2M+ 
Advanced Image labeling tool
complete solution for image annotation with advanced features
images
238 results found
1M+ 
Basic Image labeling tool
complete solution for image annotation
156K+ 
Import Images
Drag and drop images to Supervisely, supported formats: .jpg, .jpeg, jpe, .mpo, .bmp, .png, .tiff, .tif, .webp, .nrrd
45K+ 
Export as masks
For semantic and instance segmentation tasks
44K+ 
Export to Supervisely format
images and JSON annotations
25K+ 
Import images in Supervisely format
Images with corresponding annotations
19K+ 
Clone
Clone project or dataset to selected workspace or project, works with all project types: images / videos / 3d / dicom
14K+ 
Convert Supervisely to YOLO v5 format
Transform project to YOLO v5 format and prepares tar archive for download
11K+ 
Export to YOLOv8 format
Transform Supervisely format to YOLOv8 format
11K+ 
Export to COCO
Converts Supervisely to COCO format and prepares tar archive for download
8K+ 
Train YOLOv8 | v9 | v10 | v11
Dashboard to configure, start and monitor YOLOv8 | v9 | v10 | v11 training
8K+ 
Apply NN to Images Project
NN Inference on images in project or dataset
8K+ 
Export only labeled items
Export only labeled items and prepares downloadable tar archive
8K+ 
NN Image Labeling
Use deployed neural network in labeling interface
7K+ 
Convert YOLO v5 to Supervisely format
Transform YOLO v5 format to supervisely project
5K+ 
Train YOLOv5
Dashboard to configure and monitor training
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+ 
Export to Pascal VOC
Converts Supervisely Project to Pascal VOC format
4K+ 
Import images with masks
Import images with binary masks as annotations
4K+ 
Download images
Download images from project or dataset.
4K+ 
Serve YOLOv8 | v9 | v10 | v11
Deploy YOLOv8 | v9 | v10 | v11 as REST API service
3K+ 
Merge datasets
Merge selected datasets with images or videos into a single one
3K+ 
Convert Class Shape
Converts shapes of classes (e.g. polygon to bitmap) and all corresponding objects
3K+ 
Export activity as csv
Download activity as csv file
3K+ 
Import COCO
Converts COCO format to Supervisely
3K+ 
Videos project to images project
Creates images project from video project
3K+ 
RITM interactive segmentation SmartTool
State-of-the art object segmentation model in Labeling Interface
2K+ 
Serve YOLOv5
Deploy model as REST API service
2K+ 
Assign train/val tags to images
Assigns tags (train/val) to images. Training apps will use these tags to split data.
2K+ 
Train MMSegmentation
Dashboard to configure, start and monitor training
2K+ 
Import DICOM studies
Creates project with images grouped by selected metadata, converting DICOM data to NRRD format in the process.
2K+ 
ML Pipelines
Drag and drop interface for building custom DataOps pipelines
2K+ 
Filter images
Filters images and provides results in selected format
2K+ 
Metric Learning Labeling Tool
Use metric learning models to classify images
2K+ 
Serve Segment Anything Model
Deploy model as REST API service
2K+ 
Train MMDetection 3.0
Training dashboard for mmdetection framework (v3.0.0 and above).
2K+ 
Classes stats for images
Detailed statistics for all classes in images project
1K+ 
Merge classes
Merge multiple classes with same shape to a single one
1K+ 
Export COCO Keypoints
Converts Supervisely format to COCO Keypoints
1K+ 
Extract frames from videos
Read every n-th frame and save to images project
1K+ 
Serve Segment Anything 2.1
Deploy SAM 2 model as REST API service
1K+ 
Train MMDetection
Dashboard to configure, start and monitor training
1K+ 
Serve ClickSEG
Deploy ClickSEG models for interactive instance segmentation
1K+ 
Import Pascal VOC
Import public or custom data in Pascal VOC format to Supervisely
1K+ 
Train UNet
Dashboard to configure, start and monitor training
1K+ 
Train Detectron2
Dashboard to configure, start and monitor training
1K+ 
Serve MMSegmentation
Deploy model as REST API service
1K+ 
Train MMClassification
Dashboard to configure, start and monitor training
1K+ 
AI assisted classification
Use neural network in labeling interface to classify images and objects
1K+ 
Create Trainset for SmartTool
Prepare training data for SmartTool
1K+ 
Serve MMDetection
Deploy model as REST API service
1K+ 
Remote import
Connect your remote storage and import data without duplication. Data is stored on your server but visible in Supervisely
1K+ 
Export to DOTA
Export images in DOTA format and prepares downloadable archive
1K+ 
Serve OWL-ViT
Class-agnostic interactive detection for auto-prelabeling
1K+ 
Sliding window split
Configure, preview and split images and annotations with sliding window
1K+ 
Import from Google Cloud Storage
Upload images by reading links (Google Cloud Storage) from CSV file
1K+ 
Copy project between instances
Copies images + annotations + images metadata
1K+ 
Split datasets
Split one or multiple datasets into parts
1K+ 
Export to COCO mask
Converts annotations from Supervisely to COCO format as RLE masks with preserving holes
1K+ 
Train RITM
Dashboard to configure, start and monitor training
996 
ImgAug Studio
Visualize and build augmentation pipeline with ImgAug
939 
Serve MMDetection 3.0
Deploy MMDetection 3.0 model as a REST API service
930 
Download image links in CSV
Download CSV file with download links for images
918 
Export to Cityscapes
Converts Supervisely annotations to Cityscapes format and prepares downloadable tar archive
915 
Serve Segment Anything in High Quality
Run HQ-SAM and then use in labeling tool
869 
Apply Classifier to Images Project
Apply Classifier to Images Project
label project images or objects using NN
854 
Flying objects
Generate synthetic data: flying foregrounds on top of backgrounds
846 
Crop objects on images
Creates new project with cropped objects
825 
Serve Detectron2
Deploy model as REST API service
789 
CSV Products Catalog to Images Project
Convert .CSV catalog to Images Project
780 
Batched Smart Tool
Batched smart labeling tool for Images
771 
Evaluator for Model Benchmark
Evaluate the performance of the NN model and compare it with the results of other models
756 
Apply OWL-ViT To Images Project
Class-angnostic object detection model
736 
Train YOLO v8 - 26
Train YOLO models on your data
715 
Resize images
for both images and their annotations
681 
Serve ViTPose
Deploy model as REST API service
656 
Object detection metrics
Interactive Confusion matrix, mAP, ROC and more
651 
Diff and Merge Images Projects
Visual diff and merge tool helps compare images in two projects
630 
Serve MMClassification
Deploy model as REST API service
619 
Diff and Merge Project Meta
Visual diff and merge tool helps compare project tags and classes
610 
Export Items After Review
Export items after the passing labeling job review
601 
Object Size Stats
Detailed statistics and distribution of object sizes (width, height, area)
579 
Apply Detection and Pose Estimation Models to Images Project
Label project images using detector and pose estimator
561 
Rasterize objects on images
Convert classes to bitmap and rasterize objects without intersections
536 
Import Cityscapes
Import Cityscapes to Supervisely
533 
Import Metadata
Import Metadata for Images in Project
522 
Serve Metric Learning
Google landmarks challenge models
518 
ilastik pixel classification
Image Pixel Classification using ilastik
507 
Pexels downloader
Downloads images and videos from Pexels.
477 
Embeddings Calculator
Calculate embeddings for images project
474 
AI Recommendations
Recommends matching items from the catalog
444 
Predict App
This app applies neural networks to images. It supports various neural network tasks such as object detection, semantic segmentation, and instance segmentation.
426 
Explore data with embeddings
Calculate and visualize embeddings
404 
Serve YOLO v8 - 26
Deploy YOLO models as a REST API service
393 
Train HRDA
Train HRDA model for segmentation in semi-supervised mode
387 
Unpack AnyShape Classes
Split "AnyShape" classes to classes with strictly defined shapes (polygon, bitmap, ...)
387 
Serve RT-DETRv2
Deploy RT-DETRv2 as a REST API service
384 
Images project to videos project
Creates video project from images project
384 
Convert to semantic segmentation
Convert polygon and bitmap labels to semantic segmentation
384 
Instance Segmentation Metrics
Interactive evaluation of your instance segmentation model
382 
Serve UNet
Deploy model as REST API service
376 
Sliding window merge
Merge images and labels that were split by sliding window before
375 
Visual Tagging
Assign tags to images using example images
375 
Import Multiview Image Groups
Import multiview image groups connected via user defined tag
373 
Train RT-DETRv2
Train RT-DETRv2 model on your data
371 
Merge Image Projects
Merge multiple image projects into a single one
370 
Apply Detection and Classification Models to Images Project
Label project images using detector and classify predicted boxes
369 
Object tags editor
Edit tags of each object on image
354 
Classes co-occurrence matrix
Explore images for every combination of classes pairs in co-occurrence table
354 
Rotate images
Rotates images along with the annotations in the dataset
351 
Objects thumbnail preview
Review images annotations object by object with ease
349 
Export Metadata
Export Images Metadata from Project
343 
Anonymize Data
App to obscure data on images and videos
340 
Tags to object classes
Create new object classes from tags associated with objects
332 
Semantic Segmentation Metrics
Semantic Segmentation Metrics
interactive metrics analysis
330 
Roboflow to Supervisely Migration Tool
Convert and copy multiple Roboflow projects into Supervisely at once.
311 
Export project to cloud storage
Export project to Google Cloud Storage, Amazon S3, Microsoft Azure, ...
287 
Review labels side-by-side
Filter objects and tags by user and copy them to working area
286 
Convert labels to rotated bboxes
Convert all labels in the project or dataset to rotated bounding boxes
285 
Prompt-based Image Filtering with CLIP
Filter and rank images by text prompts with CLIP models
278 
Create JSON with reference items
Objects with specific tag will be treated as reference items
276 
Image Classification Metrics
Evaluate your classification model
276 
Apply Object Segmentor to Images Project
Label project images using object segmentor
271 
Render video from images
Creates video from images in dataset with selected frame rate and configurable label opacity
271 
Interactive objects distribution
Explore images with certain number of objects of specific class
266 
Train DEIMv2
Train DEIMv2 models on your data
260 
Serve Segment Anything 3
Deploy SAM 3 model as REST API service
259 
Train MMClassification V2 (MMPretrain)
Dashboard to configure, start and monitor training
245 
Tag images by dataset name
Add dataset name tag to all images in project or dataset
232 
Export YOLOv5 weights
to TorchScript and ONNX formats
229 
Fine-tune Segment Anything 2.1
Dashboard for SAM 2.1 fine-tuning
221 
EiSeg interactive segmentation SmartTool
SmartTool integration of Efficient Interactive Segmentation (EISeg)
218 
Labels spatial distribution
Build labels distribution heatmap for dataset.
199 
Render video to compare projects
Put images with labels into collage and renders comparison videos
199 
Import COCO Keypoints
Converts COCO Keypoints format to Supervisely
191 
Train YOLOv5 2.0
Dashboard to configure, start and monitor YOLOv5 2.0 training
187 
Images thumbnail preview
Preview images as a grid gallery
157 
Labeling Consensus
Compare annotations of multiple labelers
155 
Group nested objects
Binds nested objects into groups
147 
Create foreground mask
Create foreground mask from alpha channel of image
147 
Import PDF as Images
Drag and drop PDFs to import pages as images to Supervisely
137 
Import Multispectral Images
Import multispectral images as channels or as separate images.
132 
Serve HRDA
Deploy HRDA model for inference
132 
Conveyor Belt Auto Tracking
Effortlessly track and interpolate labeled objects on a conveyor belt in real-time
125 
Sample images from project
Sample images from project with different methods
120 
MMOCR Inference
Text Detection and Recognition on images
116 
Import CVAT
Import images and videos with annotations in CVAT format.
116 
Train RT-DETR
Train RT-DETR model on your data
115 
Group Images for Multiview Labeling
No description available
114 
Unpack key value tags
Rename "Key:Value" tags to key_value (fruit: lemon -> fruit_lemon)
113 
Add properties to image from CSV
Match image tag with CSV columns and add row values to image
108 
Tags to image URLs
Saves tag to images mapping to a json file
102 
Export to Supervisely Blob
Export images project to extended Supervisely format with Blobs
101 
Synthetic retail products
Generate synthetic data for classification of retail products on grocery shelves
101 
Merge Tags
Merge Tags in videos or images project
99 
Labelbox to Supervisely Migration Tool
Convert and copy multiple Labelbox projects into Supervisely at once.
98 
Annotation Validator
Validate annotations in a project
94 
Tags co-occurrence matrix
Explore images for every combination of tags pairs in co-occurrence table
93 
Serve DEIMv2
Deploy DEIMv2 models as a REST API service
86 
Apply Florence-2 + SAM 2 to Images Project
Text-Prompted Object Detection with Mask Segmentation
84 
Mark Reference Objects for Retail
Mark Reference Objects for Retail
Prepare examples for products from catalog
83 
Serve YOLOv5 2.0
Deploy YOLOv5 2.0 as REST API service
81 
Serve MMClassification V2 (MMPretrain)
Deploy model as REST API service
76 
Serve Florence-2
Deploy Florence-2 as a REST API service
75 
Import image projects in Supervisely format from cloud storage
Import image projects in Supervisely format from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)
73 
Copy image tags to objects
Tags and object classes can be customized
70 
Multiview Object Matching
Propagate bboxes to multiview images group
69 
Real-time Labeling Quality Check
Automated real-time annotation tests.
68 
Transfer Assets between Instances
Transfer and filter assets(images) between Supervisely instances
66 
Perspective transform using QR code
This app perspective transforms and warps your images using qr code in them.
61 
Create project from template
Create a new empty project with a meta of original project
59 
Serve IS-Net
Deploy model as REST API service
59 
V7 to Supervisely Migration Tool
Convert and copy multiple V7 datasets into Supervisely at once.
54 
Stable diffusion UI
Run Stable Diffusion model with User Interface
53 
Slice volume
Slice volumes to 2d images
52 
Object classes to tags
Convert each class name to tag associated with objects, and merge existing classes into single one
52 
CVAT to Supervisely Migration Tool
Convert and copy multiple CVAT projects into Supervisely at once.
51 
Review Image Annotations in Batches
Allows you to review annotation results in a user interface specifically designed for such tasks
51 
Download Project Meta
Download project meta of Supervisely project for any modality.
49 
Flickr downloader
Downloads images from the Flickr to the dataset.
49 
Compare Models
Compare Models
Compare the results of different model evaluations
48 
Import V7
Import images and videos with annotations in V7 format.
48 
Multi-Team Labeling Workflow
Creates an automated sequential labeling workflow with a lot of teams.
47 
Export YOLOv8 weights
to TorchScript and ONNX formats
46 
Serve InSPyReNet
Deploy InSPyReNet for salient object segmentation as a REST API service
45 
Serve Matte Anything
Deploy Matte Anything as REST API service
44 
Fine-tune Segment Anything 3
Dashboard for SAM 3 fine-tuning
42 
Serve RT-DETR
Deploy RT-DETR as a REST API service
39 
Serve Grounding DINO
Deploy Grounding DINO as a REST API service
34 
Object Classification Metrics
Evaluate your classification model in Detector + Classifier Pipeline
33 
Apply VIAME
Apply pretrained models for underwater species detection
31 
Train SparseInst
Dashboard to configure, start and monitor SparseInst training
30 
Movie genre from its poster
Application imports kaggle dataset 'Movie genre from its poster' as supervisely project
30 
Anomaly Sorter
Application based on Supervisely Solution engine for sorting all possible anomalies and automatically tagging only accepted anomalies.
29 
Visualize Image Updates
Application that visualizes the most recently updated images
23 
Serve Transfiner
Deploy Transfiner for instance segmentation as a REST API service
22 
Train MaskDINO
Dashboard to configure, start and monitor MaskDINO training
20 
Serve Kosmos-2
Deploy Kosmos-2 as a REST API service
18 
Retail Tagging
Retail Tagging
Supports multi-user mode
