Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
$ npx skills add open-edge-platform/training_extensionsAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
Images to inference with no labeling (use foundation models to train supervised models).
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
$ npx skills add open-edge-platform/training_extensionsAccelerated deep learning R&D
$ npx skills add catalyst-team/catalystA Python toolkit for fine-tuning Geospatial Foundation Models (GFMs).
$ npx skills add torchgeo/terratorchTorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
$ npx skills add torchgeo/torchgeoOfficial Repository for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]
$ npx skills add digantamisra98/MishXtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.
$ npx skills add xtreme1-io/xtreme1🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️
$ npx skills add laugh12321/TensorRT-YOLOScenic: A Jax Library for Computer Vision Research and Beyond
$ npx skills add google-research/scenicA python library for self-supervised learning on images.
$ npx skills add lightly-ai/lightlyPython Computer Vision & Video Analytics Framework With Batteries Included
$ npx skills add insight-platform/SavantEffortless AI-assisted data labeling with AI support from YOLO, Segment Anything (SAM+SAM2/2.1+SAM3), MobileSAM!!
$ npx skills add vietanhdev/anylabelingA modular high-level library to train embodied AI agents across a variety of tasks and environments.
$ npx skills add facebookresearch/habitat-labAn open source library and framework for deep learning on satellite and aerial imagery.
$ npx skills add azavea/raster-vision记录cv算法工程师的成长之路,分享计算机视觉和模型压缩部署技术栈笔记。https://harleyszhang.github.io/cv_note/
$ npx skills add harleyszhang/cv_noteVisit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
$ npx skills add ayoolaolafenwa/PixelLibAll-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
$ npx skills add lightly-ai/lightly-trainHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Autodistill if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.