AI photo tagging app

📰 Dev.to AI

Learn how to test vision ML models in real-world situations using a simple AI photo tagging app

intermediate Published 27 Apr 2026
Action Steps
  1. Build a simple AI photo tagging app using vision ML models
  2. Test models in real-world situations before deploying on embedded platforms
  3. Configure the app to collect and label data for model training
  4. Run the app on a variety of images to evaluate model performance
  5. Compare results with static dataset accuracy to identify areas for improvement
Who Needs to Know This

Machine learning engineers and data scientists can benefit from this app to improve model accuracy and deployment results

Key Insight

💡 Testing ML models in real-world situations can significantly improve deployment results

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New AI photo tagging app helps ML engineers test vision models in real-world situations #AI #ML #ComputerVision

Key Takeaways

Learn how to test vision ML models in real-world situations using a simple AI photo tagging app

Full Article

Introducing a newly released AI photo tagging app for the iphone. More details on our website ( https://siwave.io ) and a link to the kickstarter project. We were having a hard time matching vision ML models accuracy results on static datasets with post deployment results. Therefore, we decided to create a simple-to-use internal tool to test models in real world situation before we actually deploy them on embedded platforms. <
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