{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"},{"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":"FiftyOne is a Python framework for building, visualizing, and evaluating computer vision datasets and models, with integrated labeling, model evaluation, and data quality tools.","skillfed_tags":["computer-vision","dataset-management","model-evaluation"],"use_cases":["Visualize and explore large image or video datasets to understand data distribution and identify labeling errors before training.","Annotate and curate datasets collaboratively, with built-in tools for tagging, filtering, and organizing samples.","Evaluate model predictions on test sets, compare multiple models, and identify failure modes or systematic biases.","Debug model performance by correlating prediction errors with dataset characteristics and metadata.","Manage dataset versioning and track changes across annotation rounds and model iterations."],"what_it_does":"FiftyOne is an open-source Python framework designed to streamline the entire computer vision workflow\u2014from dataset curation and annotation through model evaluation and iteration. It provides integrated tools for visualizing image and video data, labeling datasets collaboratively, evaluating model predictions, and identifying data quality issues. The framework sits between raw datasets and model training pipelines, helping teams understand their data and debug model behavior more efficiently than manual inspection.\n\nThe package is built on a substantial dependency stack including MongoDB for data persistence, async I/O libraries for concurrent operations, and visualization tools like Plotly. It supports Python 3.10\u20133.13 and runs on Linux, macOS, and Windows. While the open-source version is suitable for individual and team workflows, the project also offers an enterprise variant for production-scale, cloud-native deployments.","worth_installing":"Yes. FiftyOne is actively maintained, has no known vulnerabilities, and offers low install friction. It is well-suited for teams building computer vision systems who need integrated dataset management and model evaluation. The permissive Apache license and broad platform support (Python 3.10\u20133.13, Linux/macOS/Windows) make it accessible. The large dependency footprint and MongoDB requirement are manageable trade-offs for the functionality gained. Install if you are working with image or video datasets and need visualization, labeling, and evaluation tools in a single framework."},"id":"fiftyone","links":{"html":"https://skillfed.io/packages/fiftyone","md":"https://skillfed.io/packages/fiftyone.md","pypi":"https://pypi.org/project/fiftyone/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-05","license_spdx":null,"license_treatment":"permissive","name":"fiftyone","python_support":"supports_current","summary":"FiftyOne: the open-source tool for building high-quality datasets and computer vision models"},"popularity":{"monthly_downloads":254545,"position":8493,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.20.1"}