Installation¶

This guide covers the installation of SMINT and its dependencies.

Prerequisites¶

SMINT requires the following:

Python 3.8 or higher
CUDA toolkit (for GPU support, optional)
R 4.0 or higher (for R integration, optional)

System Requirements¶

Memory: At least 16GB RAM, 32GB+ recommended for large images
CPU: Multi-core processor (8+ cores recommended)
GPU: NVIDIA GPU with at least 8GB VRAM (for GPU-accelerated segmentation, optional)
Storage: Depends on your image sizes, but typically 100GB+ free space

Installation Methods¶

Option 1: Install from PyPI (Recommended)¶

The simplest way to install SMINT is using pip:

pip install smint

Option 2: Install from Source¶

For the latest development version or to contribute to the project:

git clone https://github.com/JurgenKriel/SMINT.git
cd SMINT
pip install -e .

Dependencies¶

SMINT is designed with a modular approach to dependencies. Core functionality will work with minimal dependencies, while optional features require additional packages.

Core Dependencies (Automatically Installed)¶

These dependencies are automatically installed when you install SMINT:

numpy: For numerical operations
pandas: For data manipulation
matplotlib: For visualization
dask: For parallel computing (base package)
scikit-image: For image processing
tifffile: For reading/writing OME-TIFF files

Optional Dependencies¶

These dependencies enable additional features but are not required for core functionality:

Cell Segmentation¶

cellpose: For cell segmentation models
```
pip install cellpose
```
opencv-python: For image processing and contour extraction
```
pip install opencv-python
```

Distributed Processing¶

dask[distributed]: For distributed computing
```
pip install "dask[distributed]"
```
dask-cuda: For GPU-accelerated distributed computing (requires CUDA)
```
pip install dask-cuda
```

R Integration¶

rpy2: For direct R integration
```
pip install rpy2
```

Installation with All Optional Dependencies¶

To install SMINT with all optional dependencies:

pip install "smint[all]"

Or selectively:

pip install "smint[segmentation]"  # For cell segmentation features
pip install "smint[distributed]"   # For distributed computing features
pip install "smint[r]"             # For R integration features

Graceful Dependency Handling¶

SMINT is designed to degrade gracefully when optional dependencies are missing:

Missing a dependency? SMINT will log a warning but continue to operate with limited functionality.
Function that requires a missing dependency? You'll get a clear error message explaining which package you need to install.
Want to check available functionality? Run the following code:

import smint
print(f"SMINT package version: {smint.__version__}")
print("Available modules:")
[print(f"- {module}") for module in smint.__all__]

You can also check specific dependency availability:

# Check cellpose availability
try:
    import cellpose
    print("Cellpose is available")
except ImportError:
    print("Cellpose is not available")