Video labeling tool
complete solution for video annotation
complete solution for video annotation
Import Videos without annotations to Supervisely
Clone project or dataset to selected workspace or project, works with all project types: images / videos / 3d / dicom
Export videos project and prepares downloadable tar archive
Export only labeled items and prepares downloadable tar archive
Dashboard to configure and monitor training
Import videos from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)
Import videos with annotations in Supervisely format
Deploy model as REST API service
Downloads videos by URLs and uploads them to Supervisely Storage
Creates images project from video project
State-of-the art object segmentation model in Labeling Interface
Dashboard to configure, start and monitor training
Read every n-th frame and save to images project
Dashboard to configure, start and monitor training
Dashboard to configure, start and monitor training
Predictions on every frame are combined with DeepSort into tracks automatically
serve and use in videos annotator
Deploy model as REST API service
Deploy model as REST API service
Dashboard to configure, start and monitor training
Deploy model as REST API service
Creates presentation mp4 file based on labeled video
Deploy ClickSEG models for interactive instance segmentation
Dashboard to configure, start and monitor training
Deploy model as REST API service
Tag segments (begin and end) with custom attributes on single or multiple videos in dual-panel view
Interactive Confusion matrix, mAP, ROC and more
The number of objects, figures and frames for every class for every dataset
Split one or multiple datasets into parts
Training dashboard for mmdetection framework (v3.0.0 and above).
Semi-supervised, works with both long and short videos
Creates video project from images project
Deploy model as REST API service
Put images with labels into collage and renders comparison videos
Label videos for Action Recognition task
to TorchScript and ONNX formats
Creates video from images in dataset with selected frame rate and configurable label opacity
SmartTool integration of Efficient Interactive Segmentation (EISeg)
Tag segments (begin and end) on single or multiple videos in dual-panel view
Run HQ-SAM and then use in labeling tool
Deploy MMDetection 3.0 model as a REST API service
CVPR2022 SOTA video object tracking
Track points and polygons on videos
Annotate Project using Queues
Batched smart labeling tool for Videos
Extract video fragment to selected project or dataset
Import videos by urls provided in text file
Track polygons, rectangles and points using linear interpolation
Export items after the passing labeling job review
Downloads and trim video from Youtube.
Change video framerate with preserving duration (recodes video)
Track points and polygons on videos
Convert and copy multiple Labelbox projects into Supervisely at once.
Import selected videos from Team Files to selected destination
Train HRDA model for segmentation in semi-supervised mode
Compare annotations of multiple labelers
Analyse videos labeled for Action Recognition task
Merge Tags in videos or images project
Converts shapes of classes on videos (e.g. polygon to bitmap) and all corresponding objects
Create a new empty project with a meta of original project
Deploy InSPyReNet for salient object segmentation as a REST API service
serve and use in videos annotator
Synthesize videos on annotated data
Deploy HRDA model for inference
Import images and videos with annotations in CVAT format.
Deploy Transfiner for instance segmentation as a REST API service
Convert and copy multiple CVAT projects into Supervisely at once.
Deploy SelfReformer for salient object segmentation as a REST API service
Track points, polygons and skeletons (keypoints) on videos
Label and Review videos for Action Recognition task
Import images and videos with annotations in V7 format.
Convert and copy multiple V7 datasets into Supervisely at once.
Sample videos with labels
Video pairs for multicamera labeling