Semantixel

Semantixel is an advanced semantic media retrieval system for local and connected image sources. It seamlessly indexes visual content using CLIP embeddings, extracts on-image text via OCR, and exposes robust search workflows for text-to-image, image-to-image, and OCR-backed retrieval through a lightweight web interface.

The project is tailored for personal knowledge bases, research datasets, screenshot archives, and comprehensive media collections where traditional keyword search is insufficient.

Watch Demo Video

Features

• Natural-Language Image Retrieval: Leverage CLIP text and image embeddings for intuitive search.
• Visual Similarity Search: Find related images efficiently from a reference image.
• OCR-Assisted Retrieval: Search through screenshots, documents, and images containing text.
• Video Frame Extraction and Indexing: Enable semantic search across video assets by analyzing extracted frames.
• Multi-Source Media Support: Utilize source-aware media identifiers for robust indexing.
• Google Drive Integration: Authenticate via OAuth to seamlessly index and serve cloud-based images.
• Interactive Web Interface: Browse results, preview media, and explore relationships in an intuitive graph-based view.
• Configurable Indexing Behavior: Customize settings effortlessly through the desktop application.

How It Works

High-Level Workflow

Semantixel integrates three distinct retrieval strategies:

• Visual Retrieval: Embeds image and text queries into a shared CLIP space.
• OCR Retrieval: Extracts and indexes text from images for semantic and BM25 search.
• Metadata-Aware Serving: Resolves indexed items via source-aware media identifiers instead of relying purely on local file paths.

At a high level:

1. Media is discovered from configured local directories and connected sources.
2. Images and extracted video frames are embedded utilizing CLIP.
3. OCR text is extracted and stored for both semantic and BM25 search mechanisms.
4. Embeddings and metadata are managed within ChromaDB and the BM25 index.
5. The REST API serves search results and media content directly to the web UI.

Requirements

• Python 3.11
• CUDA-capable GPU (Recommended for optimal indexing and search performance)
• Conda or an alternative Python environment manager

Installation and Setup

Environment Setup

Create and activate a new environment:

conda create -n semantixel python=3.11 -y
conda activate semantixel
pip install -r requirements.txt

Application Configuration

Launch the settings utility:

python settings.py

Execution

Run a full local scan to index your files:

python main.py --scan

Start the application server:

python main.py --serve

Alternatively, execute the default combined workflow:

python main.py

Configuration Options

Runtime configuration is maintained in config.yaml. Key settings include:

• include_directories: Local directories to scan.
• exclude_directories: Local directories to ignore.
• batch_size: The number of items processed per indexing batch.
• clip: Configuration for the CLIP provider and model checkpoints.
• text_embed: Settings for the text embedding provider.
• ocr_provider: Selection of the OCR backend.
• google_drive: Configuration for Google Drive integration.

Google Drive Integration

Semantixel natively supports indexing and serving images directly from Google Drive.

Example Configuration:

google_drive:
  enabled: true
  client_secret_file: path/to/client_secret.json
  token_file: google_drive_token.json
  redirect_uri: http://localhost:23107/integrations/google_drive/auth/callback
  folder_ids: []
  include_shared_drives: false
  page_size: 100

Integration Steps:

1. Create a Google Cloud OAuth client of type Web application.
2. Set the redirect URI to http://localhost:23107/integrations/google_drive/auth/callback.
3. Download the client secret JSON file.
4. Update config.yaml accordingly.
5. Start the application and authenticate via Connect Google Drive in the web UI.
6. Run python main.py --scan to commence indexing Drive images.

Note: OAuth secrets and token files must remain secure and excluded from version control.

Search Modalities

Semantixel supports comprehensive search capabilities:

• Caption Search: Retrieve images or video frames using natural language descriptions.
• Similar Image Search: Discover visually related images starting from a reference image or identifier.
• Text Content Search: Locate images based on OCR-detected text.
• Graph Exploration: Analyze and inspect similarity relationships between indexed assets.

Sample Use Cases

• Query a screenshot archive using natural language such as "dashboard with a warning banner" or "terminal output showing build failure".
• Locate visually similar product photography, design mockups, or duplicate assets across a large catalog.
• Identify images containing specific OCR-detected phrases like invoice numbers, application labels, or error messages.
• Navigate significant segments within video files by retrieving semantically relevant extracted frames.
• Establish a unified knowledge base combining local storage with cloud-hosted libraries.

Repository Structure

Key directories:

• semantixel/: Core backend services, API endpoints, providers, and source integrations.
• settings/: Desktop configuration interface.
• UI/: Web interface and Flow Launcher integrations.
• docs/: Technical documentation and system design notes.
• db/: ChromaDB and BM25 artifacts generated during runtime.

Security Overview

• Local media access is strictly confined to configured inclusion directories.
• External URLs are rigorously validated prior to ingestion for image queries.
• Google Drive access is securely delegated via OAuth 2.0 API calls.
• Security credentials and tokens must remain local and ignored by Git.