Computer Vision with tensoryze
End-to-end solution for your Computer Vision applications.
From labeling until deployment – every step covered by tensoryze core.
Intuitive labeling.
Versioning included.
Labeling image data is often the most tedious part of any computer vision project – time-consuming, repetitive, and hard to track. At tensoryze, we’ve been there. That’s why we built a new labeling feature for tensoryze core that makes the process fast, intuitive, and traceable – developed by people who know the pain firsthand.
Model development
Use our Visual Studio extension to develop your Computer Vision models in a familiar environment. This approach provides maximum flexibility during the development process while maintaining seamless integration with tensoryze core.
Flexible pipeline orchestration.
Automatically train your Computer Vision models with full flexibility – execute manually, on a schedule, or via API. Effortlessly manage complex workflows with DAG support and ensure seamless data exchange within tensoryze core. Receive instant failure notifications, and easily review logs, code, and assets at every step.
Automated robustness tests for production-ready models.
Ensure your computer vision models are truly production-ready. Use the automated testing feature of tensoryze core to rigorously evaluate robustness against brightness changes, sensor noise, defocus, and more. Identify weaknesses early and deploy only models you can trust to perform under your manufacturing conditions.
Deployment and monitoring.
Monitor your ML assets in production and automatically rectify the situation if necessary. Detect drifts in incoming data or your model. Notify your data experts and automatically retrain your models to adapt to ever changing conditions in your shopfloor.
Industrial Computer Vision use cases realized with tensoryze.
Read in our case studies how tensoryze enabled faster, more effective computer vision solutions.
Hairpin Laser Welding
For a Hairpin Laser Welding process the use of tensoryze core significantly reduced the development and deployment time by 84%.
The developed computer vision models achieved a 23% increase in defect detection accuracy.
Want to realize your Computer Vision use cases? Contact us now!
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