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images

159 results found
 1M+

Basic Image labeling tool

complete solution for image annotation

 204K+

Advanced Image labeling tool

complete solution for image annotation with advanced features

 124K+

Import Images

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

 36K+

Export as masks

For semantic and instance segmentation tasks

 21K+

Export to Supervisely format

images and JSON annotations

 19K+

Import images in Supervisely format

Images with corresponding annotations

 6K+

Convert Supervisely to YOLO v5 format

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

 5K+

Convert YOLO v5 to Supervisely format

Transform YOLO v5 format to supervisely project

 5K+

Import images from cloud storage

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

 4K+

Export to COCO

Converts Supervisely to COCO format and prepares tar archive for download

 4K+

Import Images from CSV

Upload images using .CSV file

 3K+

Export only labeled items

Export only labeled items and prepares downloadable tar archive

 3K+

Clone

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

 3K+

Train YOLOv5

Dashboard to configure and monitor training

 2K+

Import images with masks

Import images with binary masks as annotations

 2K+

Export to Pascal VOC

Converts Supervisely Project to Pascal VOC format

 2K+

NN Image Labeling

Use deployed neural network in labeling interface

 2K+

Apply NN to Images Project

NN Inference on images in project or dataset

 2K+

Export activity as csv

Download activity as csv file

 1K+

Import dicom studies

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

 1K+

Serve YOLOv5

Deploy model as REST API service

 1K+

Merge datasets

Merge selected datasets with images or videos into a single one

 1K+

Convert Class Shape

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

 1K+

Videos project to images project

Creates images project from video project

 1K+

Classes stats for images

Detailed statistics for all classes in images project

 1K+

Extract frames from videos

Read every n-th frame and save to images project

 1K+

Assign train/val tags to images

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

 1K+

Import Pascal VOC

Import public or custom data in Pascal VOC format to Supervisely

 1K+

Train MMDetection

Dashboard to configure, start and monitor training

 1K+

Remote import

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

 992

Import from Google Cloud Storage

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

 917

RITM interactive segmentation SmartTool

State of the art object segmentation model in Labeleing Interface

 829

Create Trainset for SmartTool

Prepare training data for SmartTool

 781

Import COCO

Converts COCO format to Supervisely

 780

Merge classes

Merge multiple classes with same shape to a single one

 735

Export to Cityscapes

Converts Supervisely annotations to Cityscapes format and prepares downloadable tar archive

 724

Metric Learning Labeling Tool

Use metric learning models to classify images

 714

Export to DOTA

Export images in DOTA format and prepares downloadable archive

 695

Filter images

Filters images and provides results in selected format

 658

Train MMSegmentation

Dashboard to configure, start and monitor training

 582

AI assisted classification

Use neural network in labeling interface to classify images and objects

 572

Serve MMDetection

Deploy model as REST API service

 551

Train Detectron2

Dashboard to configure, start and monitor training

 536

Copy project between instances

Copies images + annotations + images metadata

 516

Flying objects

Generate synthetic data: flying foregrounds on top of backgrounds

 501

Train UNet

Dashboard to configure, start and monitor training

 463

Train MMClassification

Dashboard to configure, start and monitor training

 457

CSV Products Catalog to Images Project

Convert .CSV catalog to Images Project

 404

Import Cityscapes

Import Cityscapes to Supervisely

 402

ilastik pixel classification

Image Pixel Classification using ilastik

 396

Export to YOLOv8 format

Transform Supervisely format to YOLOv8 format

 395

ImgAug Studio

Visualize and build augmentation pipeline with ImgAug

 386

Batched Smart Tool

Batched smart labeling tool for Images

 373

Serve Detectron2

Deploy model as REST API service

 346

Diff and Merge Project Meta

Visual diff and merge tool helps compare project tags and classes

 346

Diff and Merge Images Projects

Visual diff and merge tool helps compare images in two projects

 335

Object Size Stats

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

 329

Sliding window split

Configure, preview and split images and annotations with sliding window

 302

Objects thumbnail preview

Review images annotations object by object with ease

 300

Apply Classifier to Images Project

Apply Classifier to Images Project

label project images or objects using NN

 291

Serve MMSegmentation

Deploy model as REST API service

 259

Classes co-occurrence matrix

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

 244

Unpack AnyShape Classes

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

 243

Crop objects on images

Creates new project with cropped objects

 239

Images project to videos project

Creates video project from images project

 236

Resize images

for both images and their annotations

 222

Interactive objects distribution

Explore images with certain number of objects of specific class

 215

Export Metadata

Export Images Metadata from Project

 207

Rasterize objects on images

Convert classes to bitmap and rasterize objects without intersections

 202

Serve MMClassification

Deploy model as REST API service

 187

Object detection metrics

Interactive Confusion matrix, mAP, ROC and more

 178

Serve UNet

Deploy model as REST API service

 178

Serve Segment Anything Model

Deploy model as REST API service

 161

Train RITM

Dashboard to configure, start and monitor training

 160

Export YOLOv5 weights

to TorchScript and ONNX formats

 153

Apply Detection and Classification Models to Images Project

Label project images using detector and classify predicted boxes

 141

Visual Tagging

Assign tags to images using example images

 140

Images thumbnail preview

Preview images as a grid gallery

 124

Import Metadata

Import Metadata for Images in Project

 120

Object tags editor

Edit tags of each object on image

 120

Explore data with embeddings

Calculate and visualize embeddings

 104

Render video from images

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

 104

Split datasets

Split one or multiple datasets into parts

 96

AI Recommendations

Recommends matching items from the catalog

 93

Convert to semantic segmentation

Convert polygon and bitmap labels to semantic segmentation

 92

Import images groups

Import images groups connected via user defined tag

 91

Serve ClickSEG

Deploy ClickSEG models for interactive instance segmentation

 84

EiSeg interactive segmentation SmartTool

SmartTool integration of Efficient Interactive Segmentation (EISeg)

 82

Unpack key value tags

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

 82

Semantic Segmentation Metrics

Semantic Segmentation Metrics

interactive metrics analysis

 77

Embeddings Calculator

Calculate embeddings for images project

 77

Export project to cloud storage

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

 76

Serve Metric Learning

Google landmarks challenge models

 76

Labels spatial distribution

Build labels distribution heatmap for dataset.

 76

Serve OWL-ViT

Deploy model as REST API service

 74

Create foreground mask

Create foreground mask from alpha channel of image

 67

Render video to compare projects

Put images with labels into collage and renders comparison videos

 67

Pexels downloader

Downloads images from the Pexels to the dataset.

 60

Prompt-based Image Filtering with CLIP

Filter and rank images by text prompts with CLIP models

 59

Sliding window merge

Merge images and labels that were split by sliding window before

 55

Review labels side-by-side

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

 55

Classification metrics

Evaluate your classification model

 52

Serve ViTPose

Deploy model as REST API service

 51

Tag images by dataset name

Add dataset name tag to all images in project or dataset

 50

Tags co-occurrence matrix

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

 50

Synthetic retail products

Generate synthetic data for classification of retail products on grocery shelves

 47

Create JSON with reference items

Objects with specific tag will be treated as reference items

 47

Convert labels to rotated bboxes

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

 47

Apply Detection and Pose Estimation Models to Images Project

Label project images using detector and pose estimator

 45

Download images

Download images from project or dataset.

 40

Tags to image URLs

Saves tag to images mapping to a json file

 39

Add properties to image from CSV

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

 38

Copy image tags to objects

Tags and object classes can be customized

 35

Rotate images

Rotates images along with the annotations in the dataset

 31

Perspective transform using QR code

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

 27

Group nested objects

Binds nested objects into groups

 27

Apply Object Segmentor to Images Project

Label project images using object segmentor

 26

Movie genre from its poster

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

 26

Import COCO Keypoints

Converts COCO Keypoints format to Supervisely

 25

Serve IS-Net

Deploy model as REST API service

 24

Tags to object classes

Create new object classes from tags associated with objects

 22

Apply OWL-ViT To Images Project

Class-angnostic object detection model

 22

Apply VIAME

Apply pretrained models for underwater species detection

 22

Transfer Images between Instances

Transfer and filter images between Supervisely instances

 15

Object classes to tags

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

 15

Create project from template

Create a new empty project with a meta of original project

 15

Flickr downloader

Downloads images from the Flickr to the dataset.

 14

Download image links in CSV

Download CSV file with download links for images

 13

Mark Reference Objects for Retail

Mark Reference Objects for Retail

Prepare examples for products from catalog

 13

Merge Tags

Merge Tags in videos or images project

 12

Export to COCO mask

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

 9

Slice volume

Slice volumes to 2d images

 8

Retail Tagging

Retail Tagging

Supports multi-user mode

 7

Serve InSPyReNet

Deploy InSPyReNet for salient object segmentation as a REST API service

 5

Stable diffusion UI

Run Stable Diffusion model with User Interface

 3

Serve SelfReformer

Deploy SelfReformer for salient object segmentation as a REST API service

 3

Instance Segmentation Metrics

Interactive evaluation of your instance segmentation model

 1

Review Retail Tags

Review Retail Tags

Review and correct tags (supports multi-user mode)

 1

Serve Transfiner

Deploy Transfiner for instance segmentation as a REST API service

 1

Import image projects in Supervisely format from cloud storage

Import image projects in Supervisely format from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)

 292

Persons

Persons

Image project with person instances

 222

Lemons (Annotated)

Lemons (Annotated)

6 images with annotated lemons and kiwifruits

 77

Country Roads

Country Roads

Labeled roads (sample: 100 images, full version: 1000 images)

 59

Lemons (Test)

Lemons (Test)

Sample images project without labels

 59

Demo Images

Demo Images

17 unlabeled images for quick tests

 42

Grocery store shelves

Labeled images of products on the shelve: snacks, chips, crisps

 34

Roads (Annotated)

Roads (Annotated)

10 images with labeled road

 31

Country Roads (Test)

Country Roads (Test)

594 unlabeled images

 24

PascalVOC GT Masks (Sample)

PascalVOC GT Masks (Sample)

726 sample gt-labeled images

 19

Seeds

Seeds

Unlabeled images: sunflower / pumpkin (peeled + unpeeled) / mix

 14

PascalVOC GT BBoxes (Sample)

PascalVOC GT BBoxes (Sample)

1171 sample gt-labeled images

 13

Snacks catalog

Snacks catalog

Labeled images: snacks: chips / crisps / mix

 13

Tomatoes (Annotated)

Tomatoes (Annotated)

Project with 66 annotated tomatoes (424 images)

 12

Cats quiz

Cats quiz

What breed is this cat? demo for visual tagging app

 9

Roads (Test)

Roads (Test)

156 unlabeled images with roads

 9

PascalVOC PRED Masks (Sample)

PascalVOC PRED Masks (Sample)

726 sample pred-labeled images

 8

Top 10 cat breeds

Top 10 cat breeds

Tag (name of breed) is assigned to every image

 7

PascalVOC PRED BBoxes (Sample)

PascalVOC PRED BBoxes (Sample)

1171 sample prediction-labeled images

 3

Images with alpha channel

Images with alpha channel

Illustrates alpha support in Supervisely