Pywayne AprilTag Detector

This module detects AprilTag fiducial markers for camera calibration and pose estimation.

Quick Start

python

from pywayne.cv.apriltag_detector import ApriltagCornerDetector

# Create detector
detector = ApriltagCornerDetector()

# Detect from file path
detections = detector.detect('test.png', show_result=True)

# Detect from numpy array
import cv2
image = cv2.imread('test.png')
detections = detector.detect(image)

Detection Methods

detect()

Detect AprilTags in an image:

python

detections = detector.detect(
    image,           # File path, Path object, or numpy array
    show_result=False  # Show visualization window
)

Returns list of detection results with:

•id: Tag ID
•hamming_distance: Detection confidence
•center: Tag center coordinates (x, y)
•corners: 4 corner coordinates

detect_and_draw()

Detect AprilTags and draw results on original image:

python

result_image = detector.detect_and_draw(image)
cv2.imshow('Detection Result', result_image)
cv2.waitKey(0)

Visualization includes:

•Green polygon outlines
•Red corner circles
•Red ID labels at tag centers

Requirements

•cv2 (OpenCV) - Image processing
•numpy - Array operations
•gettool - Downloads apriltag_detection library automatically

Library Installation

The detector automatically checks for and installs the apriltag_detection library using gettool if not found.

Detection Result Format

Each detection contains:

Field	Description
`id`	Tag identifier
`hamming_distance`	Hamming distance (lower = more confident)
`center`	Tag center as (x, y) tuple
`corners`	4 corner coordinates as [(x1, y1), (x2, y2), (x3, y3), (x4, y4)]

Notes

•Supports both grayscale and BGR images
•Automatic grayscale conversion for detection
•Visualization sizes scale with image dimensions
•Uses AprilTag 36h11 tag family