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Perch-v2
tphakala/Perch-v2
Perch-v2 is a machine learning model from tphakala. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
ONNX format of the Google Perch v2 bird vocalization classifier, repackaged for use with BirdNET-Go.
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Public
Updated Aug 14, 2026
Repo size
822 MB
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.onnx1.9 GB · 100%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- May 10, 2026
- Updated
- Aug 14, 2026
- SHA
- 244a57ef
Base models
Model card
From the Hugging Face model README
Google Perch v2 (ONNX)
ONNX format of the Google Perch v2 bird vocalization classifier, repackaged for use with BirdNET-Go.
Origin and Attribution
The Perch v2 model was developed by Google Research as part of the bird-vocalization-classifier project. It uses an EfficientNet-B3 architecture with approximately 12 million embedding parameters and 91 million classification parameters covering nearly 15,000 species.
The ONNX conversion was performed by justinchuby, who also created an optimized variant with the DFT node converted to MatMul for additional speedup.
The label file originates from the cgeorgiaw/Perch repository on HuggingFace.
Files
| File | Size | Description |
|---|---|---|
perch_v2.onnx | 409 MB | Standard ONNX model (tolerance 1e-5 vs TFLite) |
perch_v2_no_dft.onnx | 413 MB | ONNX with DFT converted to MatMul, faster inference (tolerance 2e-4) |
perch_v2_int8_arm.onnx | 131 MB | MatMul-only dynamic INT8 (arm / low-RAM). ~64% less peak RAM than fp32 (292 MB vs 816 MB on Pi5), ~34% faster, identical top-1 and top-5 vs fp32. Has the DFT front-end, so ONNX Runtime only. |
labels.txt | 313 KB | Species labels (14,795 entries, iNaturalist taxonomy) |
SHA256SUMS | - | Checksums for integrity verification |
Model Information
Input
- Name:
inputs - Shape:
[batch, 160000](5 seconds at 32 kHz) - Type:
float32
Outputs
| Output | Shape | Type | Description |
|---|---|---|---|
embedding | [batch, 1536] | float32 | Audio embedding vector |
spatial_embedding | [batch, 16, 4, 1536] | float32 | Spatial features |
spectrogram | [batch, 500, 128] | float32 | Computed spectrogram |
label | [batch, 14795] | float32 | Species classification logits |
Species Coverage
- Approximately 10,000 bird species
- Frogs, crickets, grasshoppers, and mammals
- Based on training data from Xeno-Canto, iNaturalist, Animal Sound Archive, and FSD50k
Performance (ONNX vs TFLite, 100 runs)
| Metric | ONNX | TFLite |
|---|---|---|
| Mean | 66.4 ms | 608.8 ms |
| Speedup | 9.2x faster | baseline |
License
Apache 2.0, following the original Google Perch license.
Credits
- Google Research for the original Perch v2 model
- justinchuby for the ONNX conversion and DFT-to-MatMul optimization
- cgeorgiaw for the Keras-compatible model and label files
References
- Perch model: Google Bird Vocalization Classifier on Kaggle
- ONNX source: justinchuby/Perch-onnx
- Labels and Keras model: cgeorgiaw/Perch
- Perch codebase: google-research/perch
- License
- apache-2.0
- Created
- May 10, 2026
- Updated
- Aug 14, 2026