| name | video-metadata-inspector |
| description | Use when asked to inspect video file metadata, get video duration, resolution, codec information, frame rate, or bitrate. |
Video Metadata Inspector
Extract and analyze comprehensive metadata from video files including duration, resolution, codec, frame rate, and technical specifications.
Purpose
Video metadata inspection for:
- Format verification and compatibility checking
- Quality assessment and validation
- Transcoding planning and optimization
- Video library cataloging
- Technical specification reports
Features
- 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
Quick Start
from video_metadata_inspector import VideoMetadataInspector
# 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']}")
# Export full report
inspector.export_report('report.json', format='json')
# Batch inspect directory
inspector.batch_inspect(
input_files=['video1.mp4', 'video2.mkv'],
output='metadata.csv',
format='csv'
)
CLI Usage
# Basic metadata
python video_metadata_inspector.py input.mp4
# Full technical details
python video_metadata_inspector.py input.mp4 --verbose
# Export to JSON
python video_metadata_inspector.py input.mp4 --output metadata.json --format json
# Batch inspect directory
python video_metadata_inspector.py *.mp4 --output metadata.csv --format csv
# Compare multiple videos
python video_metadata_inspector.py video1.mp4 video2.mp4 --compare
API Reference
VideoMetadataInspector
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
Basic Information
- Duration (seconds, formatted)
- Resolution (width × height)
- Frame rate (FPS)
- File size
- Aspect ratio
Video Stream
- Video codec (H.264, H.265, VP9, etc.)
- Codec profile and level
- Bitrate (kbps)
- Pixel format (yuv420p, etc.)
- Color space and range
Audio Stream
- Audio codec (AAC, MP3, Opus, etc.)
- Sample rate (Hz)
- Channels (mono, stereo, 5.1, etc.)
- Audio bitrate (kbps)
Container Format
- Container type (MP4, MKV, AVI, etc.)
- Creation date
- Metadata tags (title, artist, description)
- Number of streams
Use Cases
Format Verification:
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:
# Check if transcoding needed
metadata = inspector.get_metadata()
if metadata['video_codec'] != 'h265' or metadata['bitrate_kbps'] > 5000:
print("Transcode recommended")
Quality Assessment:
# 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
)
Common Checks
Is video 4K?
metadata['width'] >= 3840 and metadata['height'] >= 2160
Is video HDR?
'hdr' in metadata.get('color_space', '').lower()
Is audio stereo?
metadata['audio_channels'] == 2
Is codec modern?
metadata['video_codec'] in ['h265', 'vp9', 'av1']
Limitations
- 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