{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"},{"label":"Visualization","url":"https://skillfed.io/packages/category/scientific-engineering-visualization"},{"label":"Image Recognition","url":"https://skillfed.io/packages/category/scientific-engineering-image-recognition"},{"label":"Image Processing","url":"https://skillfed.io/packages/category/scientific-engineering-image-processing"}],"enrichment":{"capability":"ETA is an extensible computer vision and machine learning analytics toolkit that provides core utilities for working with images, videos, embeddings, and ML inference pipelines, along with a CLI for building and running analytics workflows.","skillfed_tags":["computer-vision","ml-pipelines","video-analytics"],"use_cases":["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."],"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\u2014classifiers, detectors, models, and pipelines\u2014and exposes a command-line interface for building and running analytics workflows without writing code.\n\nThe 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.","worth_installing":"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)."},"id":"voxel51-eta","links":{"html":"https://skillfed.io/packages/voxel51-eta","md":"https://skillfed.io/packages/voxel51-eta.md","pypi":"https://pypi.org/project/voxel51-eta/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":null,"license_treatment":"permissive","name":"voxel51-eta","python_support":"supports_current","summary":"Extensible Toolkit for Analytics"},"popularity":{"monthly_downloads":187461,"position":9963,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.17.0"}