The Database service is a crucial part of the MIND platform, which ensures the safe storage of measurements with a time stamp and enables various data operations.
With the flexibility to be deployed locally or on a remote machine running Windows or Linux, the Database service leverages a robust Postgresql database, which provides high performance and scalability for large-scale industrial applications with advanced features like data encryption, and multi-region replication. The Database service ensures that critical measurement data is always secure and available, even in the event of a system failure or disaster.
Within the MInD editor, users have full control over data management, with different user interfaces available. The database layout allows the creation of structures for factories, stations, product classes, and products, enabling assignment of measurements and management of defect tags and user accounts. The MInD editor facilitates various queries, ranging from simple drag and drop actions to complex text queries. Individual query snapshots can be captured, ensuring repeatability in neural network training.
Moreover, the Database service offers additional functionalities such as backup and import operations. For more information on these features, you can explore the YouTube videos.
PostgreSQL v14.7
Prometheus v2.37.1, TimeScaleDB v2.8.1
Backup and restore individual databases fore every projects
Creating and managing custom tags that are specific to a particular product category. These tags can be of various types that are currently usable by AI technology.
Overseeing multiple users during the annotation process, ensuring that annotations produced by individual users can be compared and erroneous annotations can be eliminated.
Easy or custom query creation, Store query result, Create snapshot from queries, Load measurements from queries
Assign tags to measurements
Apart from the basic brush painting option, there are additional choices like superpixel, watershed, and SAM.
It's possible to create unique AI models that perform annotations instead of humans, allowing users to review and rectify the results.
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