AgentSkillsCN

pywayne-cv-stereo-tag-matcher

用于双目相机系统的立体视觉AprilTag匹配。在使用pywayne.cv.stereo_tag_matcher模块将左右相机视图中的AprilTag进行匹配、在图像间寻找共同标签、将立体图像拼接在一起，并以彩色标注的方式可视化结果（所有标签显示为绿色，共同标签显示为黄色，红色连线表示连接关系）时使用此功能。

SKILL.md
--- frontmatter
name: pywayne-cv-stereo-tag-matcher
description: Stereo vision AprilTag matching for dual-camera systems. Use when working with pywayne.cv.stereo_tag_matcher module to match AprilTags from left/right camera views, find common tags between images, stitch stereo images together, and visualize results with color-coded annotations (all tags green, common tags yellow, red connection lines).

Pywayne Stereo Tag Matcher

This module matches AprilTags detected in stereo camera pairs.

Quick Start

python
from pywayne.cv.stereo_tag_matcher import StereoTagMatcher
from pathlib import Path

# Initialize matcher with custom colors
matcher = StereoTagMatcher(
    target_height=600,
    line_color=(0, 0, 255),  # Red
    all_tag_color=(0, 255, 0),  # Green
    common_tag_color=(0, 255, 255)  # Yellow
)

# Process stereo pair
left_img = Path('left.png')
right_img = Path('right.png')
matched_info, stitched = matcher.process_pair(left_img, right_img, show=True)

# Save result
if stitched is not None:
    import cv2
    cv2.imwrite('stereo_result.png', stitched)

Initialization

python
matcher = StereoTagMatcher(
    target_height=600,      # Fixed height for resizing
    line_color=(0, 0, 255),   # Custom line color (BGR)
    line_thickness=2,
    box_thickness=2,
    all_tag_color=(0, 255, 0),
    common_tag_color=(0, 255, 255)
)

Input

ParameterTypeDescription
image1_inputstr, Path, or np.ndarrayLeft camera image
image2_inputstr, Path, or np.ndarrayRight camera image
showboolDisplay stitched result with cv2.imshow

Output

Returned Dictionary

python
{
    "tag_id": {
        "cam1_center": (x, y),      # Left image center
        "cam1_corners": [(x1, y1), ...], # Left image corners
        "cam2_center": (x, y),      # Right image center
        "cam2_corners": [(x1, y1), ...]  # Right image corners
    },
    ...
}

Only tags found in both images are included in the output.

Visualization

The stitched image displays:

  • •All tags - Green boxes (BGR: 0, 255, 0)
  • •Common tags - Yellow boxes (BGR: 0, 255, 255)
  • •Connection lines - Red lines connecting common tag centers (BGR: 0, 0, 255)

Use Cases

  • •Stereo camera calibration - Match common tags to calibrate stereo cameras
  • •Robot vision - Identify shared landmarks for navigation
  • •Augmented reality - Track common fiducial markers

Requirements

  • •cv2 (OpenCV) - Image processing and display
  • •numpy - Array operations
  • •pywayne.cv.apriltag_detector - AprilTag detection

Notes

  • •Images are resized to target_height for consistent annotation
  • •Tag coordinates are scaled proportionally based on image dimensions
  • •Supports both grayscale and BGR color input images