Train and deploy image classification models

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.

Collect data 1. Collect

Start by collecting images from your cameras with the data management service. You can view the data on the Data tab.

Label data 2. Create a dataset and label

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.

Train models 3. Train an ML model

Use your labeled data to train your own models for object classification using data from the data management service.

Train models 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.

Configure a service 5. Configure an mlmodel vision service

For object classification, you can use the vision service, which provides an ml model classifier model.

Deploy your model 6. Test your classifier

Test your mlmodel classifier with existing images in the Viam app, live camera footage, or existing images on a computer.

Next steps

After testing your classifier, see the following to further explore Viam’s data management and computer vision capabilities:

You can also explore our tutorials for more machine learning ideas: