The project structure is Visual Studio 2019 with Cuda 11.7 installed. If you are using a different version of Cuda, I find the easiest was to solve this is to edit the Visual Studio project file in a text editor and change the version number there.<\/p>\n\n\n\n
Overview<\/h2>\n\n\n\n
This is an example of re-scaling the size of the image in gray-scale floating point format accelerated using cuda on a GPU.<\/p>\n\n\n\n
This example creates a simulated image of 2048×2048. In actual image processing applications you will have an image that comes from a jpeg or tiff file and must be decoded, often into an array of RGB bytes or directly into a gray-scale format. Many image processing operations occur on a gray-scale version of the image encoded as floating point, typically of values 0 to 1, or -1 to +1.<\/p>\n\n\n\n
NVIDIA cuda comes with a library of basic image processing functions which are accelerated with parallel operations on the GPU, that run on top of the cuda library.<\/p>\n\n\n\n
One of these functions is nppiResize_32f_C1R_Ctx(). The file resize.cpp implements all the memory operations necessary to resize an image using nppiResize_32f_C1R_Ctx().<\/p>\n\n\n\n
The file resize.h provides a simple entry point for an image resize function which can be called from a c program with no knowledge of cuda programming.<\/p>\n\n\n\n
Code Details<\/h2>\n\n\n\n
Refer to the gitlab project link. The sample entry point from a c programing perspective is given in main.cu. The example implementation of nppiResize_32f_C1R_Ctx() is given in resize.cpp.<\/p>\n\n\n\n
Sample Results<\/h2>\n\n\n\n
In a machine learning application, I needed to analyze a biological image (cells growing into vessel structures imaged under a microscope). The scientist provided images that were sized at 5995 x 6207 pixels. This size is too extreme for the requirements of extracting the structures. Additionally, the AI models were trained on images typically in the range of 1000×1000 to 2000×2000 pixels. So I scale down the images using the resize_Cuda() function demonstrated in the example project.<\/p>\n\n\n\n
<\/p>\n\n\n\n
Here is the original image that is too large:<\/p>\n\n\n\n Here is the downsized image at 2000 x 2070 (the width was set to be 2000, our max AI trained size, the height was calculated to be 2070 to maintain the aspect ratio):<\/p>\n\n\n\n![\"\"](\"https:\/\/davidwdrell.net\/wordpress\/wp-content\/uploads\/2023\/03\/video_000001-989x1024.jpg\")
<\/a>![\"\"](\"https:\/\/davidwdrell.net\/wordpress\/wp-content\/uploads\/2023\/03\/debug_scaled_000000-989x1024.jpg\")
<\/a>
![\"\"](\"https:\/\/davidwdrell.net\/wordpress\/wp-content\/uploads\/2023\/03\/final-1024x1022.jpg\")
<\/a>