voxel51-eta
Extensible Toolkit for Analytics
Decision gist · record as of 2026-08-14
Yes. ETA is actively maintained (release 4 days old), has low install friction, and is permissively licensed. It fills a genuine need for a modular, extensible analytics framework rather than a monolithic library. The 20 runtime dependencies are standard (numpy, opencv, scikit-image, Pillow) and well-maintained. No known security vulnerabilities. Best suited for teams building custom computer vision or ML analytics workflows; less ideal if you only need a single, narrow task (e.g., image resizing).AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Advanced features (pipelines, model management) require a properly configured eta/config.json file.
- Optional dependencies like ffmpeg or TensorFlow must be installed separately if needed.
License · maintenance · safety
Apache (permissive) — Apache License (permissive) means you can use, modify, and distribute ETA freely in commercial and private projects, provided you include a copy of the license and note any changes you make.
last release 2026-08-10 (4 days) · last repo commit 2026-08-13 · 37 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 187,461 downloads/mo, #9,963 on PyPI
Alternatives
Verify before relying
pip install voxel51-eta
import eta.core
# Create a copy of config-example.json as eta/config.json to enable advanced features
# Then use eta CLI or import eta.core submodules for image/video utilities- Whether the 20 runtime dependencies are all required for a minimal installation or if some are optional/conditional.
- Specific performance characteristics or scalability limits for large video or image datasets.
- Compatibility details between ETA and different TensorFlow versions (1.X vs 2.X) in practice.
- Whether the CLI is fully functional immediately after pip install or requires additional setup beyond config.json.
What it is and what it does
ETA is an open-source analytics infrastructure for computer vision and machine learning workflows. It provides a core library (eta.core) with utilities for image, video, and embedding manipulation, plus higher-level modules for inference with classifiers and detectors. The package is organized into submodules for different tasks—classifiers, detectors, models, and pipelines—and exposes a command-line interface for building and running analytics workflows without writing code.
The toolkit is designed to be portable across Mac, Linux, and Windows, and supports both CPU and GPU setups. It works with TensorFlow 1.X and 2.X and includes a model registry (manifest.json) that downloads pre-trained models on demand. Installation is lightweight by default (lite mode), with optional dependencies installed on first use. Configuration is managed through a JSON file that lets you customize paths, environment variables, and module search directories.
Use it for
- Build video processing pipelines that apply classifiers or object detectors to frame sequences without writing custom inference code.
- Manage and download pre-trained ML models from ETA's registry and run inference on images or video frames.
- Extract and manipulate image embeddings, metadata, and annotations for downstream ML tasks.
- Automate computer vision workflows via the CLI for batch processing, model evaluation, or remote storage integration.
- Extend ETA with custom modules, pipelines, or models by registering them in the config and module search paths.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
ETA is actively maintained (release 4 days old), has low install friction, and is permissively licensed. It fills a genuine need for a modular, extensible analytics framework rather than a monolithic library. The 20 runtime dependencies are standard (numpy, opencv, scikit-image, Pillow) and well-maintained. No known security vulnerabilities. Best suited for teams building custom computer vision or ML analytics workflows; less ideal if you only need a single, narrow task (e.g., image resizing).
Install
voxel51-eta on PyPI
Before you install
Low friction installation via pip with a pure-Python wheel. Active maintenance with a release 4 days old. The package pulls in 20 runtime dependencies including numpy, opencv-python-headless, and scikit-image; optional features like ffmpeg and TensorFlow are prompted on demand rather than bundled.
Requires Python 3.10 or later. Advanced features (pipelines, model management) require a properly configured eta/config.json file. Optional dependencies like ffmpeg or TensorFlow must be installed separately if needed.
License in practice
Apache License (permissive) means you can use, modify, and distribute ETA freely in commercial and private projects, provided you include a copy of the license and note any changes you make.
Quickstart
pip install voxel51-eta
import eta.core
# Create a copy of config-example.json as eta/config.json to enable advanced features
# Then use eta CLI or import eta.core submodules for image/video utilitiesVerify before relying
- Whether the 20 runtime dependencies are all required for a minimal installation or if some are optional/conditional.
- Specific performance characteristics or scalability limits for large video or image datasets.
- Compatibility details between ETA and different TensorFlow versions (1.X vs 2.X) in practice.
- Whether the CLI is fully functional immediately after pip install or requires additional setup beyond config.json.
Package facts
| License | Apache permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 20 packagesargcompletedillglob2jsonlinesnumpyopencv-python-headlesspackagingparamikoPillowpy7zrpython-dateutilpytzrarfilerequestsretryingscikit-imagesortedcontainerstabulatetzlocalurllib3 |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 187,461 / month, #9,963 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Scientific/Engineering :: Image ProcessingTopic :: Scientific/Engineering :: Image RecognitionTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: Visualization |
Evidence: voxel51_eta-0.17.0-py3-none-any.whl
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