diff --git a/docs/use-cases/deploy-ml.md b/docs/use-cases/deploy-ml.md index 867838063c..65c7da1d72 100644 --- a/docs/use-cases/deploy-ml.md +++ b/docs/use-cases/deploy-ml.md @@ -3,6 +3,63 @@ title: "Train and deploy image classification models" linkTitle: "Train and deploy classification models" weight: 50 type: "docs" -layout: "empty" -canonical: "ml/" +tags: ["data management", "data", "services"] +no_list: true +description: "Use Viam's machine learning capabilities to train image classification models and deploy these models to your machines." +image: "/ml/training.png" +imageAlt: "Machine Learning" +images: ["/ml/training.png"] --- + +You can create and deploy an image classification model onto your machine with Viam's machine learning (ML) capabilities. +Manage the classification model fully on one platform: collect data, create a dataset and label it, and train the model for **Single** or **Multi Label Classification**. +Then, test if your model works for classifying objects in a camera stream or existing images with the `mlmodel` classification model of vision service. + +
{{ Start by collecting images from your cameras with the data management service. You can view the data on the Data tab. + |
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{{ Once you have enough images of the objects you'd like to classify, label your data and create a dataset in preparation for training classification models. + |
+
{{ Use your labeled data to train your own models for object classification using data from the data management service. + |
+
+ 4. Deploy your ML model
+ To make use of ML models with your machine, use the built-in ML model service to deploy and run the model. + |
+
{{mlmodel vision service
+ For object classification, you can use the vision service, which provides an ml model classifier model. + |
+
{{ Test your mlmodel classifier with existing images in the Viam app, live camera footage, or existing images on a computer. + |
+