arduino code to detect signatures on pixymon

Lemon

3 min read

·

04-02-2025

1

0

Share

Arduino Code to Detect Signatures Using PixyMon

This guide details how to write Arduino code to detect predefined signatures using the Pixy camera and its accompanying PixyMon software. We'll cover the basic principles, necessary hardware, and provide a sample code snippet to get you started. This is not a plug-and-play solution; familiarity with Arduino programming and the Pixy camera's functionality is assumed.

Understanding Pixy and PixyMon

The Pixy camera is a small, inexpensive vision sensor that can detect and track colored objects. It uses a process called signature detection. You teach the Pixy to recognize specific colors or color ranges, and it then reports the location and size of these "signatures" within its field of view. PixyMon is the software used to configure the Pixy camera and view its output.

Hardware Requirements

• An Arduino board (Uno, Nano, Mega, etc.)
• A Pixy camera
• Connecting wires (jumper wires)

Software Requirements

• Arduino IDE
• Pixy2 library for Arduino (downloadable from the official PixyCam website)

Setting up Signatures in PixyMon

Before writing any Arduino code, you need to define the signatures you want to detect using PixyMon. This involves:

1. Connecting the Pixy: Connect the Pixy camera to your computer via USB.
2. Opening PixyMon: Launch PixyMon software.
3. Teaching Signatures: Point the Pixy camera at the object(s) you want it to recognize. Use the "Teach" function in PixyMon to create signatures for each object. This involves selecting a color range that uniquely identifies the object. PixyMon will provide a signature number for each object. Remember these signature numbers; they are crucial for the Arduino code.

Arduino Code Example

This code snippet demonstrates how to read signature data from the Pixy camera and print the information to the serial monitor. Remember to adjust the signature numbers according to your PixyMon configuration.

#include <Pixy2.h>

Pixy2 pixy;

void setup() {
  Serial.begin(9600);
  pixy.init();
}

void loop() {
  static int i = 0;
  uint16_t blocks;
  char buffer[100];

  blocks = pixy.ccc.getBlocks();

  if (blocks) {
    for (int i = 0; i < blocks; i++) {
      if (pixy.ccc.blocks[i].signature == 1) { // Check for signature 1
        sprintf(buffer, "Signature 1 detected at X: %d, Y: %d, Width: %d, Height: %d\n",
                pixy.ccc.blocks[i].x, pixy.ccc.blocks[i].y, pixy.ccc.blocks[i].width, pixy.ccc.blocks[i].height);
        Serial.print(buffer);
      } else if (pixy.ccc.blocks[i].signature == 2) { // Check for signature 2
        // Add your code here to handle signature 2
        Serial.println("Signature 2 detected!");
      }
      // Add more 'else if' statements for additional signatures
    }
  }
  delay(100);
}

Explanation:

• The code includes the Pixy2 library.
• The setup() function initializes the serial communication and the Pixy camera.
• The loop() function continuously reads data from the Pixy camera using pixy.ccc.getBlocks().
• The code then iterates through the detected blocks and checks if the signature matches the predefined signatures (1 and 2 in this example).
• If a match is found, the corresponding coordinates, width, and height of the detected object are printed to the serial monitor. You can replace the Serial.print statements with actions to control other components on your project, such as servos or motors.

Extending the Code

This is a basic example. You can expand this code to perform various tasks based on the detected signatures, such as:

• Controlling robotic movements based on object position.
• Triggering events when specific signatures are detected.
• Implementing object tracking.

Remember to consult the PixyCam documentation and the Pixy2 Arduino library for more detailed information and advanced functionalities. Remember to replace the example signature numbers (1 and 2) with the actual signature numbers you defined in PixyMon. This code provides a foundation upon which you can build more complex signature detection applications.