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videos

75 results found

Video labeling tool

complete solution for video annotation

Import Videos

Import Videos without annotations to Supervisely

Clone

Clone project or dataset to selected workspace or project, works with all project types: images / videos / 3d / dicom

Export videos project in Supervisely format

Export videos project and prepares downloadable tar archive

Export only labeled items

Export only labeled items and prepares downloadable tar archive

Train YOLOv5

Dashboard to configure and monitor training

Import videos from cloud storage

Import videos from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)

Import videos in Supervisely format

Import videos with annotations in Supervisely format

Serve YOLOv5

Deploy model as REST API service

Import videos by URLs from txt file

Downloads videos by URLs and uploads them to Supervisely Storage

Videos project to images project

Creates images project from video project

RITM interactive segmentation SmartTool

State-of-the art object segmentation model in Labeling Interface

Train MMDetection

Dashboard to configure, start and monitor training

Extract frames from videos

Read every n-th frame and save to images project

Train Detectron2

Dashboard to configure, start and monitor training

Train MMSegmentation

Dashboard to configure, start and monitor training

Apply NN to Videos Project

Predictions on every frame are combined with DeepSort into tracks automatically

TransT object tracking (CVPR2021)

TransT object tracking (CVPR2021)

serve and use in videos annotator

Serve Segment Anything Model

Deploy model as REST API service

Serve MMDetection

Deploy model as REST API service

Train UNet

Dashboard to configure, start and monitor training

Serve Detectron2

Deploy model as REST API service

Render Video Labels to MP4

Creates presentation mp4 file based on labeled video

Serve ClickSEG

Deploy ClickSEG models for interactive instance segmentation

Train RITM

Dashboard to configure, start and monitor training

Serve MMSegmentation

Deploy model as REST API service

Mark attributed segments on multi-camera videos

Tag segments (begin and end) with custom attributes on single or multiple videos in dual-panel view

Object detection metrics

Interactive Confusion matrix, mAP, ROC and more

Video objects stats for every class

The number of objects, figures and frames for every class for every dataset

Split datasets

Split one or multiple datasets into parts

Train MMDetection 3.0

Training dashboard for mmdetection framework (v3.0.0 and above).

XMem Video Object Segmentation

Semi-supervised, works with both long and short videos

Images project to videos project

Creates video project from images project

Serve UNet

Deploy model as REST API service

Render video to compare projects

Put images with labels into collage and renders comparison videos

Action Recognition Labeling Tool

Label videos for Action Recognition task

Export YOLOv5 weights

to TorchScript and ONNX formats

Render video from images

Creates video from images in dataset with selected frame rate and configurable label opacity

EiSeg interactive segmentation SmartTool

SmartTool integration of Efficient Interactive Segmentation (EISeg)

Mark segments on multi-camera videos

Tag segments (begin and end) on single or multiple videos in dual-panel view

Serve Segment Anything in High Quality

Run HQ-SAM and then use in labeling tool

Serve MMDetection 3.0

Deploy MMDetection 3.0 model as a REST API service

MixFormer object tracking (CVPR2022)

CVPR2022 SOTA video object tracking

PIPs object tracking

Track points and polygons on videos

Classic Labeling Queues

Annotate Project using Queues

Batched Smart Tool for Videos

Batched smart labeling tool for Videos

Take fragment from video

Extract video fragment to selected project or dataset

Import YouTube videos

Import videos by urls provided in text file

Objects Interpolation on video

Track polygons, rectangles and points using linear interpolation

Export items after review

Export items after the passing labeling job review

YouTube Downloader

Downloads and trim video from Youtube.

Change video framerate

Change video framerate with preserving duration (recodes video)

TAP-Net object tracking

Track points and polygons on videos

Labelbox to Supervisely Migration Tool

Convert and copy multiple Labelbox projects into Supervisely at once.

Import Videos from Team Files

Import selected videos from Team Files to selected destination

Train HRDA

Train HRDA model for segmentation in semi-supervised mode

Labeling Consensus for Videos

Compare annotations of multiple labelers

Action Recognition Stats Tool

Analyse videos labeled for Action Recognition task

Merge Tags

Merge Tags in videos or images project

Convert Video Class Shape

Converts shapes of classes on videos (e.g. polygon to bitmap) and all corresponding objects

Create project from template

Create a new empty project with a meta of original project

Serve InSPyReNet

Deploy InSPyReNet for salient object segmentation as a REST API service

[beta] Serve OpenCV

[beta] Serve OpenCV

serve and use in videos annotator

Synthetic videos for tracking

Synthesize videos on annotated data

Serve HRDA

Deploy HRDA model for inference

Import CVAT

Import images and videos with annotations in CVAT format.

Serve Transfiner

Deploy Transfiner for instance segmentation as a REST API service

CVAT to Supervisely Migration Tool

Convert and copy multiple CVAT projects into Supervisely at once.

Serve SelfReformer

Deploy SelfReformer for salient object segmentation as a REST API service

CoTracker object tracking

Track points, polygons and skeletons (keypoints) on videos

Action Recognition

Label and Review videos for Action Recognition task

Import V7

Import images and videos with annotations in V7 format.

V7 to Supervisely Migration Tool

Convert and copy multiple V7 datasets into Supervisely at once.

Videos example

Videos example

Sample videos with labels

Demo video pairs

Demo video pairs

Video pairs for multicamera labeling