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jenkinsm13 and others added 4 commits December 7, 2024 23:20
Added MoGrammetry-specific dependencies
Transform MoGrammetry from a 310-line stub into a comprehensive,
production-ready 3D reconstruction system (5000+ lines).

## New Features

### Core Package (mogrammetry/)
- **config.py**: Full configuration management with YAML/JSON support
- **logger.py**: Professional logging with colored output and progress tracking
- **colmap_parser.py**: Robust parser supporting all COLMAP camera models
- **alignment.py**: ROE solver + RANSAC + least squares alignment
- **fusion.py**: Advanced point cloud fusion with outlier removal
- **mesh.py**: Multiple meshing algorithms (Poisson, Ball Pivoting, Alpha Shape)
- **pipeline.py**: Complete end-to-end reconstruction pipeline

### User Interfaces
- **CLI**: Full-featured command-line interface with presets
- **Web UI**: Interactive Gradio interface for easy use
- **Python API**: Programmatic access for custom workflows

### Documentation
- MOGRAMMETRY_README.md: Comprehensive user guide (600+ lines)
- IMPLEMENTATION_SUMMARY.md: Technical implementation details
- examples/: Basic and advanced usage examples
- Config presets: Fast and quality configurations

### Testing
- Complete test suite covering all major components
- 7 test functions validating core functionality

## Key Improvements

### Alignment (alignment.py)
- Implements proper ROE (Robust Outlier Estimation) solver
- Truncated L1 loss for robustness
- Reprojection error minimization
- Multiple alignment strategies

### Point Cloud Processing (fusion.py)
- Statistical outlier removal
- Radius-based outlier removal
- Weighted merging in overlaps
- Automatic voxel size estimation
- Normal estimation and consistency

### Mesh Generation (mesh.py)
- Poisson surface reconstruction
- Ball pivoting algorithm
- Alpha shapes
- Mesh simplification with quadric decimation
- Multi-view texture mapping support

### Pipeline (pipeline.py)
- Validates COLMAP data before processing
- Batch image processing with MoGe
- Per-image alignment and transformation
- Comprehensive error handling
- Detailed statistics and reporting

## Architecture

The system is organized into modular components:
1. Configuration management (config.py)
2. COLMAP data parsing (colmap_parser.py)
3. MoGe inference + alignment (alignment.py)
4. Point cloud fusion (fusion.py)
5. Mesh generation (mesh.py)
6. Pipeline orchestration (pipeline.py)

## Usage

### CLI
```bash
python scripts/mogrammetry_cli.py run \
    --colmap-model colmap/sparse/0 \
    --image-dir images \
    --output output
```

### Python API
```python
from mogrammetry import MoGrammetryPipeline, MoGrammetryConfig
config = MoGrammetryConfig(
    colmap_model_path='colmap/sparse/0',
    image_dir='images',
    output_dir='output'
)
pipeline = MoGrammetryPipeline(config)
stats = pipeline.run()
```

### Web Interface
```bash
python scripts/app_mogrammetry.py
```

## Files Added
- 8 core modules (2800 lines)
- 2 user interfaces (700 lines)
- 4 example scripts (260 lines)
- 2 documentation files (1200 lines)
- 1 test suite (300 lines)

Total: 17 new files, ~5000+ lines of production code

## Technical Highlights
- Robust scale/shift recovery for affine-invariant geometry
- Multi-strategy point cloud fusion
- Comprehensive error handling and validation
- Professional logging and progress tracking
- Flexible configuration system
- Multiple output formats (PLY, GLB, OBJ)

🤖 Generated with Claude Code
https://claude.com/claude-code

Co-Authored-By: Claude <[email protected]>
@jenkinsm13
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@jenkinsm13 jenkinsm13 closed this Oct 27, 2025
@jenkinsm13 jenkinsm13 reopened this Oct 27, 2025
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