Roadmap

Phase One: Checkbox-Text Detector Foundation

Objective: Establish the foundational technology for checkbox-text extraction, enabling the automated identification and extraction of checkbox data from various document types.

Key Activities:

  • Conduct extensive research on existing checkbox detection algorithms, identifying gaps and opportunities for innovation.

  • Utilize a diverse dataset containing various document types with checkboxes to train the detection model.

  • Develop an initial prototype of the checkbox-text detection system, integrating image processing techniques.

  • Conduct rigorous testing of the prototype to evaluate its accuracy and performance metrics.

Expected Outcomes:

  • A functional prototype capable of detecting and extracting checkbox data from documents.

  • Performance metrics demonstrating the accuracy and reliability of the checkbox-text extraction system.

Phase Two: Launch on Testnet

Objective: Launch on testnet to validate the Document Understanding Subnet's functionalities in a controlled setting.

Key Activities:

  • Set up the necessary infrastructure for the testnet launch.

  • Launch the checkbox-text detection capabilities and other core features on the testnet.

  • Engage early adopters and developers to test the subnet, providing feedback and reporting issues.

  • Collect feedback and make necessary adjustments to enhance functionality and user experience.

Expected Outcomes:

  • A fully operational code that allows users to experiment with the Document Understanding Subnet.

  • Identified areas for improvement and enhanced features based on user feedback.

Phase Three: Launch on Mainnet

Objective: Transition the Document Understanding Subnet to the Bittensor mainnet, enabling users to leverage the platform for real-world applications.

Key Activities:

  • Register the Document Understanding Subnet on the Bittensor mainnet.

  • Conduct thorough security audits of the codebase.

  • Engage the community to encourage participation, including onboarding validators and miners.

  • Execute extensive testing in the mainnet environment.

Expected Outcomes:

  • A fully operational subnet on the Bittensor mainnet.

  • A growing network of validators and miners, contributing to the security and efficiency of the Document Understanding Subnet.

Phase Four: Internal OCR Engine Development

Objective: Develop a high-performance, proprietary OCR engine to enhance text extraction accuracy and processing speed within the Document Understanding Subnet.

Key Activities:

  • Design a technical strategy focused on high-accuracy recognition, leveraging deep learning and contextual enhancements.

  • Incorporate advanced models, such as LayoutLMv3, for interpreting intricate document layouts.

  • Train the OCR engine using a diverse dataset and rigorously test for performance and accuracy.

  • Deploy the in-house OCR engine and continuously refine it based on real-world usage and feedback.

Expected Outcomes:

  • A state-of-the-art OCR engine integrated into the Document Understanding Subnet, significantly improving text extraction capabilities.

  • Enhanced performance metrics demonstrating the superiority of our OCR engine compared to existing solutions.

Phase Five: Feature Expansion

Objective: Enhance the Document Understanding Subnet by incorporating additional document types and processing features, broadening its applicability and utility.

Key Activities:

  • Identify and develop additional document processing features such as support for invoices, receipts, and legal contracts.

  • Gather feedback from users to inform feature development.

  • Optimize the infrastructure to handle increased processing demands.

  • Develop comprehensive documentation and support resources for users.

Expected Outcomes:

  • A richer set of features enabling users to process a wider variety of documents.

  • Improved user satisfaction through ongoing engagement and support.

Phase Six: User Portal and Public Website

Objective: Create a user-friendly web-based dashboard to manage document processing tasks and provide resources.

Key Activities:

  • Design a centralized resource hub for users to upload documents, track processing status, and view analytics.

  • Provide access to educational materials and use case examples.

  • Foster engagement with users through the portal to encourage contributions.

Expected Outcomes:

  • A centralized user portal that lowers the barrier to entry for non-technical users and enhances user engagement.

Phase Seven: API Integration

Objective: Enable seamless integration of the Document Understanding Subnet with third-party applications through a robust API.

Key Activities:

  • Design a well-documented, resilient API built on RESTful principles for easy integration.

  • Allow users to access core document processing functions, such as data extraction and classification.

  • Support customization options for specific business requirements.

  • Ensure the API supports near-instantaneous analysis and results.

Expected Outcomes:

  • A robust API that facilitates easy integration and enhances the platform's usability.

Phase Eight: SDK Integration

Objective: Provide developers with comprehensive SDKs to simplify interaction with the Document Understanding Subnet API.

Key Activities:

  • Create SDKs for multiple programming environments, including Python, Java, JavaScript, and .NET.

  • Ensure SDKs are designed for usability, including sample code and documentation.

  • Facilitate integration across diverse technology stacks.

  • Encourage community contributions to the SDKs for continuous improvement.

Expected Outcomes:

  • Developer-friendly SDKs that promote widespread adoption and reduce integration barriers.

Phase Nine: Workflow Automation Tools

Objective: Enable organizations to automate document processing tasks through integration with popular workflow automation platforms.

Key Activities:

  • Integrate with leading automation platforms to trigger document processing based on specific events.

  • Streamline operations to minimize manual intervention.

Expected Outcomes:

  • Enhanced productivity and scalability for organizations through automated document processing.

Phase Ten: Innovation and Sustainability

Objective: Focus on continuous innovation and adaptability to ensure the Document Understanding Subnet remains competitive and sustainable in the evolving landscape of document processing technologies.

Key Activities:

  • Establish dedicated research teams to explore emerging technologies.

  • Implement environmentally sustainable practices within the network.

  • Forge strategic partnerships with academic institutions, industry leaders, and technology providers.

  • Commit to regular updates and enhancements of the platform.

Expected Outcomes:

  • A resilient and adaptive Document Understanding Subnet that thrives amidst technological changes and market demands.

  • A strong reputation within the industry as a leading provider of document understanding solutions.

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