SentrySearch: Semantic Video Search with AI
SentrySearch: Revolutionize Video Footage Analysis with Semantic Search
Finding specific moments in hours of video footage just got dramatically easier. SentrySearch is an open-source Python tool that uses cutting-edge video embedding models to make your videos searchable by natural language queries.
How It Works (Pure Magic)
Instead of manually scrubbing through footage, SentrySearch: 1. Chunks your videos into overlapping 30-second segments 2. Embeds each chunk using Google's Gemini Embedding API or local Qwen3-VL models 3. Stores embeddings in a local ChromaDB vector database 4. Matches your text query ("car running red light") against video embeddings 5. Automatically trims and saves the best matching clip
No transcription. No frame captioning. Direct video-to-text semantic matching.
π Quick Start (5 Minutes)
# Install with uv (fastest package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh
git clone https://github.com/ssrajadh/sentrysearch.git
cd sentrysearch
uv tool install .
# Setup API key (free tier available)
sentrysearch init
# Index your footage
sentrysearch index /path/to/videos
# Search and get clips!
sentrysearch search "red truck running stop sign"
Result: ./match_front_2024-01-15_14-30_02m15s-02m45s.mp4 β
π Two Backends: Cloud or Local
| Backend | Pros | Cons | Cost |
|---|---|---|---|
| Gemini API (default) | Best quality, no GPU needed | Requires API key | ~$2.84/hour indexed |
| Local Qwen3-VL | Free, private, offline | Needs GPU/M1+ Mac | Free |
Local model auto-scales to your hardware: - NVIDIA 18GB+ VRAM: Qwen8B (full precision) - 8-16GB VRAM: 4-bit quantized (~6GB) - M1/M2 Mac 16GB+: Qwen2B (~6GB)
Tesla Dashcam Superpowers
Got Tesla Sentry Mode footage? SentrySearch extracts embedded telemetry and burns HUD overlays:

sentrysearch search "car cutting me off" --overlay
Shows speed, GPS location, timestamp, even reverse-geocoded street names.
π° Cost Optimization
- Still-frame skipping: Skips parked car footage automatically
- Preprocessing: 95% size reduction (480p@5fps chunks)
- Tunable chunks:
--chunk-duration 60 --overlap 5halves API costs
1 hour indexing = ~$2.84 (3,600 frames Γ $0.00079)
π οΈ Pro Features
# Save top 5 matches
sentrysearch search "pedestrian" --save-top 5
# Custom confidence threshold
sentrysearch search "event" --threshold 0.7
# Manage index
sentrysearch stats
sentrysearch remove old_footage/
sentrysearch reset
π― Use Cases
- Tesla owners: Analyze Sentry Mode incidents
- Security teams: Search surveillance footage
- Content creators: Find specific clips in raw footage
- Researchers: Query behavioral patterns in video datasets
- Anyone with dashcam/action cam footage
π¦ Works With
β MP4, MOV files β Tesla firmware 2025.44.25+ (HW3+) β Regular dashcams, phone videos, security cams β Python 3.11+, ffmpeg (auto-bundled)
π Why SentrySearch Wins
- 2.6K GitHub stars, battle-tested
- MIT licensed, production-ready
- Sub-second search even on hours of footage
- Dual backend (cloud + local)
- Automatic trimming, no post-processing
- Cost-aware optimizations built-in
Stop fast-forwarding through footage. Start searching.