After uploading the code and pressing RESET, the MEMENTO's screen displays what the camera module sees.
The display shows the overlay when a face is detected. Note robots do not work!
Move in front of the camera and make sure your face is fully visible.
When the robot detects your face, the NeoPixel ring will light up.
When a face is no longer detected, the robot will move its head back to a resting position and turn off its ring light.
For more details about how the MEMENTO's TFT display illustrates how the computer vision for this project works, read through this section of a previous guide.
Troubleshooting
Uneven Lighting
One area we noticed the camera had issues with is uneven lighting. The author of this guide has a window parallel to his desk which caused uneven lighting conditions. The camera would track halfway, but stop when the face became overly saturated by light from the window.
We attempted to correct this by gently illuminating the face with a NeoPixel ring. However, you may find this is not enough. Putting a light source behind the camera will even out the lighting in your room/office/workshop.
Increasing Detection Accuracy
One of the ways to increase this project's face detection accuracy is to find a "sweet spot" in the bounding boxes width. When the robot detects a face, it prints the dimensions of the bounding box, in pixels, to the Serial port (you can read this using the Arduino Serial Monitor or a similar tool). Since the width of the frame is 240 pixels, you may find moving further (or closer) to the camera increases detection accuracy.
Once you have the robot accurately tracking your face, write down the dimensions of the bounding box. You can also put a piece of painter's tape on the floor to mark the ideal distance between you and the robot.
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