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apps

Apps help you extend functionality with custom UI

250 results found
 153K+

Import Images

Drag and drop images to Supervisely, supported formats: .jpg, .jpeg, jpe, .mpo, .bmp, .png, .tiff, .tif, .webp, .nrrd

 40K+

Export as masks

For semantic and instance segmentation tasks

 30K+

Export to Supervisely format

images and JSON annotations

 24K+

Import images in Supervisely format

Images with corresponding annotations

 15K+

Import Videos

Import Videos without annotations to Supervisely

 11K+

Clone

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

 10K+

Import Pointclouds PCD

Import pointclouds in PCD format without annotations

 9K+

Convert Supervisely to YOLO v5 format

Transform project to YOLO v5 format and prepares tar archive for download

 7K+

Export to COCO

Converts Supervisely to COCO format and prepares tar archive for download

 7K+

Convert YOLO v5 to Supervisely format

Transform YOLO v5 format to supervisely project

 6K+

Export videos project in Supervisely format

Export videos project and prepares downloadable tar archive

 6K+

Export pointclouds project in Supervisely format

Export pointclouds project and prepares downloadable tar archive

 5K+

Export only labeled items

Export only labeled items and prepares downloadable tar archive

 5K+

NN Image Labeling

Use deployed neural network in labeling interface

 5K+

Import images from cloud storage

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

 4K+

Import Images from CSV

Upload images using .CSV file

 4K+

Train YOLOv5

Dashboard to configure and monitor training

 4K+

Apply NN to Images Project

NN Inference on images in project or dataset

 4K+

Export to YOLOv8 format

Transform Supervisely format to YOLOv8 format

 4K+

Import images with masks

Import images with binary masks as annotations

 3K+

Train YOLO (v8, v9)

Dashboard to configure, start and monitor YOLO (v8, v9) training

 3K+

Export to Pascal VOC

Converts Supervisely Project to Pascal VOC format

 2K+

Import COCO

Converts COCO format to Supervisely

 2K+

Import videos from cloud storage

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

 2K+

Import videos in Supervisely format

Import videos with annotations in Supervisely format

 2K+

Merge datasets

Merge selected datasets with images or videos into a single one

 2K+

Convert Class Shape

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

 2K+

Import Pointcloud Episodes

Import Pointcloud Episodes with Annotations and Photo context

 2K+

Serve YOLOv5

Deploy model as REST API service

 2K+

Export activity as csv

Download activity as csv file

 2K+

Import DICOM studies

Creates project with images grouped by selected metadata, converting DICOM data to NRRD format in the process.

 2K+

Download images

Download images from project or dataset.

 2K+

Videos project to images project

Creates images project from video project

 2K+

RITM interactive segmentation SmartTool

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

 1K+

Assign train/val tags to images

Assigns tags (train/val) to images. Training apps will use these tags to split data.

 1K+

Import Pointclouds PLY

Import pointclouds without annotations in .ply format from Team Files

 1K+

Import DICOM Volumes

Import volumes in DICOM and NRRD formats without annotations

 1K+

Import videos by URLs from txt file

Downloads videos by URLs and uploads them to Supervisely Storage

 1K+

Classes stats for images

Detailed statistics for all classes in images project

 1K+

Filter images

Filters images and provides results in selected format

 1K+

Serve YOLO (v8, v9)

Deploy YOLO (v8, v9) as REST API service

 1K+

Train MMDetection

Dashboard to configure, start and monitor training

 1K+

Extract frames from videos

Read every n-th frame and save to images project

 1K+

Serve Segment Anything Model

Deploy model as REST API service

 1K+

Import Pascal VOC

Import public or custom data in Pascal VOC format to Supervisely

 1K+

Export Pointcloud Episodes in Supervisely format

Export project or dataset in Supervisely pointcloud episode format

 1K+

Merge classes

Merge multiple classes with same shape to a single one

 1K+

Train MMSegmentation

Dashboard to configure, start and monitor training

 1K+

Apply 3D Detection to Pointcloud Project

Run 3D Detection and tracking algorithm on pointclouds or pointcloud episodes project

 1K+

Apply NN to Videos Project

Predictions on every frame are combined with BoT-SORT/DeepSort into tracks automatically

 1K+

Train Detectron2

Dashboard to configure, start and monitor training

 1K+

Export Volumes with 3D Annotations

To Supervisely format, compatible with 3D Slicer, MITK

 1K+

AI assisted classification

Use neural network in labeling interface to classify images and objects

 1K+

Remote import

Connect your remote storage and import data without duplication. Data is stored on your server but visible in Supervisely

 1K+

Serve ClickSEG

Deploy ClickSEG models for interactive instance segmentation

 1K+

Import from Google Cloud Storage

Upload images by reading links (Google Cloud Storage) from CSV file

 1K+

Create Trainset for SmartTool

Prepare training data for SmartTool

 999

Import Point Cloud Project

Import Point Cloud Project with Annotations and Photo context in Supervisely format

 954

Export to DOTA

Export images in DOTA format and prepares downloadable archive

 947

While True Script

While True Script

Used to create infinite task for debug

 938

Serve MMDetection

Deploy model as REST API service

 932

Train MMClassification

Dashboard to configure, start and monitor training

 921

Train UNet

Dashboard to configure, start and monitor training

 892

TransT object tracking (CVPR2021)

TransT object tracking (CVPR2021)

serve and use in videos annotator

 881

Export to KITTI 3D

Converts Supervisely Pointcloud format to KITTI 3D

 863

Serve MMDetection3D

Deploy model as REST API service

 832

Export to Cityscapes

Converts Supervisely annotations to Cityscapes format and prepares downloadable tar archive

 825

Copy project between instances

Copies images + annotations + images metadata

 821

Metric Learning Labeling Tool

Use metric learning models to classify images

 814

ML Pipelines

[Beta] Drag and drop interface for building custom DataOps pipelines

 763

Flying objects

Generate synthetic data: flying foregrounds on top of backgrounds

 763

Train MMDetection 3.0

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

 746

Serve Detectron2

Deploy model as REST API service

 704

ImgAug Studio

Visualize and build augmentation pipeline with ImgAug

 696

Render Video Labels to MP4

Creates presentation mp4 file based on labeled video

 662

Batched Smart Tool

Batched smart labeling tool for Images

 645

Export COCO Keypoints

Converts Supervisely format to COCO Keypoints

 625

Train RITM

Dashboard to configure, start and monitor training

 618

Serve OWL-ViT

Class-agnostic interactive detection for auto-prelabeling

 606

Sliding window split

Configure, preview and split images and annotations with sliding window

 598

Serve MMSegmentation

Deploy model as REST API service

 591

Diff and Merge Images Projects

Visual diff and merge tool helps compare images in two projects

 585

Apply Classifier to Images Project

Apply Classifier to Images Project

label project images or objects using NN

 559

Diff and Merge Project Meta

Visual diff and merge tool helps compare project tags and classes

 545

Import Volumes in Supervisely format

Import Supervisely volumes project with annotations

 531

CSV Products Catalog to Images Project

Convert .CSV catalog to Images Project

 522

Import KITTI 3D

Converts KITTI 3D format to Supervisely pointcloud format

 515

Import Cityscapes

Import Cityscapes to Supervisely

 506

XMem Video Object Segmentation

Semi-supervised, works with both long and short videos

 492

Split datasets

Split one or multiple datasets into parts

 483

Resize images

for both images and their annotations

 477

Serve Segment Anything in High Quality

Run HQ-SAM and then use in labeling tool

 475

Object Size Stats

Detailed statistics and distribution of object sizes (width, height, area)

 475

ilastik pixel classification

Image Pixel Classification using ilastik

 473

Serve MMClassification

Deploy model as REST API service

 470

Mark attributed segments on multi-camera videos

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

 465

Object detection metrics

Interactive Confusion matrix, mAP, ROC and more

 461

Labeling Jobs Stats

General statistics for all labeling jobs in team

 446

Crop objects on images

Creates new project with cropped objects

 439

Train MMDetection3D

Dashboard to configure, start and monitor training

 419

Rasterize objects on images

Convert classes to bitmap and rasterize objects without intersections

 418

Video objects stats for every class

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

 406

Download image links in CSV

Download CSV file with download links for images

 405

Apply OWL-ViT To Images Project

Class-angnostic object detection model

 401

Serve ViTPose

Deploy model as REST API service

 399

Serve MMDetection 3.0

Deploy MMDetection 3.0 model as a REST API service

 365

Jupyter datascience notebook

Run Jupyterlab server on your computer with Supervisely Agent and access it from anywhere

 337

Objects thumbnail preview

Review images annotations object by object with ease

 332

MixFormer object tracking (CVPR2022)

CVPR2022 SOTA video object tracking

 307

Import images groups

Import images groups connected via user defined tag

 304

Classes co-occurrence matrix

Explore images for every combination of classes pairs in co-occurrence table

 304

Apply Detection and Pose Estimation Models to Images Project

Label project images using detector and pose estimator

 299

Export Metadata

Export Images Metadata from Project

 291

Images project to videos project

Creates video project from images project

 286

Serve UNet

Deploy model as REST API service

 285

Unpack AnyShape Classes

Split "AnyShape" classes to classes with strictly defined shapes (polygon, bitmap, ...)

 281

Apply Detection and Classification Models to Images Project

Label project images using detector and classify predicted boxes

 276

Visual Tagging

Assign tags to images using example images

 271

Instance Segmentation Metrics

Interactive evaluation of your instance segmentation model

 270

Import LAS/LAZ format

Import LAS/LAZ format files to Supervisely 3D point cloud labeling tool

 269

Import Metadata

Import Metadata for Images in Project

 260

Archive Projects to Dropbox

Archive old projects on community

 259

Convert Point Clouds project to Episodes

Creates sequence of connected point clouds with tracklets

 256

Interactive objects distribution

Explore images with certain number of objects of specific class

 255

Object tags editor

Edit tags of each object on image

 247

Review labels side-by-side

Filter objects and tags by user and copy them to working area

 242

Labeling exams

App for creating and managing annotation exams

 238

Explore data with embeddings

Calculate and visualize embeddings

 230

Export to COCO mask

Converts annotations from Supervisely to COCO format as RLE masks with preserving holes

 229

3D BBox Interpolation

Deploy interpolation method as REST API service

 227

Semantic Segmentation Metrics

Semantic Segmentation Metrics

interactive metrics analysis

 227

Convert to semantic segmentation

Convert polygon and bitmap labels to semantic segmentation

 225

Export items after review

Export items after the passing labeling job review

 215

Volume Interpolation

ITK algorithms for volume interpolation

 211

Export YOLOv5 weights

to TorchScript and ONNX formats

 208

Image Classification Metrics

Evaluate your classification model

 203

Batched Smart Tool for Videos

Batched smart labeling tool for Videos

 199

Pexels downloader

Downloads images from the Pexels to the dataset.

 195

Render video to compare projects

Put images with labels into collage and renders comparison videos

 192

EiSeg interactive segmentation SmartTool

SmartTool integration of Efficient Interactive Segmentation (EISeg)

 189

Rotate images

Rotates images along with the annotations in the dataset

 186

Action Recognition Labeling Tool

Label videos for Action Recognition task

 183

Render video from images

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

 182

Apply NN to video frames

Apply NN models to video frames

 181

Prompt-based Image Filtering with CLIP

Filter and rank images by text prompts with CLIP models

 178

Train HRDA

Train HRDA model for segmentation in semi-supervised mode

 174

Images thumbnail preview

Preview images as a grid gallery

 173

Mark segments on multi-camera videos

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

 170

Roboflow to Supervisely Migration Tool

Convert and copy multiple Roboflow projects into Supervisely at once.

 169

Merge Image Projects

Merge multiple image projects into a single one

 168

Convert labels to rotated bboxes

Convert all labels in the project or dataset to rotated bounding boxes

 168

PIPs object tracking

Track points and polygons on videos

 167

Import COCO Keypoints

Converts COCO Keypoints format to Supervisely

 163

Import KITTI-360

Import Pointcloud Episodes from KITTI-360 format

 163

Take fragment from video

Extract video fragment to selected project or dataset

 160

Import Volumes with 3D Masks

Import Volumes with .nrrd 3D Masks to Supervisely

 157

Classic Labeling Queues

Annotate Project using Queues

 153

Create JSON with reference items

Objects with specific tag will be treated as reference items

 152

Print Progress and Error

Print Progress and Error

Prints progress and then raises error

 147

Tag images by dataset name

Add dataset name tag to all images in project or dataset

 144

Import volumes from cloud storage

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

 143

Labels spatial distribution

Build labels distribution heatmap for dataset.

 143

Group nested objects

Binds nested objects into groups

 143

On-the-Fly Quality Assurance

Get instant DatasetNinja statistics for your project

 142

Serve Metric Learning

Google landmarks challenge models

 140

Apply Object Segmentor to Images Project

Label project images using object segmentor

 135

Render previews GUI

Service to render annotations on the fly and show them in Supervisely

 131

Develop and Debug

Develop and Debug

Used to create infinite task for debug

 127

Objects Interpolation on video

Track polygons, rectangles and points using linear interpolation

 125

Create foreground mask

Create foreground mask from alpha channel of image

 124

Sliding window merge

Merge images and labels that were split by sliding window before

 118

Import YouTube videos

Import videos by urls provided in text file

 115

Labeling Consensus

Compare annotations of multiple labelers

 110

AI Recommendations

Recommends matching items from the catalog

 107

Labeling Events Stats

Total number of labeling actions and annotated unique images in a time interval

 100

Change video framerate

Change video framerate with preserving duration (recodes video)

 96

Synthetic retail products

Generate synthetic data for classification of retail products on grocery shelves

 96

Embeddings Calculator

Calculate embeddings for images project

 95

Unpack key value tags

Rename "Key:Value" tags to key_value (fruit: lemon -> fruit_lemon)

 92

Train YOLOv5 2.0

Dashboard to configure, start and monitor YOLOv5 2.0 training

 90

Anonymize Data

App to obscure data on images and videos

 88

Export project to cloud storage

Export project to Google Cloud Storage, Amazon S3, Microsoft Azure, ...

 86

YouTube Downloader

Downloads and trim video from Youtube.

 86

MBPTrack 3D Point Cloud Tracking

Deploy MBPTrack as REST API service

 82

MMOCR Inference

Text Detection and Recognition on images

 77

Tags to image URLs

Saves tag to images mapping to a json file

 75

Cleaner

Remove temporary files from Team files

 75

TAP-Net object tracking

Track points and polygons on videos

 75

Serve HRDA

Deploy HRDA model for inference

 73

Tags co-occurrence matrix

Explore images for every combination of tags pairs in co-occurrence table

 73

Project 3D statistics

Detailed statistics for all classes in pointcloud or episodes project

 73

Import PDF as Images

Drag and drop PDFs to import pages as images to Supervisely

 71

Labelbox to Supervisely Migration Tool

Convert and copy multiple Labelbox projects into Supervisely at once.

 70

Add properties to image from CSV

Match image tag with CSV columns and add row values to image

 67

Labeling Consensus for Videos

Compare annotations of multiple labelers

 65

Import CVAT

Import images and videos with annotations in CVAT format.

 64

Copy team between instances

Copy team from one Supervisely Instance to another (including workspaces, team members and team files)

 63

Hello World!

Demonstrates how to turn your python script into Supervisely App

 63

Labeler First Time Through

First Time Through ratio shows how many items labeler annotated right the first time (i.e. reviewer accepted his work on first round).

 60

Transfer Assets between Instances

Transfer and filter assets(images) between Supervisely instances