Data management in Supervisely Blog
Dataset Versioning for Computer Vision and Experiment Tracking
Dataset versioning for computer vision: compare DVC, Git LFS and Supervisely, and link dataset versions to experiments, models and benchmark reports.
Sergey Sych
Data Annotation QA: Checklist and Tools for Training Datasets
A data annotation QA checklist for computer vision datasets: what to check, which numbers to track, and how to find label errors with interactive statistics.
How to Filter and Query a Computer Vision Dataset
Filter image datasets by class, tag, object count, author, issue or labeling job status, preview results live and act on them. A Supervisely filters tutorial.
Synthetic Data for Segmentation: 7 Steps That Improved Our Model
What we learned training dozens of segmentation models on synthetic cracks: seven data steps, from edge smoothing to style transfer, that narrowed the gap.
Dataset Ninja: Search and Explore Computer Vision Datasets
Dataset Ninja is a free catalog to search computer vision datasets by industry, class or license, explore statistics and train in Supervisely in a click.
Synthetic Crack Segmentation Dataset: How We Built It
A synthetic crack segmentation dataset: 1,558 labeled 512x512 images built from real textures, procedural cracks and style transfer. See how it was made.
OpenAI CLIP for Image Retrieval: Filter a Dataset by Text Prompt
Type a text prompt and find the most relevant images in a large training dataset. See how CLIP embeddings work and filter images with a UI in Supervisely.