{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"}],"enrichment":{"capability":"Provides Python APIs for loading, parsing, and working with the MS-COCO dataset, including annotation access and evaluation metrics for object detection and segmentation tasks.","skillfed_tags":["dataset-tools","computer-vision","coco-format"],"use_cases":["Load COCO-format annotations and retrieve image metadata and ground-truth bounding boxes for training object detection models.","Evaluate detection and segmentation model predictions against COCO ground truth using standard metrics (AP, AR).","Decode and manipulate instance segmentation masks stored in run-length encoded format within COCO JSON files.","Query and filter annotations by category, image ID, or area to prepare dataset splits for training and validation.","Integrate COCO dataset loading into computer vision pipelines that require standard annotation formats."],"what_it_does":"pycocotools is a maintained fork of the official MS-COCO dataset API, providing Python bindings to load and manipulate COCO-format annotations for object detection, instance segmentation, and keypoint detection tasks. It wraps the original C++ implementation and depends only on numpy. The package includes utilities to parse JSON annotation files, query images and annotations, compute evaluation metrics, and encode/decode run-length encoded segmentation masks.\n\nThe fork addresses long-standing issues in the original cocoapi: it installs cleanly via pip on Windows and modern Python versions, avoids unnecessary matplotlib imports, fixes file handle leaks, and resolves segmentation faults in RLE decoding. It maintains API compatibility with the original to ensure existing code continues to work without modification.","worth_installing":"Yes, if you work with COCO-format datasets. The package is actively maintained, widely used (top 5000 on PyPI), has no known vulnerabilities, and the fork fixes real issues in the original. Verify the FreeBSD license terms for your use case before committing to a production dependency."},"id":"pycocotools","links":{"html":"https://skillfed.io/packages/pycocotools","md":"https://skillfed.io/packages/pycocotools.md","pypi":"https://pypi.org/project/pycocotools/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-12-15","license_spdx":null,"license_treatment":"unclear","name":"pycocotools","python_support":"supports_current","summary":"Official APIs for the MS-COCO dataset"},"popularity":{"monthly_downloads":5686892,"position":2053,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"2.0.11"}