# Follow a Colored Object with a Rover (like SCUTTLE)

In this tutorial, you’ll learn how to use the [vision service](https://docs.viam.com/reference/services/vision/) to make a rover follow a colored object. We’re using a [SCUTTLE rover](https://www.scuttlerobot.org/) for this tutorial but you can use any rover, including the [Viam rover](https://docs.viam.com/try/).

#### You will learn

- How to run control code with Viam SDKs
- How to use the base API and the vision API to follow a line with a rover

There should have been a video here but your browser does not seem to support it.

You can see the [full code](https://docs.viam.com/tutorials/services/color-detection-scuttle/#full-code) at the end of the tutorial.

## Requirements

You don’t need to buy or own any hardware to complete this tutorial.

You will need the following hardware to complete this tutorial:

- A wheeled rover, configured with a base component. If you have your own Viam rover [follow the Viam Rover configuration instructions](https://docs.viam.com/try/). If you own another mobile robot [follow the general configuration instructions](https://docs.viam.com/tutorials/configure/configure-rover/).

This tutorial uses a [SCUTTLE rover](https://www.scuttlerobot.org/shop/) as an example but you can complete this tutorial using a Yahboom 4WD Smart Robot or any other wheeled robot that can be configured as a [base component](https://docs.viam.com/reference/components/base/wheeled/).

- An attached and configured [webcam camera](https://docs.viam.com/reference/components/camera/webcam/).

## Set up the hardware

Connect the camera to the rover’s board. Turn on the power to the rover.

## Configure color detection

This tutorial uses the color `#a13b4c` or `rgb(161,59,76)` (a reddish color).

To create a [color detector vision service](https://docs.viam.com/reference/apis/services/vision/#detections):

- [Builder](https://docs.viam.com/tutorials/services/color-detection-scuttle/#tabset-tutorialsservicescolor-detection-scuttle-1-0)
- [JSON Template](https://docs.viam.com/tutorials/services/color-detection-scuttle/#tabset-tutorialsservicescolor-detection-scuttle-1-1)

Navigate to your machine’s **CONFIGURE** tab. Click the **+** (Create) icon next to your machine part in the left-hand menu and select **Blocks**. Search for `color detector`, then select the `vision/color_detector` block. Enter `my_color_detector` as the name for your service and click **Add to machine**.

In your vision service’s panel, set the following **Attributes**:

- Set the color to `#a13b4c` or `rgb(161,59,76)`
- Set hue tolerance to `0.06`
- Set the segment size to `100`px

Add the vision service object to the services array in your rover’s JSON configuration:

```json

```

Click **Save**.

You have configured a heuristic-based detector that draws boxes around objects according to their color.

#### Tip

If you want to detect other colors, change the color parameter `detect_color`. Object colors can vary dramatically based on the light source. We recommend that you verify the desired color detection value under actual lighting conditions. To determine the color value from the actual cam component image, you can use a pixel color tool, like [Color Picker for Chrome](https://chrome.google.com/webstore/detail/color-picker-for-chrome/clldacgmdnnanihiibdgemajcfkmfhia).

### Test your color detector

You can test your detector by clicking on the **Test** area of the vision service’s configuration panel or from the [**CONTROL** tab](https://docs.viam.com/monitor/default-interface/#web-ui):

The camera stream will show detections with bounding boxes around the detected colors.

#### Tip

If the color is not reliably detected, try increasing the `hue_tolerance_pct` or adjusting the lighting of the area to make the color being detected more visible. Note that the detector does not detect black, perfect greys (greys where the red, green, and blue color component values are equal), or white.

## Program your rover

### Set up your code environment

We are going to use Virtualenv to set up a virtual environment for this project, in order to isolate the dependencies of this project from other projects. Run the following commands in your command-line to install `virtualenv`, set up an environment `venv` and activate it:

```sh
python3 -m pip install --user virtualenv
python3 -m venv env
source env/bin/activate
```

Then, install the Viam Python SDK:

```sh
pip3 install viam-sdk
```

### Connect

Next, go to the **CONNECT** tab on your [machine page](https://app.viam.com/robots) and select **API keys** to get your credentials.

To show your machine’s API key in the sample code, toggle **Include API key**.

#### Caution: Keep your API key safe

We strongly recommend that you add your API key as an environment variable. Anyone with your API key can access your machine, and the computer running your machine.

This code snippet imports all the necessary packages and sets up a connection with Viam.

Next, create a file named main.py with the sample code from the **CONNECT** tab. Then, save your file.

Run the code to verify that the Viam SDK is properly installed and that the `viam-server` instance on your robot is live. If you haven’t yet installed `viam-server`, follow the [installation guide](https://docs.viam.com/set-up-a-machine/first-machine/) to install `viam-server` on your robot before proceeding with this tutorial.

You can run your code by typing the following into your terminal from the same directory as your `main.py` file:

```sh
python3 main.py
```

The program prints a list of robot resources.

On top of the packages that the code sample snippet imports, import `pil_to_viam_image` and `viam_to_pil_image` from `viam.media.utils.pil`. The top of your code should now look like this:

```python

```

You will update the `main()` function later.

### Detect the location of a colored object

With the configured color detector, you can programmatically retrieve a list of detections. Each detection comes with information about where in the camera’s picture it is detected.

The following `leftOrRight` function checks where in the picture the largest detection is and returns a responding integer: `0` for left, `1` for center, and `2` for right.

Add the `leftOrRight` function below your `connect` function:

```python

```

### Add the main function

The `main` function:

- defines variables for how the robot should move,
- connects to the robot,
- initializes the base, the camera, and the detector, and
- repeatedly calls the `leftOrRight` function and turns the rover’s base in the respective direction.

Replace the `main` function with the following code:

```python

```

For `<camera-name>`, insert the name of your configured physical camera.

## Run the code

Now, run the code again, from the same directory as your `main.py` file:

```sh
python3 main.py
```

Your rover should detect and navigate towards any red objects that come into view of its camera. Use something like a red sports ball or book cover as a target to follow to test your rover:

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## Next steps

Congratulations! If you’re ready for more, try making your rover detect other colors. You could also write some code with a Viam SDK to [make your rover move in a square](https://docs.viam.com/try/viam-rover/drive-rover/).

You can also ask questions in the [Community Discord](https://discord.gg/viam) and we will be happy to help.

## Full code

```python

```