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RAPiD Quick Start Guide

Get up and running with RAPiD in minutes! 🚀

✅ How to install:

  • Local source installation with pip install -e .
  • Local source installation with uv pip install -e .

🚀 Quick Installation

Option 1: Using uv (Recommended)

# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone repository (REQUIRED - no pip install available)
git clone https://github.com/l1997i/rapid-seg.git
cd rapid-seg

# Create and activate environment
uv venv
source .venv/bin/activate  # Linux/Mac
# or
.venv\Scripts\activate     # Windows

# Install RAPiD from source (ONLY method available)
uv pip install -e .

Option 2: Using pip

# Clone repository (REQUIRED - no pip install available)
git clone https://github.com/l1997i/rapid-seg.git
cd rapid-seg

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # Linux/Mac
# or
.venv\Scripts\activate     # Windows

# Install RAPiD from source (ONLY method available)
pip install -e .

🧪 Quick Test

import torch
from rapid_seg import RAPiDCalculator

# Create sample point cloud
coordinates = torch.randn(100, 3) * 5.0
reflectivity = torch.rand(100) * 0.8 + 0.1

# Initialize calculator
calculator = RAPiDCalculator(device="cpu")

# Extract features
features = calculator.compute_rapid_features(coordinates, reflectivity, k=8)
print(f"Features shape: {features.shape}")

📚 Learn More

  1. Start with: examples/01_getting_started.py
  2. Advanced features: examples/02_advanced_features.py
  3. Semantic processing: examples/03_c_rapid_semantic.py
  4. Memory optimization: examples/04_memory_optimization.py
  5. Performance tuning: examples/05_performance_benchmarking.py
  6. Real-world integration: examples/06_integration_examples.py

🔧 Configuration

from rapid_seg.config import create_config

# Fast configuration for real-time applications
fast_config = create_config("fast")

# Balanced configuration for general use
balanced_config = create_config("balanced")

# Accurate configuration for high-quality features
accurate_config = create_config("accurate")

📖 Full Documentation

🆘 Need Help?

🚨 Common Installation Mistakes

Remember: This project can ONLY be installed from source!

# ❌ These will NOT work:
pip install rapid-seg
conda install rapid-seg
uv pip install rapid-seg

# ✅ This IS the correct way:
git clone https://github.com/l1997i/rapid-seg.git
cd rapid-seg
uv pip install -e .

Happy coding with RAPiD! 🎯