*```[]``` The first empty array indicates that this is an optional parameter. For Gaussian smoothing this parameter is to indicate how many times this smoothing should be performed.
*```[]``` The last parameter is to indicate which GPU to use. Passing an empty array indicates that all devices can be utilized. HIP will distribute work across each device when appropriate.
## Python Bindings (alpha)
Requirements:
* Windows 7 or above
*[Visual Studio 2015 Community Edition](https://visualstudio.microsoft.com/vs/older-downloads)
*[Python (64-bit) 3.4 or greater](https://www.python.org/downloads)
*[Numpy 1.12 or greater](http://www.numpy.org)
*[CUDA capable device](https://developer.nvidia.com/cuda-gpus) with the latest drivers installed
* Watchdog registry values set (see [Registry Changes](#registry-changes))
Experimental Python bindings have been created for the Hydra Image Processing library, however, they must currently be built from source, since Python versions only support limited binary compatibility.
### Windows Build
The full Hydra Image Processing library can be built using the Visual Studio solution file ```src/c/CudaImageProccessing.sln```. Python bindings are built as part of the main solution, or can be built separately by ```src/c/CudaPy3DLL.vcxproj```.
Two environment variables must be defined for a successful build:
1. PYTHON3_DIR - Root directory of the Python 3.x installation to build against
2. NUMPY3_DIR - Root directory of the Numpy installation to build against
It is currently simplest to build Python bindings using the full solution file, at present, as the Python project is dependent on the core image processing library. NOTE: Unless you have ```Debug``` build of Python 3.x, the bindings must be built in ```Release``` mode.
### Installation and Usage
After a successful build the file ```src/Python/HIP.pyd``` should be placed in a directory on the PYTHON_PATH to make the Hydra Image Processing tools accessible from Python.
For use in Python import the HIP module:
```
import HIP
```
Example of blurring a random numpy volume:
```
import HIP
import numpy as np
im = np.random.randint(0,256, size=(512,512,25), dtype=np.uint8)
imOut = HIP.Gaussian(im, [25,25,10])
```
# Feedback
If you would like to provide feedback about this tutorial or HIP in general, please use the forum [here](https://www.hydraimageprocessor.com/forum).
