Reverse Dependencies of supervision

The following projects have a declared dependency on supervision:

• achatbot — An open source chat bot for voice (and multimodal) assistants
• ArtTracker — Efficient person tracking using YOLOv8 and ZeroMQ (Zmq)
• atar — A CLI tool for AI tasks such as dataset handling, training, and validation.
• autodistill — Distill large foundational models into smaller, domain-specific models for deployment
• autodistill-albef — ALBEF module for use with Autodistill
• autodistill-altclip — AltCLIP model for use with Autodistill.
• autodistill-azure-vision — Azure Vision base model for use with Autodistill
• autodistill-bioclip — BioCLIP model for use with Autodistill
• autodistill-blip — BLIP module for use with Autodistill
• autodistill-clip — CLIP module for use with Autodistill
• autodistill-codet — CoDet model for use with Autodistill
• autodistill-detic — DETIC module for use with Autodistill
• autodistill-detr — DETR module for use with Autodistill
• autodistill-dinov2 — DINOv2 module for use with Autodistill
• autodistill-efficient-yolo-world — EfficientSAM + YOLO-World base model for use with Autodistill
• autodistill-efficientsam — EfficientSAM model for use with Autodistill
• autodistill-eva-clip — EvaClip module for use with Autodistill
• autodistill-fastsam — FastSAM module for use with Autodistill
• autodistill-fastvit — FastViT model for use with Autodistill
• autodistill-florence-2 — Use Florence 2 to auto-label data for use in training fine-tuned object detection models.
• autodistill-gcp-vision — Autodistill Google Cloud Vision module for use in training a custom, fine-tuned model.
• autodistill-gemini — Model for use with Autodistill
• autodistill-gpt-4o — GPT-4o model for use with Autodistill
• autodistill-gpt-4v — GPT-4V model for use with Autodistill
• autodistill-grounded-edgesam — Model for use with Autodistill
• autodistill-grounded-sam — Automatically distill large foundational models into smaller, in-domain models for deployment
• autodistill-grounded-sam-2 — Use Segment Anything 2, grounded with Florence-2, to auto-label data for use in training vision models.
• autodistill-grounding-dino — GroundingDINO module for use with Autodistill
• autodistill-hls-geospatial — Use the HLS Geospatial model made by NASA and IBM to generate masks for use in training a fine-tuned segmentation model.
• autodistill-metaclip — MetaCLIP base model for use with Autodistill.
• autodistill-mobileclip — Model for use with Autodistill
• autodistill-owl-vit — OWL-ViT module for use with Autodistill
• autodistill-owlv2 — OWLv2 base model for use with Autodistill.
• autodistill-paligemma — Auto-label data with a PaliGemma model, or ine-tune a PaLiGemma model using custom data with Autodistill.
• autodistill-rekognition — AWS Rekognition base model for use with Autodistill
• autodistill-roboflow-universe — Use models on Roboflow Universe to auto-label data for use in model training.
• autodistill-sam-clip — SAM-CLIP model for use with Autodistill
• autodistill-sam-hq — Segment Anything High Quality (SAM HQ) model for use with Autodistill
• autodistill-seggpt — SegGPT for use with Autodistill
• autodistill-segment-anything — Segment Anything model for use with Autodistill
• autodistill-transformers — Use object detection models in Hugging Face Transformers to automatically label data to train a fine-tuned model.
• autodistill-vit — ViT module for use with Autodistill
• autodistill-vlpart — VLPart for use with Autodistill
• autodistill-yolo-world — YOLO World for use with Autodistill
• autodistill-yolonas — YOLO-NAS module for use with Autodistill
• autodistill-yolov5 — YOLOv5 module for use with Autodistill
• AxleSpacing — A Python library for vehicle axle spacing detection.
• baseballcv — A collection of tools and models designed to aid in the use of Computer Vision in baseball.
• bluevision — Bluesignal Vision AI project
• coralnet-toolbox — Tools for annotating and developing ML models for benthic imagery
• cua-som — Computer Vision and OCR library for detecting and analyzing UI elements
• ezsam — Extract foreground from images or video via text prompt
• face-recognition-pkg — A package for face recognition in images and videos
• gdinopy — open-set object detector
• gptstream — OpenAI GPT Vision meets your webcam
• groundingdino-gml — open-set object detector
• groundingdino-iscas — open-set object detector
• groundingdino-stk — Welcome to the GroundingDINO-stk project! This repository provides a source that can install the `GroundingDINO` library from `PyPI`. The `GroundingDINO` version was last updated on `2023/06/29`.
• groundingdino-yl — open-set object detector
• groundino-samnet — A SAM model with GroundingDINO model for feet segmentation
• gvision — End-to-end automation platform for computer vision projects.
• indoxMiner — Indox Data Extraction
• inference — With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference.
• inference-cli — With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference CLI.
• inference-core — With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference.
• inference-cpu — With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference.
• inference-gpu — With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference.
• inference-sdk — With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference.
• juxtapose — no summary
• maestro — Streamline the fine-tuning process for vision-language models like PaliGemma 2, Florence-2, and Qwen2.5-VL.
• mdify — A powerful tool to extract text, tables, charts, and formulas from documents and convert them into Markdown format, ideal to improve LLM's accuracy and for versatile document processing.
• meta-label — Meta Auto Label Toolkit
• modelzilla — It is a lightweight Python package that enables developers to transform any AI model into a fully functional Command-Line Interface (CLI) plugin
• multimodal-maestro — Visual Prompting for Large Multimodal Models (LMMs)
• nw-groundingdino — open-set object detector
• ocr-loc — Add your description here
• opsci-toolbox — a complete toolbox
• ovsegmentation — Open vocabulary detection and segmentation package
• pdf-processing-lib — A library for processing PDF documents, images, extracting text, parsing TSV to JSON, and merging JSON files
• pi-inference — pi-inference
• pyniche — An AI Library for Niche Squad
• pyresearch — Computer Vision Helping Library
• PytorchWildlife — a PyTorch Collaborative Deep Learning Framework for Conservation.
• reefbuilder_segmentation — An instance segmentation library focussed on solving marine conservation-related problems
• rf-groundingdino — open-set object detector
• rfdetr — RF-DETR
• rlmc — Python utils for AI 🚀
• rt-pose — Real-time (GPU) pose estimation pipeline with 🤗 Transformers
• segment-lidar — A package for segmenting LiDAR data using Segment-Anything Model (SAM) from Meta AI Research.
• setofmark — Visual Prompting for Large Multimodal Models (LMMs)
• smart-reid — With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference CLI.
• ubigeoaii — Libreria que automatiza procesos espaciales complejos
• video-annotator — A Python package for video annotation, object tracking, and cropping
• visionframe — Empower Your Computer Vision Projects with VisionFrame: Seamlessly Handle Video and Image
• visionscript — VisionScript is an abstract programming language for doing common computer vision tasks, fast.
• vodin — Odin - Pytorch
• webcamgpt — WebcamGPT - chat with video stream
• yolo-world-open — YOLO-World: Real-time Open Vocabulary Object Detection