deep_cortex_svl_simple.c File Reference

Tutorial 13 - Deep Cortex - How to create a project, set model to images and execute the training (SVL). More...

#include "../common/common.h"

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Functions
sb_t_err	create_deep_cortex_project_file (SB_HANDLE *deep_cortex)
	Create a deep_cortex project file. More...
sb_t_err	set_model_to_images (SB_HANDLE deep_cortex)
	Set samples. More...
sb_t_err	execute_training (void)
	Execute training. More...
int	main (void)

Detailed Description

Tutorial 13 - Deep Cortex - How to create a project, set model to images and execute the training (SVL).

Attention

To execute this tutorial you need:

• to have installed the SB Deep Learning Framework
• to ensure that path to SB Deep Learning Framework is included in the PATH enviroment variable (LD_LIBRARY_PATH in Linux) or in any case to be visible by the program. In Windows it is possible to specify additional paths as argument to the sb_init_dl function.

This tutorial shows you what you should do to train a model using a set of images and starting from scratch, i.e. without using the SB GUI. You should follow the following steps:

1. create a new project with the function sb_project_create
2. add a list of models to the project with the functions sb_project_get_par, sb_project_set_par and sb_par_add_model
3. labeling the images, i.e. add a model sample to each image in the dataset
4. execute the training with the function sb_svl_run

   See also

   sb_init

   sb_init_dl

   sb_release

   sb_get_info

   sb_license_get_info

   sb_project_create

   sb_solution_get_info

   sb_solution_destroy_info

   sb_project_load

   sb_project_destroy

   sb_project_save

   sb_project_get_par

   sb_project_set_par

   sb_par_add_model

   sb_image_info_load

   sb_image_info_destroy

   sb_image_info_save

   sb_image_info_reset

   sb_get_uuid

   sb_svl_reset

   sb_svl_run

   sb_svl_get_res

   sb_svl_destroy_res

Definition in file deep_cortex_svl_simple.c.

Function Documentation

create_deep_cortex_project_file()

sb_t_err create_deep_cortex_project_file

(

SB_HANDLE *

deep_cortex

)

Create a deep_cortex project file.

1. Add models to the project
2. Save the Deep Cortex project file.

Definition at line 112 of file deep_cortex_svl_simple.c.

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execute_training()

sb_t_err execute_training

(

void

)

Execute training.

1. Get the solution information.
2. Load the project.
3. Reset a previous training.
4. Set training parameters.
   • set device for SVL
   • set network parameters
   • set perturbations (flip, rotation, shift)
5. Execute the training (SVL).
6. Get training results.
7. Save the training.
8. Destroy the handles.

Definition at line 200 of file deep_cortex_svl_simple.c.

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main()

int main

(

void

)

In the following the list of the program steps:

1. Initialization of the SqueezeBrains library.
2. Initialization of the Squeezebrains deep learning modules.
3. Wait until the license is active.
4. Create Deep Cortex project file.
5. Add samples to images.
6. Execute training.
7. Destroy the project handle.
8. Release the library.

Definition at line 61 of file deep_cortex_svl_simple.c.

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set_model_to_images()

sb_t_err set_model_to_images

(

SB_HANDLE

deep_cortex

)

Set samples.

1. Set the parameters common to all the model samples. For each sample:
   • Set the sample as required
   • Set the scale to 1.0, i.e. no scaling
2. Add a model sample for each image in the dataset. For each one:
   • Set the flag classified of the image in order for the image to be considered for the learning
   • Set the sample centre position
   • Set the sample UUID in order to uniquely identify the sample
   • Add the sample to the image

Definition at line 136 of file deep_cortex_svl_simple.c.

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