PetWatch - Automated Pet Detection & Deterrent System

# Load YOLOv5 model
model = torch.hub.load('ultralytics/yolov5', 'yolov5l', pretrained=True)
model.conf = 0.25  # Confidence threshold
model.iou = 0.45   # IoU threshold for NMS

# Target pet classes from COCO dataset
target_classes = [15, 16, 17, 21]  # Cat, Dog, Sheep, Bear
class_names = {15: 'Cat', 16: 'Dog', 17: 'Sheep', 21: 'Bear'}

# Process detection
results = model(image)
detections = results.pandas().xyxy[0]
pet_detections = detections[detections['class'].isin(target_classes)]

if len(pet_detections) > 0:
    # Draw bounding boxes and send alarm
    annotated_image = draw_detection_boxes(image, pet_detections)
    send_alarm_notification(annotated_image)
    return "ALARM"

/** 
 * @brief Alarm timing
*/
#define ALARM_DURATION_MS      5000   // Total alarm duration
#define PUMP_TOGGLE_COUNT      3      // Number of pump activations  
#define PUMP_TOGGLE_DELAY_MS   1500   // Delay between toggles
#define RELAY_PULSE_MS         100    // Pulse duration for latching relay

SUMMARY = "PetWatch System Image"
DESCRIPTION = "Minimal Linux image with PetWatch application"

inherit core-image

# Core packages
IMAGE_FEATURES += "ssh-server-openssh"

IMAGE_INSTALL:append = " \
    kernel-modules \
    kernel-devicetree \
    config-pin \
    systemd-serialgetty \
    openssh \
    python3 \
    python3-modules \
    python3-opencv \
    python3-pyserial \
    python3-numpy \
    v4l-utils \
    usbutils \
    petwatch \
    "

# Camera, UART and USB support
IMAGE_INSTALL:append = " \
    kernel-module-uvcvideo \
    kernel-module-usb-storage \
    "

// Network configuration
#define WIFI_SSID               "SomeSSID"
#define WIFI_PASSWORD           "SomePassword" 
#define PC_SERVER_IP            "192.168.1.1xx"
#define PC_SERVER_PORT          7702

// BBB communication
#define BBB_UART_ID             uart1
#define BBB_UART_BAUD           460800
#define BBB_UART_TX_PIN         4
#define BBB_UART_RX_PIN         5

// Hardware pins
#define PUMP_RELAY_PIN          12
#define BUZZER_PIN              14

// Frame protocol
#define MAX_IMAGE_SIZE          (100 * 1024)  // 100KB max
#define IMAGE_TIMEOUT_MS        15000
#define FRAME_TIMEOUT_MS        5000

// Alarm configuration  
#define ALARM_DURATION_MS       5000
#define PUMP_TOGGLE_COUNT       3
#define PUMP_TOGGLE_DELAY_MS    1500
#define BUZZER_BEEP_COUNT       10
#define BUZZER_BEEP_DELAY_MS    250

#!/usr/bin/env python3

# Camera configuration
CAM_ID = 0  # /dev/video0
camera_resolution = (640, 480)
camera_fps = 10

# UART configuration
TTY_DEV = "/dev/ttyS1"
BAUDRATE = 460800

# Motion detection thresholds
bg_history = 300          # Frames for background model
var_threshold = 20        # Variance threshold
motion_threshold = 300    # Minimum motion area
motion_cooldown = 1.5     # Seconds between captures

# JPEG compression
jpeg_quality_low = 70     # For high motion
jpeg_quality_high = 85    # For moderate motion

# Email configuration
notification_emails = ["receiver@example.com"]
smtp_server = "smtp.gmail.com"
smtp_port = 587
email_user = "sender@gmail.com"
email_password = "app_specific_password"

# YOLOv5 detection settings
model_variant = 'yolov5l'
confidence_threshold = 0.25
iou_threshold = 0.45
target_classes = [15, 16, 17, 21]

# Server configuration
server_port = 7702
server_address = '0.0.0.0'