Instructions to use TheVortexProject/insectnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use TheVortexProject/insectnet with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("TheVortexProject/insectnet", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
| license: cc-by-nc-sa-4.0 | |
| library_name: sklearn | |
| tags: | |
| - bioacoustics | |
| - audio-classification | |
| - birdnet | |
| - edge-ai | |
| - research | |
| - non-commercial | |
| datasets: | |
| - academic-datasets/InsectSet459 | |
| - ESC-50 | |
| # InsectNet v0.1.0 | |
| InsectNet v0.1.0 is a preserved research classifier for scoring insect- and amphibian-related acoustic classes from frozen BirdNET v2.4 output logits. | |
| This Hugging Face repository is the model-release mirror. The canonical source, tests, package, and GitHub Release are at [github.com/vortexpjeff/insectnet](https://github.com/vortexpjeff/insectnet). | |
| This repository intentionally contains one model artifact and one release identity. It does **not** publish live sensor addresses, deployment credentials, exact collection locations, private media, or an unattended capture service. | |
| ## Release identity | |
| ```text | |
| Release: insectnet-v0.1.0 | |
| Artifact: classifier.joblib | |
| SHA-256: 5e6ecfc68d78a2cf2e9e9e47da5cb58d696e8de354fd620cfcccc5db9da48702 | |
| Bytes: 474,892 | |
| Status: historical research reference | |
| ``` | |
| The artifact is byte-for-byte preserved from the original v0.1 field prototype. | |
| ## Model contract | |
| ```text | |
| Audio window: 3.0 seconds | |
| Sample rate: 48,000 Hz mono | |
| Backbone: BirdNET v2.4 FP16 TFLite | |
| Feature space: 6,522 BirdNET output logits | |
| Classifier: StandardScaler → OneVsRest LogisticRegression | |
| Serialization: scikit-learn 1.8.0 | |
| Output semantics: independent per-class probabilities | |
| ``` | |
| Class order: | |
| 1. `background` | |
| 2. `bee` | |
| 3. `cicada_drone` | |
| 4. `cricket_katydid` | |
| 5. `frog` | |
| 6. `grasshopper` | |
| The model file does not embed thresholds, a version number, or its original training snapshot. Those omissions are part of the preserved v0.1 record rather than silently reconstructed metadata. | |
| ## What is included | |
| - the exact v0.1 model artifact; | |
| - a machine-readable release manifest; | |
| - artifact and feature-contract verification; | |
| - offline scoring for precomputed BirdNET logit vectors; | |
| - tests that enforce the model checksum, class order, feature dimension, and public privacy boundary; | |
| - documented provenance and limitations. | |
| ## What is not included | |
| - live capture or sensor-watching code; | |
| - deployment scripts; | |
| - device addresses or credentials; | |
| - exact collection locations; | |
| - raw or private field audio; | |
| - later experimental model candidates; | |
| - claims of production readiness. | |
| The original live sidecar diverged from the public v0.1 source during field experiments. That runtime is not republished here until it can be recovered, tested, and released under a separate reviewed version. | |
| ## Verify the preserved artifact | |
| From a source checkout: | |
| ```bash | |
| uv run insectnet verify | |
| ``` | |
| Expected SHA-256: | |
| ```text | |
| 5e6ecfc68d78a2cf2e9e9e47da5cb58d696e8de354fd620cfcccc5db9da48702 | |
| ``` | |
| ## Score precomputed logits | |
| InsectNet v0.1 expects one finite NumPy vector with shape `(6522,)` extracted from the declared BirdNET backbone: | |
| ```bash | |
| uv run insectnet score logits.npy | |
| ``` | |
| The command returns one probability per declared class. These scores are model assertions for review, not confirmed biological observations. | |
| > **Joblib safety:** joblib artifacts use Python pickle internally. Load only the artifact whose checksum matches the release manifest. | |
| ## Known limitations | |
| - Later audits found high false-positive rates on some bird vocalizations. | |
| - Bee and grasshopper had limited training coverage. | |
| - The surviving metrics came from limited public-data evaluation and one private field site; they do not establish general production performance. | |
| - Exact reproduction is blocked because the original per-record training snapshot is unavailable. | |
| - The classifier relies on BirdNET logits and cannot score raw audio by itself. | |
| - There is no validated automated-decision threshold policy in this release. | |
| ## Provenance | |
| The surviving records identify these source families: | |
| - **InsectSet459:** current dataset card states CC BY 4.0, with some source material CC0. | |
| - **ESC-50:** CC BY-NC 3.0. | |
| - **iNaturalist audio:** licenses vary per recording; the original per-record manifest is unavailable. | |
| - **Private field negatives:** not redistributed. | |
| See [`PROVENANCE.md`](PROVENANCE.md) and the release manifest for the exact surviving claims and gaps. | |
| ## Privacy and security | |
| The public release intentionally omits exact collection location, network topology, account names, credentials, private paths, and raw evidence. See [`SECURITY_AND_PRIVACY.md`](SECURITY_AND_PRIVACY.md). | |
| ## License | |
| The repository and preserved release are distributed under CC BY-NC-SA 4.0, subject to the licenses and terms of the upstream backbone and source media. Source-media rights vary; users are responsible for reviewing those upstream terms for their use case. | |
| This provenance statement is not legal advice. | |