sparrow-engine (Python)
Camera-trap ML inference engine — Python API. sparrow-engine loads ONNX
models and runs detection, classification, and audio inference.
This package ships the Python API only (import sparrow_engine). The
command-line binaries (spe / spe-gpu) and the HTTP server are distributed
separately (Homebrew, the system installer, or the GitHub Release tarball) —
pip install does not place them on your PATH.
Install
pip install sparrow-engine # CPU build (depends on onnxruntime)
pip install sparrow-engine-gpu # GPU/CUDA build (depends on onnxruntime-gpu)
Both distributions import as sparrow_engine and are drop-in replacements for
each other. Install exactly one per environment; pip refuses to install both
into the same environment. Neither wheel bundles ONNX Runtime or CUDA — those
come from the runtime dependency (onnxruntime / onnxruntime-gpu).
Usage
import sparrow_engine
# Models are read from ~/.sparrow-engine/models (override with
# SPARROW_ENGINE_MODEL_DIR). Device defaults to "auto".
print(sparrow_engine.list_models())
# Object detection — returns list[DetectResult], one per input image.
results = sparrow_engine.detect("photo.jpg", model="MDV6-yolov10-c")
for det in results[0].detections:
# bbox coordinates are normalized to [0, 1].
print(det.label, det.confidence, det.bbox.x_min, det.bbox.y_min)
# Classification — result.top1 is the highest-confidence class (or None).
clf = sparrow_engine.classify("crop.jpg", model="Deepfaune-Europe")
print(clf[0].top1)
# Detect-then-classify pipeline (ad-hoc; no TOML required).
pipe = sparrow_engine.pipeline("photo.jpg", detector="MDV6-yolov10-c",
classifier="Deepfaune-Europe")
# Audio detection (WAV input).
audio = sparrow_engine.detect_audio("recording.wav", model="md-audiobirds-v1")
init(device=..., model_dir=...) is optional — the engine auto-initializes on
the first inference call. detect / classify / detect_audio / pipeline
each accept a file path, a directory, or a list of paths, and take an optional
progress_callback(index, total, filename).
Documentation
See the user manual (docs/user-manual.md) in the sparrow-engine repository for
the full model catalog, device selection, and the CLI / server surfaces.
1 maintainer
Metadata
1 maintainer
Release files for sparrow-engine 0.1.28
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sparrow_engine-0.1.28-cp311-abi3-win_amd64.whl | CPython 3.11 | abi3 | Windows x86-64 | Details |
| sparrow_engine-0.1.28-cp311-abi3-manylinux_2_28_x86_64.whl | CPython 3.11 | abi3 | Linux glibc 2.28+ x86-64 | Details |
| sparrow_engine-0.1.28-cp311-abi3-macosx_11_0_arm64.whl | CPython 3.11 | abi3 | macOS 11.0+ ARM64 | Details |
Total release size: 6.9 MB
Release files / sparrow_engine-0.1.28-cp311-abi3-win_amd64.whl
| Download URL | sparrow_engine-0.1.28-cp311-abi3-win_amd64.whl |
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| Size | 2.2 MB |
| Tags | CPython 3.11 Windows x86-64 abi3 |
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| Download URL | sparrow_engine-0.1.28-cp311-abi3-manylinux_2_28_x86_64.whl |
|---|---|
| Size | 2.6 MB |
| Tags | CPython 3.11 Linux glibc 2.28+ x86-64 abi3 |
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| Download URL | sparrow_engine-0.1.28-cp311-abi3-macosx_11_0_arm64.whl |
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| Size | 2.2 MB |
| Tags | CPython 3.11 abi3 macOS 11.0+ ARM64 |
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