This post was originally published by Jayita Bhattacharyya at Analytics India Magazine
Data annotation is the process of labelling images, video frames, audio, and text data that is mainly used in supervised machine learning to train the datasets that help a machine to understand the input and act accordingly. There are many types of annotations, some of them being – bounding boxes, polyline annotation, landmark annotation, semantic segmentation, polygon annotation, key points, 3D point cloud annotations, named entity recognition, etc.
With the advancements in deep learning algorithms, computer vision and NLP have greatly evolved and done wonders around the world of AI. Along with this AutoML has also grown. This has led many industries to adopt AI smoothly and make efficient use of it in various use cases.
There are many tools readily available for data annotation which can be utilised. Professional data annotators and labellers verify the annotations. Many of their platforms even offer end to end machine learning services from data loading, preprocessing, cleaning, data analysis/visualization, to deployment, production, and re-engineering. They also allow team coordination and management along with job assignments to each role.
In this article, I’ll be discussing these tools and at the end, there is a comprehensive table for guidance to services and solutions provided by each.
Different annotations tools
SuperAnnotate is an AI-powered image and video annotation platform. It has a partnership with OpenCV for its desktop version.
- Allows users to create high-quality training datasets providing annotations for computer vision tasks.
- Design projects work and distribute tasks among teams.
- Building large projects at scale.
- Using active learning to accurately annotate images.
- Annotations automation for predefined classes.
- Transfer learning to predict new classes.
- Use of QA automation to detect mislabeled annotations.
- Viewing analytics to keep track of annotation speed, quality.
To know more visit -> SuperAnnotate
Labelbox is an enterprise-grade platform providing solutions for training data with AI-enabled labeling tools for both image and text data, enabling labeling automation, integrating the human workforce, and data management. Has accessibility to a powerful API, along with Python SDK for extensibility.
- Best suited for commercial solutions with the features for creating and maintaining high-quality training data.
- Labeling tools for images, video text, and geospatial data.
- A standardized way for organizations to collaborate on the creation, manage, and review of data.
- Automation labeling to reduce costs, enhance the speed with QA.
- The external labeling service to support and maintain data quality with an internal labeling team.
To know more visit -> LabelBox
Playment helps ML teams build high-quality training data with ML-assisted tools, structured project management systems, expert human workforce, and much more. Provides solutions in image, video, and sensor annotation along with API integration to ML pipelines, and GT Studio.
- Has the best-in-class annotations for Lidar and Radar.
- A standardized way to manage high-quality training data for computer vision tasks.
- Has a Ground-truth Studio to serve data labeling for creating diverse, high-quality ground truth datasets at scale
- Streamline data pipelines to enable faster development of AI systems.
- Auto-scaling Workforce.
- Provisions for customized use cases.
To know more visit -> Playment
Clarifai is one of the leading data annotation platforms providing developers, data scientists, and enterprises with deep learning tools to build entire AI lifecycles for various products and use-cases.
- Workflow management
- API integration
- Wide range of computer vision and NLP tasks across various industries
- Provisions for custom and pre-trained AI models
- Nominal pricing as per usage
- Scalable deployment
- User-friendly UI/UX
- Quality assurance by professionals
To know more visit -> Clarifai
Datasaur is one of the best text annotation platforms providing AI-based solutions to extract, analyze, maintain, and modify text data.
- Datasaur uses NLP along with other ML-assisted tools to build high-quality training text data.
- Can detect misclassified content using automation tools
- Provide summarization and analysis
- Free usage up to 5000 labels per month with 100MB storage
- Optimized labeling interface, Fully programmatic project creation and export via API, Regular Expression extension, Automatic file converter, Data validation, and review.
- Team Management, Performance Dashboard, Data Privacy, Cloud sync
To know more visit -> Datasaur
Lightly uses one of the eminent deep learning algorithms called self-supervised learning techniques to enhance data labeling. It can improve ML models with its tools for data preparation and curation for vision data.
- Can perform image classification and image segmentation
- On-premise Docker service to store, manage and work efficiently
- Has both web app and Python API interfaces
- Build on top of PyTorch library.
- Performance measures of datasets through graph analysis
- Active feedback and support
- Free services up to 5000 private and 25000 public images
To know more visit -> Lightly
Hive provides enterprise AI solutions for industry-specific use-cases. Used in both computer vision and NLP tasks. Hive believes in an AI-as-a service platform.
- Data labelling by categorizing
- Entire workflow management with constant feedback and support until the final production
- Hive predict is Model-as-a-service providing predictions on visuals, audio, and text data
- Training data is customizable, flexible, and built with proper high-quality assurance.
To know more visit -> Hive
Lionbridge deals with all kinds of data Image, Video, Audio, Text, and Geospatial data for providing annotation and labeling services. It is one of the oldest companies in the market.
- Its text annotation has multilingual services covering many languages across the globe.
- Provides entire service from data collection to validation.
- Has open access to 300+ datasets
- Follows human-in-loop annotation format by crowdsourcing
- AI consulting
- Partnered and trusted by fortune 500 companies
To know more visit -> Lionbridge
V7 labs had launched V& darwin platform for data annotation and data labeling purposes. Darwin makes use of deep learning algorithms to generate state-of-the-art high- quality ground truth datasets.
- End to end services for computer vision tasks.
- Automated image annotation
- Use of active learning for training datasets
- Allows team collaboration and data visualization
- API and CLI tools availability along with Python SDK
- Complete model training pipeline
- Quality Review during the entire product lifecycle
To know more visit -> V7 Darwin
Amazon Sagemaker Ground Truth
AWS as we all know is a leading cloud service provider. Amazon Sagemaker Ground Truth is one of its products used for data labeling to generate ground truth datasets using the machine learning platform Amazon Sagemaker.
- Sagemaker GT can be integrated with Amazon Mechanical Turk
- Labelling goes through various processes assisted labelling by external and internal labellers
- Label verification, adjustment, and validation
- Flexible pricing
- Datasets are stored in S3(Amazon simple storage service) buckets
- Amazon CLI to download the annotated dataset
To know more visit -> Amazon Sagemaker Ground Truth
LightTag is another text annotation platform providing faster NLP services.
- Allow designation allotments for various tasks distributions in data annotation
- Performance dashboard for both data and annotators
- Evaluation metrics
- Review & QA.
To know more visit -> LightTag
Kili technology covers all the multimedia data for annotation and labelling at industry-specific levels.
- computer vision (image, video) or on NLP (text, pdf, voice) topics
- Allowance for on-boarding business experts & external workforce to scale projects.
- simple collaboration, quality control, data management, and labeling workforce
- Available online or on-premise
- ML with active learning, online learning, and semi-supervised learning
- Python Client GraphQL API
To know more visit -> Kili Technology
Dataturks is an AI startup later acquired by Walmart Labs. It helps developers and researchers in annotating an image, video, and text data.
- Open source datasets are available
- Generates real-time reports
- Enables crowdsourcing
- Has open-sourced GitHub repo
- Software support in Linux and Windows
- Complete API service to upload, process, and download data
To know more visit -> Dataturks
TagTog is another self-supervised text annotation tool.
- NLP modeling
- Text analytics, visualization, and annotation
- SMEs with domain-specific insights
- Provides moderation and customization
- Access to pre-annotated data
- Unicode support
- Multiple format support ( PDF, CSV, etc)
To know more visit -> tagtog
LinkedAI is a no-code AI-assisted mostly for computer vision annotation platform but also offers NLP services.
- Data labelling, and Data tagging
- generating synthetic data
- Quality checks by professionals
- Auto labelling services
- Annotations available in JSON and CSV
To know more visit -> LINKEDAI
Choose The suitable Data Annotator Tool
|Tool Name||Services Provided/Tools||Solutions/ Use Cases|
|SuperAnnotate||Image & VideoBounding boxes, Polylines, polygons, Cuboid, Ellipse, Line, Point||Aerial Imaging, Autonomous Driving, Retail, Security & Surveillance, Medical, Robotics.|
|LabelBox||Image, Video, Text, Geospatial data.bounding box, Points, superpixel, brush, eraser, polylines, Polygons, NER||Document data extraction, manufacturing, health, insurance, aerial, agriculture, transportation|
|Playment||Image, Video, Sensor2D & 3Dbounding box, polygons, cuboid, polylines, landmark, semantic & point cloud segmentation, 2D-3D object linking||Autonomous Vehicles, Human Pose Estimation and Tracking, Security surveillance, insurance, fashion, gaming, agriculture|
|Clarifai||Image, Video, Text.Single and Multilabel classification, bounding box, polyline, video tracking, NER, OCR, text moderation||E-commerce, hospitality, document analysis, user content monitoring, chatbots, aviation, tourism, OTT platforms, insurance, public sector, brick & mortar|
|Datasaur||Named Entity Recognition, Part-of-speech, Coreference Resolution,Dependency Resolution,Document Labelling, OCR||Finance, Healthcare, Legal, Media, E-commerce|
|Lightly||Image and VideoData augmentation, semantic segmentation||Autonomous Vehicles, Visual Inspection, Medical Imagery, Geospatial Data|
|Hive||Image, audio, video, textbounding boxes, polygons, semantic segmentation, cuboids, key points, lines, principal axes rotation, timestamp, contours, transcriptions||Logo identification, content moderation, document parsing, retail, advertisement, automotive, hospitality, speech to text,|
|Lionbridge||2D & 3D bounding boxes, cuboids, Image Classification/Image Categorization, Landmark Annotation, Pixel-precise / Pixel-wise Segmentation, Polygons, Semantic Segmentation, Grammar and Spelling, Machine translation Quality Assurance, Indent Variation||AR/VR, Drones and aerial imagery, Autonomous Vehicles, Car infotainment, Face Recognition, Medical Imagery, Video Data analysis, Social Media, Robotics, Analytics and visualization.Sentiment analysis, entity extraction, Automatic Speech Recognition, Voice assistants, Text-to-Speech, pronunciation dictionary creation, Sales Call Analysis, Point of interest tagging, address verification, car and pedestrian routing,|
|V7 Darwin||Image & Videopolygon, brush and eraser, bounding boxes, key points, line, ellipse, cuboid, classification tags, attributes, instance tags, directional vectors||Vision AI for visually impaired, Retail, life sciences, environment, manufacturing.|
|Amazon Sagemaker GT||Image, Video and textImage Classification, Object Detection, and Semantic Segmentation, multi-frame object classification, object tracking, and video clip classification, 3D point clouds, Entity extraction||autonomous vehicles, product descriptions, movie reviews or sentiment analysis|
|LightTag||textSpan Annotation,Entity Annotations, Relationships Annotation.Phrase and Subword Annotations, Document Metadata, Pre-Annotations, Keyboard Shortcuts.||Document Classifications, Document Tagging, Very Long Class Lists, Guidelines,Auto Save, Search.Finance, legal, medical.|
|Kili Technology||Image, video, audio and textpoints, polyline, polygon, bounding boxes, and segmentationobject detection, OCR, entity extraction||Image classification, Medical Imagery, Audio transcription, Conversational Bot|
|Dataturks||Image, video and textimage classification and segmentation, object detection using polygons and bounding boxes, OCR, Document Annotation, Sublabels, NER, PoS||Text Summarization, Content Moderation, Image Label generation|
|TagTog||Textentity extraction, entity normalisation, concept search, Big Texts, annotated corpus, semantic search, text mining,||Chatbot Training, business intelligence, and CRM data enrichment|
|LinkedAI||Image, Video & textbounding boxes, polygons, lines, semantic segmentation and landmarks||Image categorization, automation vehicle, face recognition systems|
The post A Complete Learning Path To Data Labelling & Annotation (With Guide To 15 Major Tools) appeared first on Analytics India Magazine.
This post was originally published by Jayita Bhattacharyya at Analytics India Magazine