Analyze video/image with machine learning methods, exif data, and other file based information.
Project description
Media Analyzer
Media Analyzer is a Python library designed to analyze media files, providing insights into their content and metadata. It supports various functionalities, including image classification, captioning, optical character recognition (OCR), and facial recognition.
Features
- GPS: Gather GPS coordinates from exif, and reverse geocode to get the country, province and city.
- Exif: Extract exif data/metadata from photos, videos, gifs, etc.
- Weather: Get weather info at the time the photo/video was taken.
- temperature
- dewpoint
- relative humidity
- precipitation
- wind gust
- pressure
- sun hours
- condition
- Quality Detection: Detect objectively measurable quality of images:
- Sharpness
- Noise
- Exposure
- Dynamic range
- Color clipping (white/black levels)
- A composite score is generated, so photos can be ranked by quality.
- Image Classification: Identify objects, scene type, activities, animals, and events present in images.
- Image Captioning: Generate descriptive captions for images using models like BLIP or LLM-based captioners.
- Embedding: Generate clip embeddings for images and text. Can be used to cluster images or search semantically through images.
- Optical Character Recognition (OCR): Extract text from images to identify documents, receipts, menus, and more.
- LLM: Get detailed image summary, more indepth than just a caption, using an LLM. Can also be used to generate a summary of a document shown in a photo or video.
- Facial Recognition: Detect faces in images and provide details such as age, sex, bounding box, and facial landmarks. Includes an embedding of the face, which can be used for clustering.
- Datetime Taken: Photo and video files are messy and have unreliable datetime tags. This packages uses six different methods with varying priority to get the datetime a photo is taken, including the timezone if possible.
- Data Url: Generate data url for tiny preload thumbnail.
Installation
To install Media Analyzer, use pip:
pip install media-analyzer
Requirements
You must have the following in PATH.
- ExifTool: https://exiftool.org/
- Tesseract OCR: https://tesseract-ocr.github.io/tessdoc/Installation.html
Examples
Example output of the main analyze function can be viewed at example_output.json. Further example code is available at /examples.
Usage
Here's a basic example of how to use Media Analyzer:
from media_analyzer import MediaAnalyzer
from pathlib import Path
analyzer = MediaAnalyzer()
media_file = Path("image.jpg")
result = analyzer.photo(media_file)
print(result)
Disable analysis modules
The analysis is done based on modules, the following modules are available and enabled by default:
File-based Modules:
"DataUrlModule""ExifModule""GPSModule""TimeModule""WeatherModule"
Visual Modules:
"CaptionModule""ClassificationModule""EmbeddingModule""FacesModule""ObjectsModule""OCRModule""QualityDetectionModule""SummaryModule"
Modules can be turned off by changing the config provided to the MediaAnalyzer class:
from media_analyzer import MediaAnalyzer, AnalyzerSettings, FileModule, VisualModule
from pathlib import Path
config = AnalyzerSettings(
enabled_file_modules={FileModule.EXIF}, # Only do exif data analysis on file
enabled_visual_modules={VisualModule.CAPTION}, # Only do caption module as visual module
)
analyzer = MediaAnalyzer(config=config)
media_file = Path(__file__).parents[1] / "tests/assets/tent.jpg"
result = analyzer.photo(media_file)
Configuration
The AnalyzerSettings class allows you to customize various aspects of the analysis:
media_languages: List of languages for OCR to consider.
captions_provider: The provider for image captioning (e.g., 'BLIP', 'LLM').
enable_text_summary: Enable or disable text summarization.
enable_document_summary: Enable or disable document summarization.
document_detection_threshold: Confidence threshold for document detection.
face_detection_threshold: Confidence threshold for face detection.
enabled_file_modules: List of file modules to enable (e.g., exif data, gps, weather detection).
enabled_visual_modules: List of visual modules to enable (e.g., 'classification', 'captioning', 'ocr', 'facial_recognition').
Full docs can be found at https://ruurdbijlsma.github.io/media-analyzer.
Attribution
- Meteostat for weather info: https://dev.meteostat.net/python/
- Reverse geocoding data from geonames: https://download.geonames.org/
- ExifTool for exif and similar data: https://exiftool.org/
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