
python
'hdr' in metadata.get('color_space', '').lower()
Is audio stereo?
python
metadata['audio_channels'] == 2
Is codec modern?
python
metadata['video_codec'] in ['h265', 'vp9', 'av1']
视频是否为4K？
python
metadata['width'] >= 3840 and metadata['height'] >= 2160
视频是否为HDR？
python
'hdr' in metadata.get('color_space', '').lower()
音频是否为立体声？
python
metadata['audio_channels'] == 2
编解码器是否为现代格式？
python
metadata['video_codec'] in ['h265', 'vp9', 'av1']

Limitations

局限性

  • Cannot extract corrupt/damaged video metadata
  • Some proprietary formats may have limited support
  • DRM-protected content cannot be analyzed
  • Metadata extraction may be slow for very large files
  • Requires FFmpeg/FFprobe for full codec details
  • 无法提取损坏视频的元数据
  • 部分专有格式可能支持有限
  • 受DRM保护的内容无法分析
  • 超大文件的元数据提取可能较慢
  • 需要FFmpeg/FFprobe才能获取完整的编解码器详情