### Coordination between Arduino and Image Recognition #### Feasibility and Frameworks - Integration between Arduino and image recognition is feasible. - Various small cameras like OV7670 are compatible with Arduino. - Available image processing libraries: - OpenCV: Resource-intensive but widely used. - Alternatives: Cameramatcs or Pixy2, tailored for microcontrollers. - Object recognition: - Pre-trained models or frameworks like TensorFlow Lite for Microcontrollers or EdgeImpulse suitable for microcontrollers. #### Processing and Output - Data processing on Arduino: - Camera detects cards, sends raw data to Arduino. - Arduino analyzes data and interprets recognized cards. - Decision logic: - Implementation of decision logic on Arduino defining actions. - Possible speech output based on card recognition. #### Energy Consumption - Low power consumption or consistent power supply is desirable. *Note*: Image processing on Arduino can be challenging due to limited resources and performance capabilities. Finding compromises may be necessary. #### Frameworks - TensorFlow Lite for Microcontrollers: - Executes machine learning models on resource-constrained devices. - Edge Impulse: - Simplifies application development for microcontrollers, facilitates data collection, model training, and deployment. - OpenMV: - Platform for computer vision on microcontrollers, supports basic image processing tasks. - Arduino Libraries: - Example: Arduino Computer Vision Library. #### Considerations - Processing 10-15 playing cards simultaneously on Arduino can be challenging, considering resource limitations. - Possibilities: 1. Algorithm optimization. 2. External processing unit. 3. Prototype and test. #### Example Code Collection ##### Image Recognition with Color Detection (Arduino) ```cpp #include #include #include #include #define RED_THRESHOLD 1000 // Threshold for red color detection Adafruit_TCS34725 tcs = Adafruit_TCS34725(TCS34725_INTEGRATIONTIME_50MS, TCS34725_GAIN_4X); void setup() { Serial.begin(9600); if (tcs.begin()) { Serial.println("Color sensor found!"); } else { Serial.println("Color sensor not found. Check connection."); while (1); } } void loop() { uint16_t clear, red, green, blue; tcs.getRawData(&red, &green, &blue, &clear); if (red > RED_THRESHOLD) { Serial.println("Red color detected!"); // Further actions for the detected card can be implemented here } else { Serial.println("No red color detected."); } delay(1000); // Delay between detection loops }