Navigate with a Rover Base
Introduction to using a rover base with the navigation service.
Introduction to using a rover base with the navigation service.
A heuristic detector that draws boxes around objects according to their hue (does not detect black, gray, and white).
A detector or classifier that uses an ML model available on the machine to draw bounding boxes around objects or return a class label.
Use your image data to train a model, so your machines can make inferences about their environments.
The vision service enables your machine to use its on-board cameras to intelligently see and interpret the world around it.
Give commands to get detections, classifications, or point cloud objects, depending on the ML model the vision service is using.
This model takes 2D bounding boxes from an object detector and projects the pixels in the bounding box to points in 3D space.
A segmenter for depth cameras that returns the perceived obstacles as a set of 3-dimensional bounding boxes, each with a Pose as a vector.
A segmenter that takes point clouds from a camera input and returns the average single closest point to the camera as a perceived obstacle.
A segmenter that identifies well-separated objects above a flat plane.
Detect people and their location in an image with any webcam and a vision service.
Design your ML Model service to work with Viam’s vision services.
Create an alarm system that can detect people and can recognize faces, allowing it to smartly trigger alarms.
Use the filter modular component in the Viam app to photograph your pet in their collar.
Make a functional guardian with a servo motor, some LEDs, a camera, and the ML Model and vision service to detect people and pets.
Modernize the Omnibot 2000 from the 1980s with Viam and AI.
Use the vision service and the Python SDK to send yourself a text message when your webcam detects a person.
How to turn a light on when your webcam sees a person.
Harness AI and use ChatGPT to add life to your Viam rover and turn it into a companion robot.
Detect colors and their location in an image with any webcam and a vision service.
Build a line-following robot that relies on a webcam and color detection.
Instructions for detecting and following a colored object with a rover, like a SCUTTLE robot.