{"categories":[{"label":"Image Recognition","url":"https://skillfed.io/packages/category/scientific-engineering-image-recognition"}],"enrichment":{"capability":"Provides a collection of pretrained computer vision models for PyTorch, including image classification, segmentation, detection, and pose estimation architectures.","skillfed_tags":["model-zoo","transfer-learning","computer-vision"],"use_cases":["Load a pretrained ResNet or EfficientNet for image classification without writing model code from scratch.","Benchmark multiple architectures on a custom dataset using the same normalization and interface.","Extract features from intermediate layers of pretrained models for transfer learning tasks.","Evaluate segmentation models like PSPNet or DeepLabv3 on Pascal VOC or ADE20K without reimplementing them.","Prototype mobile-efficient models like MobileNetV3 or ShuffleNet for deployment scenarios."],"what_it_does":"pytorchcv is a model zoo for PyTorch that bundles implementations of dozens of computer vision architectures\u2014from classic networks like AlexNet, VGG, and ResNet to modern designs like EfficientNet, MobileNetV3, and HRNet. Models are pretrained on standard datasets including ImageNet-1K, CIFAR-10/100, COCO, and others, and load with ordinary normalization applied automatically. It covers classification, semantic segmentation, object detection, and pose estimation tasks.\n\nThe package depends on torch, torchvision, numpy, and requests. It is intended for researchers and practitioners who want quick access to reference architectures without reimplementing them. Training and evaluation scripts are maintained separately in the imgclsmob repository. The package is classified as Alpha and has not seen active development recently, though the repository remains accessible.","worth_installing":"Yes, if you need quick access to a broad range of pretrained PyTorch vision models and can tolerate aging maintenance. The package has no known vulnerabilities and low install friction. However, verify the license terms in the repository first, and confirm that model loading and normalization behavior match your requirements\u2014the lack of recent updates and unclear license status warrant a brief review before production use."},"id":"pytorchcv","links":{"html":"https://skillfed.io/packages/pytorchcv","md":"https://skillfed.io/packages/pytorchcv.md","pypi":"https://pypi.org/project/pytorchcv/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2026-01-13","license_spdx":null,"license_treatment":"unclear","name":"pytorchcv","python_support":"supports_current","summary":"Computer vision models for PyTorch"},"popularity":{"monthly_downloads":74902,"position":14772,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.0.74"}