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Fish recognition and classification platform

client:

Fishial.ai

industry:

community

region:

USA

overview

Lack of globally available database with fish species. The idea was to build largest open-source fish species image library labelled for AI machine learning and seek the development of a highly accurate ope-source AI model that can identify fish species world wide.

Approach and Solution

Let community to build up the entire database by uploading the pictures of the fish and combine AI to learn and determine the type, subtype etc. Codahead set the entire architecture for browser based service that manages community of enthusiasts, scientific marine and angler communities, let them upload images plus modify their images so the AI categorizes them.

Project highlights

  • Advanced AI-enhanced photo editor
  • Complex user structure for a review process
  • Comprehensive portal summary statistics for admins, editors and team owners
  • CSV batch import for one-click upload of several hundreds of photos
  • ML-based fish and species recognition
  • Manual and automatic datasets exports
  • Open and public teams for volunteers
  • Machine learning engine has been continuously operating for over 4 years

Deliverables

  • Architecture
  • Full backend incl. Data management
  • Web-based front end
  • Machine learning engine, incl. Training for fish species recognition
  • Tech Stack: React.js, Google Cloud, Rails, Type Script, PyTorch, OpenCV.js

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