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Analyze video/image with machine learning methods, exif data, and other file based information.

Project description

from media_analyzer.data.enums.analyzer_module import VisualModulefrom media_analyzer.data.enums.analyzer_module import FileModule

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.

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.

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