Blog News and guides from the Supervisely team.
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Scalable Polygon Annotation: Clean, Aligned Boundaries for Geospatial Data
Annotate buildings, parcels and land cover with polygons in Supervisely: start from AI masks, align boundaries between objects, cut holes and fix local errors.
Stan Soldatov
Introducing Video + GPS Telemetry: Synchronize Footage, Maps, and Sensor Data
Review video with synchronized GPS maps and sensor charts in Supervisely, find events by route or telemetry, and label real-world footage for Physical AI.
Ultimate Guide On Multiview Image Annotation For Custom Training Datasets in Computer Vision
Learn how to use Supervisely's Multiview Image Labeling Toolbox to upload and annotate multiview images simultaneously.
Introducing Video Annotation 3.0
Our largest update so far, with AI-powered auto tracking, enhanced tag management, and a sleek new design for faster, smarter video labeling.
Introducing MLOps Workflow and Data Versioning: track your datasets, models and Computer Vision experiments
Easy-to-use visual MLOps Pipelines simplify data version control and the ML modeling process, making all experiments reproducible and clear.
Introducing Definitions Panel: a new way to assign classes and tags
How to reduce the number of steps and clicks to label an object or change its class.
Segment Anything 2 (SAM2) in Supervisely: The Fast and Accurate Object Segmentation Tool for Image and Video Labeling
How to automatically segment and track objects on images and videos using Segment Anything model 2 in Supervisely
Complete guide on 2D medical image annotation in Supervisely
Learn how to annotate DICOM, NRRD, NIfTI medical images in 2D with efficient collaboration, CT / MRI windowing and AI auto-labeling.
The Complete Guide to Image Matting: Segment using Matte Anything Model and Brush Tool with Transparency
Learn how to annotate images for image matting task in Supervisely using predictions from Matte Anything model.
How to use 3D Slicer with Supervisely to Annotate Medical Training Datasets At Scale | Computer Vision Guide
Discover how to unlock the power of annotating 3D medical images and boost teamwork collaboration by using the best of both worlds.
Top 10 Quality Assurance Tools And Interactive Statistics For Your Training Dataset | Ultimate Guide
Learn how to use best quality assurance and interactive statistical tools to perfect your custom training datasets and improve neural network performance.
Introducing Advanced Dataset Filters for Efficient Data Management | Supervisely Tutorial
Learn how to use conditional filters and build custom queries to your training data. Easily search, filter, sample and explore your Computer Vision datasets.
The Ultimate Image Annotation Tool: The Complete Guide to New Supervisely Labeling Toolbox
Learn how to use new Supervisely Image Annotation Tool designed for fast and accurate image annotation in Computer Vision.
Manual Image Segmentation in Computer Vision: A Comprehensive Overview of Annotation Techniques
An overview of the three main manual image segmentation methods in computer vision: overlaying, snapping to object boundaries and splitting masks.
Sidebar is back! New layout and more — February 2024 updates
Learn about the new sidebar that offers quick access to frequently used pages, recent apps and updated team and workspace context switchers.
How To Segment Entire Object And Its Component Parts With Mask Splitting Method
Complete tutorial on labeling multiple parts of the object using efficient splitting annotation technique in Computer Vision
How To Tag Multi-Camera Video Segments For Action Recognition In Computer Vision | Full Tutorial
Guide on video annotation, tagging and management tool tailored for multi-camera videos in Supervisely
Guide to Training Custom Interactive Instance Segmentation Model for Agricultural Images
We trained Instance Segmentation model for agricultural plant images and achieved remarkable results.
Image and object tags for classification in Computer Vision: Complete Guide
Tutorial on how to use tags and attribute of different types in various industries with real examples.
How to Annotate Multispectral Images for Computer Vision Models
Learn how to use multi-view display in Supervisely Image Labeling Tool to efficiently annotate multispectral images
How To Use Model Assisted Labeling To Boost Annotation Performance With Supervisely
A Deep Dive into the Beloved Supervisely Smart Labeling Tools for AI-Assisted Interactive Object Segmentation
Brush Annotation Tool: your must-have for Object Segmentation
Learn how to annotate objects of any complexity by creating freeform outlines using the Brush annotation tool.
Mask Pen Annotation Tool for Object Segmentation in Supervisely
Learn how to use Mask Pen annotation tool as a combination of polygonal contours and free-form drawing contours.
How to Train a Model with Only 62 Labeled Images using Semi-Supervised Learning
This experiment reveals the potential of semi-supervised learning, proving the opportunity to train a model using only a small fraction of labeled data.
Polygon Annotation Best Practices for Semantic & Instance Segmentation
Learn how to use Polygon tool for efficient and precise object segmentation in Computer Vision.
Best Bounding Box Image Annotation Tools For Object Detection - Complete Overview
How to use modern bounding box image labeling toolbox for Computer Vision in Supervisely.
How To Use 3D Object Interpolation To Speed Up Point Cloud Annotation for LiDAR & Radar
The complete guide on 3D bounding box interpolation in point cloud episodes in Supervisely.
What is Sliding Window in Object Detection: Complete Overview of Methods & Tools
How to use sliding window method with object detection models to improve accuracy in Computer Vision.
MBPTrack Tutorial: 3D Point Cloud Object Tracking for LiDAR & Radar
The complete guide on 3D single object tracking on custom point cloud episodes in Supervisely LiDAR annotation toolbox.
Unleash The Power of Domain Adaptation - How to Train Perfect Segmentation Model on Synthetic Data with HRDA
Tutorial on training accurate and robust Semantic Segmentation model without manual annotation using only synthetic training dataset
Labeling Queues: Streamline Your Labeling Pipeline
Discover the optimal approach for annotating and structuring large-scale data labeling tasks with using Labeling Queues and following our step-by-step guide.
Lessons Learned From Training a Segmentation Model On Synthetic Data
Insights from training dozens of segmentation models on synthetic data, and methods that improve the quality of synthetic training data.
Mastering Labeling Jobs: Your Ultimate Guide
Discover the power of collaborative annotation through labeling jobs. Learn how to harness teamwork for efficient and accurate data annotation.
Dataset Ninja 🥷 — the best way to Search and Explore Computer Vision Datasets
High-quality training datasets with deep analysis and visualization tools.
Human Pose Estimation: all you need to know
Get ready to be impressed by how quickly and accurately Supervisely can estimate human poses using advanced techniques.
Unlocking Text - OCR with Supervisely
Discover how to make the most of Optical Character Recognition (OCR) capabilities within Supervisely.
The Complete Guide to Animal Pose Estimation: Tools, Models, Tutorial
Discovering animal pose estimation with Supervisely. Learn how to annotate animals using keypoints and State-of-the-Art neural networks.
ViTPose — How to use the best Pose Estimation Model on Humans & Animals
The complete guide on automatic body pose estimation of animals and humans on your images in Supervisely.
Introducing Supervisely Synthetic Crack Segmentation Dataset
We present our synthetic dataset for road surface crack segmentation that was generated automatically, available for research purposes.
How to Train Smart Tool for Precise Cracks Segmentation in Industrial Inspection
Step-by-step guide for industrial inspection cracks segmentation on images using custom interactive AI model.
How to run OpenAI CLIP with UI for Image Retrieval and Filtering your dataset
How to use text prompts and AI to search and query relevant images in your training datasets.
Segment Anything in High Quality (HQ-SAM): a new Foundation Model for Image Segmentation (Tutorial)
How to use new version of Segment Anything + detailed comparison with original SAM model.
Complete Guide to Object Tracking: Best AI Models, Tools and Methods
In this ultimate guide and tutorial you will learn what is object tracking and learn how to track objects on your videos with the best models and tools.
XMem + Segment Anything: Video Object Segmentation SOTA | Tutorial
How to segment and track objects on videos automatically with Segment Anything and XMem to build custom training datasets.
Automate manual labeling with custom interactive segmentation model for agricultural images
How to speed up image segmentation in agriculture with custom AI models
How to auto-label images with OWL-ViT - SOTA Google's foundation object detector
Automatically detect anything with only one example using OWL-ViT - one-shot object detection SOTA
No-code tutorial: train and predict YOLOv8 on custom data
The easiest way to get custom YOLOv8 model trained on your own dataset and deploy it with zero coding in the browser.
Best DICOM & NIfTI annotation tools for Medical Imaging AI
Learn how to label CT, MRI, and PET medical images for your computer vision models.
Top 5 AI tools for fast surgical video annotation
How to use modern AI object tracking and segmentation tools to get medical training data 10x faster
How to use labeling consensus to get accurate training data
Consensus with detailed reports allows you to monitor and prevent systematic inconsistencies during the labeling process