AI Suite: Difference between revisions
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In order to create your own AI model based on a [[Neural Network]] you have to follow these steps. | In order to create your own AI model based on a [[Neural Network]] you have to follow these steps. | ||
* Start with a definition of which objects you want to detect. For example trees, cars, solar panels, etc. | * Start with a definition of which objects you want to detect. For example trees, cars, solar panels, etc. These can also be subsets for example trees can also be sub dived into palms, pines, etc. | ||
* Now create one or more projects (with a good variation) and manually create your training data by creating areas containing outlining these objects. | |||
* | * Now create one or more projects (with a good variation) and manually create your training data by creating areas containing outlining these objects. Follow: [[How to create AI train data with QGIS]] | ||
* After exporting | |||
* Then import the [[ONNX]] back into the [[software]] an run it in an Inference Overlay. | * Create to groups of objects a TRAIN and TEST dataset that can be exported. Follow: [[How to export AI Training Data]] | ||
* Finally validate the results on a different project and iterate back to a previous step if needed. | |||
* After exporting you can start training your [[Neural Network]] resulting in a [[ONNX]] file. Follow: [[How to train your own AI model for an Inference Overlay]]. | |||
* Then import the [[ONNX]] back into the [[software]] an run it in an Inference Overlay. For example: [[How to detect foliage using an Inference Overlay]] | |||
* Finally validate the results on a different project and iterate back to a previous step if needed. Follow: [[How to validate an AI model]] | |||
==Apply a model== | ==Apply a model== | ||
* When you have created your own model or by selecting an existing [[ONNX]] file you can apply it to other projects using the [[Inference Overlay]]. | * When you have created your own model or by selecting an existing [[ONNX]] file you can apply it to other projects using the [[Inference Overlay]]. | ||
Revision as of 08:45, 15 October 2025
The Tygron AI Suite consist of a several tools that can help when using an existing Neural Network in an Inference Overlay or when creating a new one.
Steps for creating you own model
In order to create your own AI model based on a Neural Network you have to follow these steps.
- Start with a definition of which objects you want to detect. For example trees, cars, solar panels, etc. These can also be subsets for example trees can also be sub dived into palms, pines, etc.
- Now create one or more projects (with a good variation) and manually create your training data by creating areas containing outlining these objects. Follow: How to create AI train data with QGIS
- Create to groups of objects a TRAIN and TEST dataset that can be exported. Follow: How to export AI Training Data
- After exporting you can start training your Neural Network resulting in a ONNX file. Follow: How to train your own AI model for an Inference Overlay.
- Then import the ONNX back into the software an run it in an Inference Overlay. For example: How to detect foliage using an Inference Overlay
- Finally validate the results on a different project and iterate back to a previous step if needed. Follow: How to validate an AI model
Apply a model
- When you have created your own model or by selecting an existing ONNX file you can apply it to other projects using the Inference Overlay.