pywayne-cv-apriltag-detector

Pywayne AprilTag Detector

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

Quick Start

from pywayne.cv.apriltag_detector import ApriltagCornerDetector

# Create detector. Default tag family is 36h11.
detector = ApriltagCornerDetector(tag_family="36h11")

# 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)

Corner Extraction Task Pattern

When the user asks to detect AprilTag corners in an image, produce IDs and corner coordinates directly. Prefer non-GUI code unless the user asks for visualization.

from pywayne.cv.apriltag_detector import ApriltagCornerDetector

detector = ApriltagCornerDetector(
    tag_family="36h11",
    preprocess=None,  # or "norm", "clahe", "equalize", "norm-clahe"
)
detections = detector.detect("image.jpg")

for det in detections:
    print({
        "id": det.id,
        "hamming_distance": det.hamming_distance,
        "center": tuple(det.center),
        "corners": [tuple(p) for p in det.corners],
    })

If detection is poor because of lighting or contrast, retry with preprocess="norm-clahe" or preprocess="clahe" before changing algorithm parameters.

Detection Methods

detect()

Detect AprilTags in an image:

detections = detector.detect(
    image,           # File path, Path object, or numpy array
    show_result=False, # Show visualization window
    preprocess=None    # Optional override for this call
)

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:

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