biodex 1.0.2

Local, privacy-first AI for wildlife camera trap analysis and conservation monitoring

BioDex

Local AI for wildlife camera traps. Detect animals, filter blanks, identify species, export results — on your machine, not in the cloud.

Built for conservation research, field review, and defensive wildlife monitoring (Fratres / EcoSentinel integration hooks).

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Install from PyPI (recommended)

Step 1 — base package + UI (fast, stable):

pip install biodex
pip install "biodex[ui,video,analytics]" --prefer-binary

Step 2 — inference models (heavy; install after step 1):

pip install protobuf==3.20.1
pip install "biodex[heavy]" --prefer-binary

Then run the UI: biodex-ui → http://127.0.0.1:7860

Windows: always pass --prefer-binary on the heavy step to avoid slow or failed source builds (cmake, onnx compile errors).

Do not use pip install "biodex[all]" as your first install. [all] is a conservative bundle (UI + video + analytics + dev tools) and does not include MegaDetector/SpeciesNet. For the full stack: [ui,video,analytics] + [heavy].

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Run locally (do this)

Mac / Linux

git clone https://github.com/FratresMedAI/BioDex.git
cd BioDex
./run_biodex.sh

Windows

git clone https://github.com/FratresMedAI/BioDex.git
cd BioDex
run_biodex.bat

Your browser opens http://127.0.0.1:7860. Use the Batch tab to process a folder, or Quick demo for a fast preview.

First analysis downloads models once (~500 MB). After that, everything stays offline on your computer.

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v1.0 highlights

• Pluggable models — registry architecture (core/models/) with MegaDetector + SpeciesNet adapters
• Batch performance — chunking, cancel, ETA progress, optional torch.compile
• Video foundations — frame sampling + timeline export (biodex video, requires [video] extra)
• Advanced exports — Wildlife Insights, iNaturalist drafts, timelapse JSON, SQLite, EcoSentinel hook
• Tabbed UI — Dashboard, Batch, Video, Analytics, Settings
• Optional AI review (BYOK) — per-frame LLM notes after batch runs (see below)
• Docker — CPU and GPU images for deployment
• Release maturity — stable API surface, strict typing/linting, and CI-gated quality

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Optional AI review (BYOK)

Core detection runs fully offline on your machine. AI review is an optional power feature:

1. Open Use via API in the footer.
2. Choose a provider, paste your API key, pick a model (or type a custom model ID), then Save.
3. After a batch run, select a frame and click AI review (LLM) for a field note: scene summary, species second opinion, and data-quality flags.

Privacy: API keys are stored locally in ~/.cache/biodex/settings.json and sent only to the provider you choose — never to BioDex servers. See SECURITY.md.

Scope in v1.0.1: batch frame review only. Single-image spot check, video key frames, and batch-level summaries are planned for v1.1. Not every model slug in the dropdown is guaranteed to work with every provider — use a custom model ID if needed.

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Extras install matrix

Extra	What it installs	When to use
ui	Gradio web UI	Default — always
heavy / models	MegaDetector, SpeciesNet, PyTorch, protobuf pin	After ui; required for detection
video	OpenCV (headless, wheel-pinned)	Video tab / biodex video
analytics	matplotlib, seaborn	Analytics tab heatmaps
edge	onnxruntime stubs	Experimental edge deploy
dev	pytest, ruff, mypy	Contributors
all	ui + video + analytics + dev + desktop + edge	No inference stack — not a one-shot full install

From source (git clone): use run_biodex.bat / run_biodex.sh — they run scripts/install_biodex.*, which installs the heavy stack in a protobuf-safe order.

pip install -e ".[ui,heavy]" --prefer-binary    # after scripts/install_biodex.sh, or manual protobuf pin
pip install -e ".[video,analytics]" --prefer-binary

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Installation troubleshooting

Clean install (upgrading from 0.5.0 or fixing a broken env)

pip uninstall biodex megadetector speciesnet onnx onnx2torch -y
pip cache purge
pip install biodex
pip install "biodex[ui,video,analytics]" --prefer-binary
pip install protobuf==3.20.1
pip install "biodex[heavy]" --prefer-binary

On Windows, use a fresh virtual environment when possible:

python -m venv .venv
.venv\Scripts\activate

cmake / onnx build errors on Windows

SpeciesNet pulls onnx transitively. If pip tries to build from source:

1. Use --prefer-binary on every BioDex extra install.
2. Pin protobuf first: pip install protobuf==3.20.1
3. Install [heavy] in a separate command after [ui].
4. If it still fails, clone the repo and use run_biodex.bat (uses the ordered install script).

Slow dependency resolution

Avoid biodex[all,heavy] in one command on Windows. Install in the two-step order above.

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Batch CLI

For large folders (100+ images), no browser:

biodex batch /path/to/images -o ./results --classify-species --recursive
biodex batch /path/to/images -o ./results --chunk-size 500 --torch-compile
biodex video /path/to/clip.mp4 -o ./video-results --fps 1 --max-frames 120

Environment variables: BIODEX_DETECTOR_MODEL, BIODEX_TORCH_COMPILE, BIODEX_GEOFENCE_REGION, BIODEX_AUDIT_LOG=1

Docker quick start

docker build -t biodex:cpu -f Dockerfile .
docker run --rm -p 7860:7860 biodex:cpu

GPU:

docker build -t biodex:gpu -f Dockerfile.gpu .

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Developers

pip install -e ".[ui,models,dev]"
pytest tests/ -v -m "not slow"
ruff check core app.py ui
mypy core app.py ui
pre-commit install   # optional

See CHANGELOG.md, docs/roadmap.md, CONTRIBUTING.md, and SECURITY.md.

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MIT License. Uses MegaDetector and SpeciesNet.