Edge-based object matching using Chamfer distance for CAPTCHA solving
Project description
Shape Matcher
Edge-based object matching using Chamfer distance. Finds the most similar pair of objects in an image.
Algorithm
- LAB Chroma Mask - Separates colored objects from background (catches faint colors, ignores shadows)
- Binary Patch Normalization - Converts each object contour to a square binary patch
- Edge Extraction - Gets silhouette edge from binary patch (no fake edges from shading)
- Chamfer Distance - Compares edges with rotation sweep for rotation invariance
Installation
pip install -r requirements.txt
Usage
CLI
# Basic usage
python -m shape_matcher --image examples/image.png --out result.png
# With options
python -m shape_matcher -i examples/image.png -o result.png --chroma_thr 5.0 --angles_step 10 --debug
Python API
from shape_matcher import Config, MatcherFactory
import cv2
# Load image
img = cv2.imread("examples/image.png")
# Create matcher
config = Config.default()
matcher = MatcherFactory.create(config)
# Process
objects, best_match, result_img = matcher.process(img)
if best_match:
print(f"Best match: Object {best_match.idx1} <-> Object {best_match.idx2}")
print(f"Chamfer distance: {best_match.chamfer_distance:.4f}")
Options
| Option | Default | Description |
|---|---|---|
--chroma_thr |
6.0 | LAB chroma threshold (lower = catch fainter colors) |
--min_area |
300 | Minimum contour area |
--min_wh |
20 | Minimum bbox width/height |
--min_hole_area_ratio |
0.02 | Minimum hole area ratio vs parent contour |
--hole_mismatch_penalty |
2.0 | Penalty per hole-count mismatch |
--hole_area_weight |
1.0 | Weight for hole area ratio difference |
--hu_weight |
0.6 | Weight for Hu moment distance |
--angles_step |
15 | Rotation step in degrees (smaller = more accurate) |
--patch |
96 | Normalized patch size |
--debug |
False | Enable debug logging |
Project Structure
TikTok-Captcha-Solver/
├── shape_matcher/ # Main package
│ ├── __init__.py # Package exports
│ ├── __main__.py # CLI runner
│ ├── config.py # Configuration classes
│ ├── models.py # DetectedObject, MatchResult
│ ├── protocols.py # Abstract interfaces
│ ├── mask.py # LABChromaMaskGenerator
│ ├── patch.py # PatchProcessor
│ ├── chamfer.py # ChamferDistance
│ ├── extractor.py # ContourObjectExtractor
│ ├── similarity.py # EdgeChamferSimilarity
│ ├── renderer.py # DefaultResultRenderer
│ ├── factory.py # MatcherFactory
│ └── service.py # MatcherService
├── examples/ # Test images
├── requirements.txt
└── README.md
License
MIT
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