Parallel implementations to accelerate the
autofocus process in microscopy applications
Juan C. Valdiviezo-N, Francisco J.
Hernandez-Lopez, Carina Toxqui-Quitl
autofocus_stacks_win
,
autofocus_stacks_ubuntu
:
This demo (autofocus_stacks) computes the autofocus function (VOL4,
MDCT, TEN and LAP) for a dataset. To run the demo, open a command
window, find the folder that contains the demo and call the
executable program as follows:
autofocus_stacks_MCore.exe <method> <path>
<num_init_folder> <num_last_folder> <N_Images>
<N_T2> <N_T1>
<N_T> //From
Windows
autofocus_stacks_GPU.exe <method> <path>
<num_init_folder> <num_last_folder> <N_Images>
<N_T2> <N_T1> <N_T>
./autofocus_stacks_MCore <method> <path>
<num_init_folder> <num_last_folder> <N_Images>
<N_T2> <N_T1> <N_T>
//From Linux
./autofocus_stacks_GPU <method> <path>
<num_init_folder> <num_last_folder> <N_Images>
<N_T2> <N_T1> <N_T>
where:
* method: number of method, 1--> VollathF4, 2--> MDCT,
3--> TEN, 4-->LAP
* path: path of the dataset, example:
D:/pictures/autofocus_stacks/
* num_init_init: number of the initial folder
* num_last_folder: number of the last folder
* N_Images: number of images inside each folder
* N_T2: Number of threads launched in the second external
for-loop of the algorithm
* N_T1: Number of threads launched in the first external
for-loop of the algorithm
* N_T: Number of threads launched in the inner for-loop of
the algorithm
Requirements:
- Windows versions 8.1 and 10
- Ubuntu 16.04
- CUDA
- OpenCV
This page was last modified on December, 2019 by Francisco J.
Hernandez-Lopez.