Computer Vision at Human
HUMAN Protocol is a decentralized, open-source platform that enables anyone to request or contribute to tasks. By supporting a variety of all existing data sources, it ensures higher accuracy at minimal cost.
At its core, HUMAN Protocol leverages the power of distributed networks to create a more efficient and accessible marketplace for AI and machine learning tasks. This democratic approach not only reduces costs but also improves the quality of data by drawing from a diverse global pool of contributors.
The platform's has processed millions of data points for image recognition, object detection, and semantic segmentation.
Human Vision
Human is a work-agnostic protocol capable of performing any task that can be evaluated by a computer. This makes it especially well-suited for machine learning workflows—such as data annotation and inference—as well as any situation where you need to measure the success of a desired outcome using computational methods. The protocol's flexibility allows it to handle everything from simple classification tasks to complex multi-step evaluations, making it invaluable for both researchers and enterprises. By leveraging human and computers in the loop, Human grows in capability as computers gain agency.
Whether you're training AI models, validating data quality, or measuring real-world outcomes, Human's sdk and smart contracts are the same.
Work-Agnostic Protocol
Capable of performing any task that can be evaluated by a computer
Machine Learning Workflows
Well-suited for data annotation and inference tasks
Outcome Measurement
Measures success of desired outcomes using computational methods, providing detailed metrics and analytics. Supports real-time monitoring and validation of results across diverse use cases and applications.
Provide Agency
The Human Protocol enables providers to securely stake HMT and gain access to our established worker pools, creating a robust ecosystem for distributed task completion. Through the comprehensive Human Protocol Grant Program, providers can seamlessly onboard to the Human App and begin testing their labeling applications on a live public workpool, with full support from our technical team and community. Human is actively onboarding agents and human labeling services to the platform, fostering a growing network of skilled workers and innovative service providers who are reshaping the future of decentralized work.
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Secure Staking
Providers can securely stake HMT to access established worker pools, ensuring commitment and quality while maintaining network security. Our staking mechanism creates alignment between providers and the network, while providing opportunities for rewards through active participation.
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Grant Program
Seamless onboarding to the Human App for testing labeling applications through our comprehensive grant program. Providers receive technical support, documentation, and resources needed to successfully integrate their solutions. The program includes testing credits, development assistance, and direct access to our engineering team.
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Active Onboarding
Human is actively bringing agents and human labeling services to the platform, with a focus on quality and diversity. We provide specialized onboarding support, training resources, and community integration to ensure successful participation. Our growing network includes specialized providers across various domains including data annotation, content moderation, and AI training.
Use Agency
Providers can use CVAT to onboard agents or human labeling interfaces, or they can integrate their own platform for greater flexibility. All Human Protocol labeling leverages ML model-in-the-loop technology to streamline the work of labelers and ensure the highest quality for users through our Job Launcher. The Job Launcher is designed to support the ML inference or labeling APIs you already use.
Our CVAT integration offers a complete suite of labeling tools and workflows, making it easy to start working with minimal setup time. For organizations with existing infrastructure, our custom platform integration provides full API access and seamless connectivity with your current systems. The ML model-in-the-loop technology automatically pre-labels data and suggests corrections, reducing manual effort by up to 70% while maintaining exceptional accuracy.
By choosing Human Protocol for your labeling needs, you'll benefit from our robust quality assurance systems, scalable infrastructure, and active community of skilled labelers. Our platform handles everything from worker management to payment distribution, allowing you to focus on getting high-quality labeled data for your specific use case.
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CVAT Integration
Onboard agents or human labeling interfaces with comprehensive tools and pre-built workflows
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Custom Platform Integration
Integrate your own platform with full API access and flexible configuration options
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ML Model-in-the-Loop
Streamline labeling work with automated pre-labeling and quality checks
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Job Launcher
Supports existing ML inference or labeling APIs with seamless deployment
Our CV Work in Numbers
24B+
Tasks Solved
Successfully completed CV tasks through December 2024, representing one of the largest datasets in the industry
33K+
Active Holders
Engaged stakeholders participating in our ecosystem across multiple blockchain networks
174K+
Active Workers
Skilled professionals from 150 countries contributing to our global computer vision initiatives
27M+
Transactions
Verified on-chain interactions, ensuring complete transparency and trust in our ecosystem
Jobs, Tasks and Rewards
Our decentralized platform efficiently connects project owners with skilled workers through a systematic process that ensures quality and fair compensation.
Project Requests
Projects begin with high-level job requests from organizations worldwide. These jobs are intelligently broken down into thousands of smaller, manageable tasks using our advanced task-splitting algorithms. This granular approach ensures precise execution and quality control at every step.
Task Distribution
Tasks are efficiently distributed through our network of supported applications to our global workforce. Our smart matching system considers workers' skills, experience, and performance history to ensure optimal task allocation. Workers can choose tasks that match their expertise and availability, creating a flexible and efficient marketplace.
Rewards
Our blockchain-based verification system automatically validates completed work using sophisticated quality control measures. Once verified, workers receive instant compensation in HMT tokens or any preferred ERC-20 token. This transparent reward system ensures fair compensation and builds trust between project owners and workers. Performance tracking helps workers build reputation and access higher-value opportunities.
Vision
We are building a revolutionary platform that combines cutting-edge technology with global human intelligence. Our vision encompasses four key pillars that work together to create a powerful, scalable ecosystem for AI training and human computation.
Computer Vision
Advanced image and video processing capabilities that enable AI systems to understand and interpret visual data with unprecedented accuracy. Our technology handles everything from basic object detection to complex scene understanding.
Decentralized Network
Built on blockchain technology, our distributed processing and task allocation system ensures transparency, security, and efficiency. This decentralized approach eliminates single points of failure and enables seamless scaling of operations.
HMT Token
Our native token powers the entire ecosystem, providing instant, secure rewards for task completion. The HMT token enables seamless cross-border payments and creates a fair, transparent marketplace for human intelligence tasks.
Global Reach
Our worldwide network of workers and providers spans continents, cultures, and time zones. This diverse community enables 24/7 task completion while ensuring high-quality results through multiple verification layers and specialized expertise.
Open Vision Jobs on HUMAN Protocol
The HUMAN Protocol enables a diverse range of computer vision tasks to be completed through our decentralized network. Below are examples of images that workers process, followed by the different types of jobs available.
Choose from our comprehensive range of vision tasks, each designed to meet specific AI training needs:
Label Binary
Simple yes/no classification tasks where workers make quick decisions about image content. Perfect for initial data sorting and basic content verification. Common uses include identifying presence of specific objects or characteristics.
Label Area Select
Workers perform precise area selection in images using bounding boxes or polygons. Essential for object detection training, these tasks help create accurate boundaries around objects of interest in images.
Label Area Adjust
Fine-tuning of pre-selected areas to improve accuracy. Workers refine existing annotations, ensuring pixel-perfect precision for training data. Ideal for improving existing datasets or correcting automated selections.
Multiple Choice
Classification tasks with multiple predefined options. Workers select from various categories to label images, helping create structured datasets for multi-class classification models.
Label Semantic Segmentation
Advanced image segmentation tasks where workers identify and label different parts of an image at the pixel level. Critical for applications in autonomous driving, medical imaging, and scene understanding.
Free Entry
Open-ended text input tasks allowing workers to provide detailed descriptions or annotations. Perfect for generating natural language descriptions of images or collecting diverse perspectives on visual content.
Queries
Specialized question-answering tasks about image content. Workers respond to specific queries about visual elements, relationships, or characteristics within images. Ideal for training AI systems in visual reasoning.
Website / Link Queries
Complex tasks combining visual and web content analysis. Workers evaluate images in the context of associated web pages or links, perfect for training AI in understanding multi-modal content and web-based visual information.
Each job type is designed to generate high-quality training data for specific machine learning applications. Workers can choose tasks that match their skills and interests, while requesters get precisely labeled data for their AI models.
The HUMAN Protocol Foundation partnered with the prestigious Salk Institute to enhance their scientific research through advanced computer vision capabilities. By implementing CVAT (Computer Vision Annotation Tool) and leveraging HUMAN Protocol's distributed workforce, we helped accelerate their biological research data processing.
Data Annotation Excellence
Successfully processed thousands of biological images using CVAT integration with HUMAN Protocol's distributed workforce
Research Acceleration
Dramatically reduced research data processing time through efficient crowd-powered image annotation and classification
Scientific Impact
Enabled faster breakthrough discoveries by combining Salk's expertise with HUMAN Protocol's distributed intelligence platform
Scaling Salk's Bug Classification Project
Building on our successful partnership with the Salk Institute, we're expanding our bug classification initiative by 4x while delivering superior results through distributed human intelligence.
4x
Capacity Increase
Expanded processing capabilities for specimen analysis
60%
Cost Reduction
More efficient than traditional classification methods
95%
Accuracy Rate
Consistent high-quality specimen identification
Through our distributed workforce platform, we've transformed the Salk Institute's specimen classification process, enabling faster research outcomes while significantly reducing costs. Our human-verified classifications maintain exceptional accuracy while processing a dramatically increased volume of specimens.
Get in Touch
We welcome your questions and collaboration interests. Connect with us through any of these channels: