C

computer-vision

Semantic Vectorizing and Masking Creator: A desktop application for AI-powered image segmentation, masking, and vectorization.

Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

GitHub: https://github.com/ultralytics/ultralytics

https://platform.ultralytics.com

Local-first, vision-LLM CAPTCHA solver for AI agents — MCP plugin + NopeCHA-style HTTP job API over any Chromium

Official Python SDK for the Ultralytics Platform API

GitHub: https://github.com/ultralytics/sdk

https://platform.ultralytics.com/api/docs

YOLOE data pipeline for grounding and detection labels, predictions, text refinement, cache generation, and visualization.

GitHub: https://github.com/ultralytics/yoloe_data_engine

https://docs.ultralytics.com/models/yoloe/

Ready-to-use Cog deployments and CI/CD for running Ultralytics YOLO11, YOLO World, YOLOE, and YOLO26 models on Replicate.

GitHub: https://github.com/ultralytics/replicate

https://replicate.com/ultralytics/yolo11n

Ultralytics YOLO tutorials for Colab, Kaggle, and SageMaker covering training, inference, export, and vision tasks.

GitHub: https://github.com/ultralytics/notebooks

https://docs.ultralytics.com

PyTorch model profiler for computing MACs and parameter counts to measure deep learning model complexity.

GitHub: https://github.com/ultralytics/thop

https://pypi.org/project/ultralytics-thop/

Retired Python SDK for the shut-down Ultralytics HUB API, kept for reference; build new integrations on the Ultralytics Platform REST API

GitHub: https://github.com/ultralytics/hub-sdk

https://docs.ultralytics.com/platform/api

Ultralytics model comparison docs and automated QA for websites, links, spelling, sitemaps, and image sizes.

GitHub: https://github.com/ultralytics/docs

https://docs.ultralytics.com

Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.

GitHub: https://github.com/ultralytics/yolov5

https://docs.ultralytics.com/yolov5/

Bing image scraper with HTML and Selenium search, format filters, CLI and Python APIs, and dataset downloads.

GitHub: https://github.com/ultralytics/google-images-download

https://ultralytics.com

Python Flickr image scraper for building keyword-based computer vision datasets with pagination and deduplication.

GitHub: https://github.com/ultralytics/flickr_scraper

https://ultralytics.com

PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.

GitHub: https://github.com/ultralytics/yolov3

https://docs.ultralytics.com/models/yolov3/

Docker container, inference pipeline, and submission tooling for deploying trained YOLOv3 object detection models in the xView satellite imagery challenge.

GitHub: https://github.com/ultralytics/xview-docker

https://challenge.xviewdataset.org/

PyTorch sandbox for testing convolutional networks, ResNets, and other architectures on MNIST digits.

GitHub: https://github.com/ultralytics/mnist

https://ultralytics.com

YOLOv3 training, preprocessing, validation, and inference for object detection in xView satellite imagery and the xView detection challenge.

GitHub: https://github.com/ultralytics/xview-yolov3

https://docs.ultralytics.com

Machine learning and Structure-from-Motion tools for estimating vehicle speed from imagery for traffic monitoring, road safety, and autonomous systems research.

GitHub: https://github.com/ultralytics/velocity

https://www.ultralytics.com

An open-source computer vision framework for wildlife image analysis, featuring state-of-the-art models for species classification and detection.

Turns ordinary photos into thermographic, X-ray, Kirlian, and night-vision renders via real physics simulation — not a filter.