Video Tagging and Extraction Scripts

This repository contains two Python scripts for working with a SQLite database (.ritt format) that stores metadata for video files. The scripts allow filtering, extracting, and organizing .mp4 files based on their tags.

Table of Contents

• Scripts Overview
• Installation
• Usage
• Script Details
  • tag_filter_ritt.py
  • extract_videos&tags.py
• Requirements

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Scripts Overview

Script	Purpose
tag_filter_ritt.py	Filters and retrieves .mp4 files based on specific tags in the database.
extract_videos&tags.py	Extracts video-tag relationships and organizes them into categories, saving the results in a CSV file.

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Installation

1. Clone this repository:

   git clone
   cd

2. Install required dependencies:

   pip install -r requirements.txt

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Usage

Running tag_filter_ritt.py:

python tag_filter_ritt.py

This script:

• Connects to the SQLite database (.ritt).
• Filters video files that match a specific set of tags.
• Searches for corresponding .mp4 files in a given directory.
• Prints the matching files and their counts.

Running extract_videos&tags.py:

python extract_videos&tags.py

This script:

• Extracts all videos and their associated tags from the SQLite database.
• Categorizes the extracted tags into predefined families (e.g., shot type, quality, lighting conditions).
• Searches for the corresponding .mp4 files.
• Saves the organized data into a CSV file.

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Script Details

tag_filter_ritt.py

This script is designed to filter video files based on specific tags stored in the SQLite database. It performs the following steps:

1. Connects to the SQLite database and searches for records that match the provided tags.
2. Extracts video file names associated with the matching tags.
3. Searches for .mp4 files in the specified directory.
4. Prints the list of matching files along with the number of times each file appears.

This script is useful when you need to retrieve a subset of videos from a large dataset based on specific filtering criteria.

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extract_videos&tags.py

This script is designed to extract video-tag relationships and save them into a structured CSV file. It performs the following steps:

1. Extracts all videos and their IDs from the SQLite database.
2. Extracts all available tags and associates them with their corresponding videos.
3. Categorizes the extracted tags into predefined families:
   • Camera angle (e.g., orbital, higher, lower)
   • Shot type (e.g., close-up, panoramic)
   • Environment (e.g., indoor, outdoor)
   • Lighting conditions (e.g., backlight, shadows)
   • Quality (e.g., poor, best)
   • Camera movement (e.g., static, dynamic)
   • Density (e.g., low, high)
4. Finds the corresponding .mp4 files in the directory.
5. Saves the results in a CSV file for further analysis.

This script is useful when you need a structured dataset that links videos to their descriptive tags.

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Requirements

• Python 3.x
• SQLite3
• JSON support (built-in)
• CSV support (built-in)
• OS module (built-in)

Ensure that your .ritt database file and .mp4 footage are accessible from the paths specified in the scripts.

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Notes

• If the database file is missing, the scripts will raise an error.
• If any .mp4 file is not found, it will be skipped.
• The CSV output is generated in the script's directory and can be modified to save elsewhere.

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Author

Developed for video metadata processing and automatic tagging.