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apps

Apps help you extend functionality with custom UI

204 results found

Import Images

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

Export as masks

For semantic and instance segmentation tasks

Export to Supervisely format

images and JSON annotations

Import images in Supervisely format

Images with corresponding annotations

Import Videos

Import Videos without annotations to Supervisely

Import Pointclouds PCD

Import pointclouds in PCD format without annotations

Convert Supervisely to YOLO v5 format

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

Export pointclouds project in Supervisely format

Export pointclouds project and prepares downloadable tar archive

Export videos project in Supervisely format

Export videos project and prepares downloadable tar archive

Convert YOLO v5 to Supervisely format

Transform YOLO v5 format to supervisely project

Import images from cloud storage

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

Export to COCO

Converts Supervisely to COCO format and prepares tar archive for download

Import Images from CSV

Upload images using .CSV file

Export only labeled items

Export only labeled items and prepares downloadable tar archive

Clone

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

Train YOLOv5

Dashboard to configure and monitor training

Import images with masks

Import images with binary masks as annotations

Import videos from cloud storage

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

Export to Pascal VOC

Converts Supervisely Project to Pascal VOC format

NN Image Labeling

Use deployed neural network in labeling interface

Apply NN to Images Project

NN Inference on images in project or dataset

Import videos in Supervisely format

Import videos with annotations in Supervisely format

Export activity as csv

Download activity as csv file

Import dicom studies

Convert DICOM data to nrrd format and creates a new project with images grouped by selected metadata

Import Pointcloud Episodes

Import Pointcloud Episodes with Annotations and Photo context

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

Import Pointclouds PLY

Import pointclouds without annotations in .ply format from Team Files

Merge datasets

Merge selected datasets with images or videos into a single one

Convert Class Shape

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

Videos project to images project

Creates images project from video project

Classes stats for images

Detailed statistics for all classes in images project

Extract frames from videos

Read every n-th frame and save to images project

Assign train/val tags to images

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

Import Pascal VOC

Import public or custom data in Pascal VOC format to Supervisely

Train MMDetection

Dashboard to configure, start and monitor training

Remote import

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

Import from Google Cloud Storage

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

Export Pointcloud Episodes in Supervisely format

Export project or dataset in Supervisely pointcloud episode format

RITM interactive segmentation SmartTool

State of the art object segmentation model in Labeleing Interface

Create Trainset for SmartTool

Prepare training data for SmartTool

Merge classes

Merge multiple classes with same shape to a single one

Import COCO

Converts COCO format to Supervisely

Export to Cityscapes

Converts Supervisely annotations to Cityscapes format and prepares downloadable tar archive

TransT object tracking (CVPR2021)

TransT object tracking (CVPR2021)

serve and use in videos annotator

Metric Learning Labeling Tool

Use metric learning models to classify images

Import DICOM Volumes

Import volumes in DICOM and NRRD formats without annotations

Export to DOTA

Export images in DOTA format and prepares downloadable archive

Apply 3D Detection to Pointcloud Project

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

Filter images

Filters images and provides results in selected format

Train MMSegmentation

Dashboard to configure, start and monitor training

Export volumes in Supervisely format

Export project or dataset in Supervisely volumes format

AI assisted classification

Use neural network in labeling interface to classify images and objects

Serve MMDetection

Deploy model as REST API service

Export to KITTI 3D

Converts Supervisely Pointcloud format to KITTI 3D

Train Detectron2

Dashboard to configure, start and monitor training

Apply NN to Videos Project

NN Inference on videos in project or dataset

Copy project between instances

Copies images + annotations + images metadata

Flying objects

Generate synthetic data: flying foregrounds on top of backgrounds

Render Video Labels to MP4

Creates presentation mp4 file based on labeled video

Import Pointcloud Project

Import Pointcloud Project with Annotations and Photo context in Supervisely format

Train UNet

Dashboard to configure, start and monitor training

Train MMClassification

Dashboard to configure, start and monitor training

CSV Products Catalog to Images Project

Convert .CSV catalog to Images Project

Import Volumes in Supervisely format

Import Supervisely volumes project with annotations

Labeling Jobs Stats

General statistics for all labeling jobs in team

Import Cityscapes

Import Cityscapes to Supervisely

ilastik pixel classification

Image Pixel Classification using ilastik

Serve MMDetection3D

Deploy model as REST API service

ImgAug Studio

Visualize and build augmentation pipeline with ImgAug

Batched Smart Tool

Batched smart labeling tool for Images

Serve Detectron2

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

Export to YOLOv8 format

Transform Supervisely format to YOLOv8 format

While True Script

While True Script

Used to create infinite task for debug

Diff and Merge Images Projects

Visual diff and merge tool helps compare images in two projects

Diff and Merge Project Meta

Visual diff and merge tool helps compare project tags and classes

Object Size Stats

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

Sliding window split

Configure, preview and split images and annotations with sliding window

Objects thumbnail preview

Review images annotations object by object with ease

Apply Classifier to Images Project

Apply Classifier to Images Project

label project images or objects using NN

Video objects stats for every class

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

Serve MMSegmentation

Deploy model as REST API service

Import KITTI 3D

Converts KITTI 3D format to Supervisely pointcloud format

Classes co-occurrence matrix

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

Unpack AnyShape Classes

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

Crop objects on images

Creates new project with cropped objects

Images project to videos project

Creates video project from images project

Resize images

for both images and their annotations

Interactive objects distribution

Explore images with certain number of objects of specific class

Export Metadata

Export Images Metadata from Project

Rasterize objects on images

Convert classes to bitmap and rasterize objects without intersections

Convert point clouds project to episodes

Creates sequence of connected point clouds with tracklets

Train MMDetection3D

Dashboard to configure, start and monitor training

Serve MMClassification

Deploy model as REST API service

Object detection metrics

Interactive Confusion matrix, mAP, ROC and more

Serve UNet

Deploy model as REST API service

Serve Segment Anything Model

Deploy model as REST API service

Jupyter datascience notebook

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

Export YOLOv5 weights

to TorchScript and ONNX formats

Train RITM

Dashboard to configure, start and monitor training

Mark segments on multi-camera videos

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

Apply Detection and Classification Models to Images Project

Label project images using detector and classify predicted boxes

Visual Tagging

Assign tags to images using example images

Images thumbnail preview

Preview images as a grid gallery

Import Metadata

Import Metadata for Images in Project

Import LAS/LAZ format

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

Object tags editor

Edit tags of each object on image

Explore data with embeddings

Calculate and visualize embeddings

Import KITTI-360

Import Pointcloud Episodes from KITTI-360 format

Render video from images

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

Split datasets

Split one or multiple datasets into parts

Volume Interpolation

Slicer 3D algorithms for volume interpolation

Action Recognition Labeling Tool

Label videos for Action Recognition task

Batched Smart Tool for Videos

Batched smart labeling tool for Videos

AI Recommendations

Recommends matching items from the catalog

Convert to semantic segmentation

Convert polygon and bitmap labels to semantic segmentation

Labeling Events Stats

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

Serve ClickSEG

Deploy ClickSEG models for interactive instance segmentation

PIPs object tracking

serve and use in videos annotator

EiSeg interactive segmentation SmartTool

SmartTool integration of Efficient Interactive Segmentation (EISeg)

Import images groups

Import images groups connected via user defined tag

Unpack key value tags

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

Semantic Segmentation Metrics

Semantic Segmentation Metrics

interactive metrics analysis

Import volumes from cloud storage

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

3D BBox Interpolation

3D BBox Interpolation

Deploy interpolation method as REST API service

Embeddings Calculator

Calculate embeddings for images project

Export project to cloud storage

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

Serve Metric Learning

Google landmarks challenge models

Serve OWL-ViT

Deploy model as REST API service

Create foreground mask

Create foreground mask from alpha channel of image

Labels spatial distribution

Build labels distribution heatmap for dataset.

Classic Labeling Queues

Annotate Project using Queues

Render video to compare projects

Put images with labels into collage and renders comparison videos

Pexels downloader

Downloads images from the Pexels to the dataset.

Import Volumes with Masks

Import Volumes with .nrrd masks to Supervisely

Sliding window merge

Merge images and labels that were split by sliding window before

Review labels side-by-side

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

Classification metrics

Evaluate your classification model

Prompt-based Image Filtering with CLIP

Filter and rank images by text prompts with CLIP models

Take fragment from video

Extract video fragment to selected project or dataset

Tag images by dataset name

Add dataset name tag to all images in project or dataset

Serve ViTPose

Deploy model as REST API service

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).

Synthetic retail products

Generate synthetic data for classification of retail products on grocery shelves

Tags co-occurrence matrix

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

Objects Interpolation on video

Track polygons, rectangles and points using linear interpolation

Create JSON with reference items

Objects with specific tag will be treated as reference items

Convert labels to rotated bboxes

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

Apply Detection and Pose Estimation Models to Images Project

Label project images using detector and pose estimator

Hello World!

Demonstrates how to turn your python script into Supervisely App

Import YouTube videos

Import videos by urls provided in text file

TAP-Net object tracking

serve and use in videos annotator

Invite users to team from CSV

Invite users to team

Change video framerate

Change video framerate with preserving duration (recodes video)

Tags to image URLs

Saves tag to images mapping to a json file

Project 3D statistics

Detailed statistics for all classes in pointcloud or episodes project

Add properties to image from CSV

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

Copy image tags to objects

Tags and object classes can be customized

Download images

Download images from project or dataset.

Convert Video Class Shape

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

Perspective transform using QR code

This app perspective transforms and warps your images using qr code in them.

Create users from CSV

Only instance admin has permissions to run it

Action Recognition Stats Tool

Analyse videos labeled for Action Recognition task

Import Videos from Team Files

Import selected videos from Team Files to selected destination

Rotate images

Rotates images along with the annotations in the dataset

Group nested objects

Binds nested objects into groups

Movie genre from its poster

Application imports kaggle dataset 'Movie genre from its poster' as supervisely project

Apply Object Segmentor to Images Project

Label project images using object segmentor

Serve IS-Net

Deploy model as REST API service

Tags to object classes

Create new object classes from tags associated with objects

Apply VIAME

Apply pretrained models for underwater species detection

Export volume project to cloud storage

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

Import COCO Keypoints

Converts COCO Keypoints format to Supervisely

Apply OWL-ViT To Images Project

Class-angnostic object detection model

Group reference objects into batches

Group items by selected columns from CSV catalog

Print Progress and Error

Print Progress and Error

Prints progress and then raises error

Serve Custom Detection Model Template

Template application to serve custom detection models

Transfer Images between Instances

Transfer and filter images between Supervisely instances

Object classes to tags

Convert each class name to tag associated with objects, and merge existing classes into single one

Create project from template

Create a new empty project with a meta of original project

Flickr downloader

Downloads images from the Flickr to the dataset.

While True App

While True App

nocode app that ignores soft stop

[beta] Serve OpenCV

[beta] Serve OpenCV

serve and use in videos annotator

Mark Reference Objects for Retail

Mark Reference Objects for Retail

Prepare examples for products from catalog

Merge Tags

Merge Tags in videos or images project

Synthetic videos for tracking

Synthesize videos on annotated data

Cleaner

Remove temporary files from Team files

Export to COCO mask

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

Slice volume

Slice volumes to 2d images

Tensorboard

Open metrics in tensorboard

Retail Tagging

Retail Tagging

Supports multi-user mode

Serve InSPyReNet

Deploy InSPyReNet for salient object segmentation as a REST API service

Download image links in CSV

Download CSV file with download links for images

Stable diffusion UI

Run Stable Diffusion model with User Interface

App Template (No GUI)

template for your headless app

Insert YouTube logo

Puts YouTube logo on all images in directory

Training tensorboard template

Simple integration of NN training with tensorboard support.

YouTube Downloader

Downloads and trim video from Youtube.

Serve SelfReformer

Deploy SelfReformer for salient object segmentation as a REST API service