CV Computer Vision

---

• Asynchronous methods
  • get_available_models()
  • enable_model()
  • disable_model()
  • disable_all_models()
  • train_model_folder_path()
  • train_model()
  • delete_face()
• Handlers
  • find_tags()
  • get_current_predictions()
  • get_predictions_once()
  • set_predictions_callback()
  • set_img_predictions_callback()
  • find_objects()
  • cancel_find_objects()
  • get_objects_names()
  • Overview
  • Common Methods
  • Handlers List
• Exceptions

1. Overview

As you already saw, we created a wide range of controllers that allow you to control and manipulate the robot in a very easy and efficient way.

The goal of this controller is to provide an extra layer of capabilities, enabling detection and recognition of objects/faces/tags to leverage your applications.

Among with this controller, we are providing some ready-to-use models.

For the simulation environment, the following models are available right now:

• unity_apartment.

• Coco.

In a real robotic device, you will be able to use your own predefine model by adding it to the dat folder.

2. Using the controller

from raya.application_base import RayaApplicationBase

class RayaApplication(RayaApplicationBase):
    async def setup(self):
        self.interactions = await self.enable_controller('cv')
        ...

If you want to use any CV functionality, your first need to enable the model that you want to use, by calling enable_model() method.

3. Example

See examples starting with ‘cv’ in the pyraya_examples GitHub.