How to use from the
Use from the
Scikit-learn library
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

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 repository preserves one canonical v0.1 release identity and also carries separately versioned Perch 2 research candidates. It does not publish live sensor addresses, deployment credentials, exact collection locations, private media, or an unattended capture service.

Public discovery and versioned downloads are organized in the The Vortex Project — Multi-Taxa Bioacoustics Hugging Face collection. GitHub remains the source, tests, and release-engineering surface.

Release identity

Release:  insectnet-v0.1.0
Artifact: src/insectnet/data/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

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;
  • claims of production readiness.

The original v0.1 live sidecar diverged from this public source during early field experiments and is not a current deployment target. It has been superseded operationally by the separately versioned Perch 2 specialist architecture; the preserved v0.1 artifact remains a historical BirdNET-logit reference.

Verify the preserved artifact

From a source checkout:

uv run insectnet verify

Expected SHA-256:

5e6ecfc68d78a2cf2e9e9e47da5cb58d696e8de354fd620cfcccc5db9da48702

Score precomputed logits

InsectNet v0.1 expects one finite NumPy vector with shape (6522,) extracted from the declared BirdNET backbone:

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.

Perch 2 research artifacts and field heads

Three provenance-locked specialist lines were trained and audited in July 2026. None replaces the preserved BirdNET-logit v0.1 artifact. Each line has an explicit public research boundary and a separate operational status. FrogNet's public mirror contains the exact checked JSON/NPZ bundle used by its private review-only field head; the public InsectNet and ChickenNet research artifacts must not be conflated with later private field bundles.

Candidate Status Key external result
ChickenNet Research 0.1.0 frozen public joblib not deployed; later private JSON/NPZ successor operates as a review-only field head 33/42 broad-head hits on a locked iNaturalist chicken challenge; 10/1,308 candidate activations on a private local confound set
InsectNet Research 0.2.0 frozen public joblib not deployed; later private JSON/NPZ successor operates as a review-only field head 11/26 broad activations on an untouched iNaturalist dog challenge
FrogNet Research 0.1.0 public noncommercial research artifact; exact strict bundle deployed privately for review 1,253/1,308 local frog-window activations and 0/3,781 tested confound activations at threshold 0.95

All three lines consume 1,536-dimensional Google Perch 2 embeddings from five-second, 32 kHz mono windows. They include exact model/data hashes, grouped split reports, hierarchy contracts, source summaries, and challenge reports. They do not include Perch weights or source audio.

Training strategy

docs/PERCH2_TRAINING_STRATEGY.md records the provenance-first design used for the Perch 2 specialist heads. The current FrogNet research and operational contract is frozen in docs/FROGNET_FIELD_PROBE.md. The dated architecture and artifact-versus-runtime boundary for all three living heads is recorded in docs/LIVING_DEPLOYMENT.md.

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 docs/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 docs/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.

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