{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/8"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/17"}],"enrichment":{"capability":"Detects and localizes faces in images using a PyTorch implementation of the RetinaFace single-stage face detection model, with support for both ResNet50 and MobileNet0.25 backbones.","skillfed_tags":["face-detection","computer-vision","abandoned"],"use_cases":["Detect and extract face regions from images for downstream face recognition or verification tasks.","Localize facial landmarks (e.g., eyes, nose, mouth) for face alignment preprocessing.","Deploy lightweight face detection on mobile or edge devices using the MobileNet0.25 backbone.","Benchmark face detection performance on standard datasets like WIDERFACE or FDDB.","Integrate into batch image processing pipelines to filter or annotate images containing faces."],"what_it_does":"RetinaFace-py is a PyTorch port of the RetinaFace face detection algorithm, a single-stage detector designed to localize faces and facial landmarks in unconstrained images. It offers two backbone architectures: MobileNet0.25 for lightweight deployment (model size 1.7M) and ResNet50 for higher accuracy. The package wraps the core detection logic and is intended for integration into face-detection pipelines, particularly on edge devices or resource-constrained environments.\n\nThe package depends on numpy, torch, torchvision, and opencv-python for tensor operations, model inference, and image I/O. It is abandoned as of February 2023 with no maintenance since its single release, meaning it will not receive updates for new PyTorch versions, security patches, or API changes in its dependencies. Users should expect potential compatibility issues with modern PyTorch releases and should treat it as a reference implementation rather than a production-ready library.","worth_installing":"No, not recommended for new projects. While the package has low install friction and permissive licensing, it is abandoned (last commit February 2023) and will not receive maintenance or updates. For production face detection, use actively maintained alternatives. Consider this package only for research, reference, or legacy system maintenance where the specific RetinaFace architecture is required and you can manage dependency conflicts independently."},"id":"retinaface-py","links":{"html":"https://skillfed.io/packages/retinaface-py","md":"https://skillfed.io/packages/retinaface-py.md","pypi":"https://pypi.org/project/retinaface-py/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2023-02-14","license_spdx":null,"license_treatment":"permissive","name":"retinaface-py","python_support":"supports_current","summary":"RetinaFace: Single-stage Dense Face Localisation in the Wild"},"popularity":{"monthly_downloads":153897,"position":10867,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.0.2"}