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Detect Color with a Webcam

In this guide you will detect the color red using your computer’s webcam and the Viam vision service. Without writing any code, you will be able to view your camera stream, with detection bounding boxes, from the Viam app control interface.

You will learn

How to configure a webcam
How to use the color detection vision service

Requirements

You don’t need to buy or own any hardware to complete this tutorial. If you have the following components, you can follow along on your own hardware:

A Linux, macOS or WSL computer that can run viam-server.
A webcam: this could be the webcam on your laptop or any other webcam you can connect to your computer.

No computer or webcam?

No problem. Use Try Viam to borrow a rover free of cost online. The rover already has viam-server installed and is configured with some components to test with, including a webcam.

Once you have borrowed a rover, go to the CONFIGURE tab of the machine, find the cameras and click on the Test panel at the bottom of each camera’s configuration panel to test the camera stream. You should have a front-facing camera and an overhead view of your rover. Now you know what the rover can perceive.

If your rover is facing a wall, find the base configuration panel and click on its Test panel. Use the controls to drive your rover to a different location.

Now that you have seen that the cameras on your Try Viam rover work, continue with Step 4.

Tip

Be aware that if you are running out of time during your rental, you can extend your rover rental as long as there are no other reservations.

Have your own rover?

If you are running this tutorial on your own Viam Rover, make sure you have configured your rover. Go to the CONFIGURE tab of the machine, find the camera and click on the Test panel at the bottom of the camera’s configuration panel to test the camera stream.

Instructions

Follow these instructions to configure your machine and test detecting colors:

Step 1: Create a new machine

Add a new machine in the Viam app by providing a name in the New machine field and clicking Add machine.

Click the name of a machine to go to that machine’s page, where you’ll find a variety of tools for working with your machine.

Step 2: Install viam-server

Follow the that appear on your new machine’s CONFIGURE page to install viam-server on your computer, start running it and connect it to the Viam app. Select the Platform you want to install viam-server on.

Step 3: Configure your webcam

Click the + icon next to your machine part in the left-hand menu and select Component. Select the camera type, then select the webcam model. Enter a name or use the suggested name for your camera and click Create.

Click the Save button in the top right corner of the page to save your configuration. Then click on the Test panel at the bottom of the camera’s configuration panel to test the camera stream.

If you don’t see an image stream, you need to configure the video_path attribute.

For more detailed information, including optional attribute configuration, see the webcam docs.

Step 4: Configure a color detection vision service

The vision service enables a robot to use its cameras to see and interpret the world around it. The service also allows you to create different types of detectors with which the robot can recognize objects, scan QR codes, perform optical quality inspections, and more. The color_detector model of the vision service is a heuristic-based detector that draws boxes around objects according to their hue.

In this guide, we use the color #7a4f5c or rgb(122, 79, 92) (a reddish color).

Hex color #7a4f5c:

Builder
JSON Mode

On your machine’s CONFIGURE tab, add a vision Service and select the color detector model.

In the resulting vision service panel, click the color picker box to set the color to be detected. For this tutorial, set the color to rgb(122, 79, 92) or use hex code #7a4f5c.

Then, set Hue Tolerance to 0.06 and Segment size px to 100.

Your configuration should look like the following:

The vision service configuration panel showing the color set to a reddish color, the hue tolerance set to 0.06, and the segment size set to 100.

On your machine’s CONFIGURE tab, select JSON mode on the CONFIGURE tab. Add the vision service object to the services array in your rover’s JSON configuration:

"services": [
  {
    "name": "my_color_detector",
    "type": "vision",
    "model": "color_detector",
    "attributes": {
      "segment_size_px": 100,
      "detect_color": "#7a4f5c",
      "hue_tolerance_pct": 0.06
    }
  },
  ... // Other services
]

Click the Save button in the top right corner of the page to save your vision service configuration.

Tip

If you want to detect other colors, change the color parameter. Object colors can vary dramatically based on the light source. We recommend you verify the desired color detection value under the lighting conditions your machine will be in when in use.

To determine the color value from the camera stream, you can use a pixel color tool, like Color Picker for Chrome.

Note that the detector does not detect black, perfect greys (greys where the red, green, and blue color component values are equal), or white.

Step 5: Test color detection

Now, test your color detection in the Test section of the computer vision service’s configuration panel or on the CONTROL tab.

You will see your camera stream and see detections as labeled boxes on the images along with labels and confidence data:

If the color is not reliably detected, change the color detectors configuration and increase the Hue Tolerance or decrease the segment size.

(Optional) Step 6: Limit the number of detections

If you are seeing a lot of detections, adjust the hue tolerance to be smaller or the segment size to be bigger.

Click the Save button in the top right corner of the page to save your configuration and close and reopen the Test panel of the vision service configuration panel. You must close and reopen the panel for the new configuration to take effect.

Next steps

You can now detect colors on a camera stream. Of course these detections are not just accessible from the Viam app, but you can also use the vision service API.

You can also use the vision service with Machine Learning models: