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AI-Powered Data Annotation

Save time & resources with smart tools for polygon selection, frame-to-frame predictive labeling, & automated object recognition.

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SmartPoly Object Selection

Save time labeling polygons for instance segmentation by drawing a simple rectangle that resolves to an object.

mtn dew bottle tracking

TrackForward Labeling

Track a labeled objects from frame-to-frame to automatically apply polygons or bounding boxes.

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AutoLabel Common Classes

Select common objects to recognize and Sense will use pre-trained models to automatically apply labels. 

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Label Your Data Faster, Smarter, Better

A full set of features to equip all your computer vision labeling projects. Sense Data Annotation is designed to maximize productivity and scale.

1. Ingest Data

Connect to multiple sources from Amazon S3, Google Cloud Storage, or local files. Apply filters & create data subsets for projects.

2. Define Labels

Configure labels for your dataset. Select from: Rectangle, Polygon, Point, Feature Points, Text, Classification

3. Label Data

Use AI-Powered tools for fast & easy smart polygon selection, frame-to-frame object tracking, & common object auto-labeling

4. Export Datasets

Export labeled data to the format you need including COCO, Pascal VOC, YOLO, Create ML, or Sense’s own flexible JSON format

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Flexible Label Types

Sense supports all major definitions used in computer vision labeling. Choose from Rectangles, Polygons, Point, Feature Points, Text, Class, or Multi-Class.

object detection labeling


Draw boxes to detect specific objects within images.

Image Segmentation labeling


Segment objects for detection within image frames.

Feature point labeling

Feature Points

Use for highly detailed detection such as emotion & body pose.

object detection labeling


Leverage for free text production for image captions ideal for accessibility.

Multi-Class labeling


Apply for image classification & attribute identification.

Construction Computer Vision


Add sub-labels into the label definitions for rectangles, polygons, and point labels.

Easy Exports

Sense Data Annotation supports the most common label formats for computer vision. Choose to export as COCO, Pascal VOC, YOLO, Create ML or Sense’s own JSON format.

Image Segmentation labeling


A large-scale object detection, segmentation, and captioning dataset

Pascal VOC

Pattern Analysis, Statistical Modeling and Computational Learning Visual Object Classes

object detection labeling


“You Only Look Once”. A popular real-time object detection algorithm

Create ML Support

Create ML

Apple’s machine learning model creation and training framework

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Sense JSON

Sense’s format is a schema defined JSON document containing all Sense label elements. Sense also includes metadata about the image and source video if applicable.

Team Collaboration

Sense Data Annotation makes labeling as a team easy. Add new members, sync data sources across teams, manage roles, provide labeling instructions, add comments, review labeling progress and time spent per label.

object detection labeling

Cloud Sync

Sync data sources across teams

Multi-Class labeling


Add labeling and project details

Construction Computer Vision

Project Review

Approve or reject labels & track progress

Data Source Connections

Connect both local storage and remote data sources to projects.

Supported image formats: JPG, PNG, GIF, BMP, TIFF, WEBP
Supported video formats from S3 & GCS : AVI, FLV, MKV, MOV, MP4, OGG, WEBM

object detection labeling

Amazon S3

Connect an Amazon S3 bucket

Create ML Support

Google Cloud Storage

Connect a GCP bucket

object detection labeling

Local Assets

Upload files for labeling

Create ML Support

Local CSV

Use a CSV file to upload assets

Get Started for FREE

No matter the size of your labeling projects, if you’re an expert, or just getting started with machine learning, Sense provides the speed, automation, and ease you need.