retina_svl_custom_elaboration.c File Reference

Tutorial 5 - Retina - How to do training and detection with custom elaboration. More...

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

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Data Structures
struct	retina_svl_user_data

Functions
sb_t_err	create_retina_project_file (SB_HANDLE *retina)
	Create a retina project file. More...
sb_t_err	set_samples (SB_HANDLE retina)
	Set samples. More...
sb_t_err	execute_svl (void)
	Execute svl. More...
sb_t_err	detection (void)
	Detection on resized images. More...
int	main (void)

Detailed Description

Tutorial 5 - Retina - How to do training and detection with custom elaboration.

This tutorial shows how to use:

• the luts (see Lut)
• the SVL callbacks (see SVL Callbacks)

You should follow the following steps:

1. create a new project with the function sb_project_create
2. add a model to the project and set its parameters with the functions sb_project_get_par and sb_project_set_par
3. labeling the image, i.e. set the occurrences of the model in the dataset images
4. execute the training with the function sb_svl_run
5. perform a detection with the function sb_project_detection For more informations on the ROI see ROI management.

   See also

   sb_init

   sb_release

   sb_get_info

   sb_license_get_info

   sb_image_load

   sb_image_create

   sb_image_destroy

   sb_image_resize

   sb_roi_create

   sb_roi_destroy

   sb_roi_set_rect

   sb_lut_create

   sb_lut_destroy

   sb_lut_get_prt

   sb_image_info_load

   sb_image_info_destroy

   sb_image_info_save

   sb_image_info_set_notes

   sb_image_info_reset

   sb_image_info_add_sample

   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_par_format

   sb_svl_reset

   sb_svl_stop_request

   sb_svl_run

   sb_svl_get_res

   sb_svl_destroy_res

Definition in file retina_svl_custom_elaboration.c.

Function Documentation

create_retina_project_file()

sb_t_err create_retina_project_file

(

SB_HANDLE *

retina

)

Create a retina project file.

1. Create the handle RETINA.
2. Set parameters of the model of the object.
3. Save the Retina project file.

Definition at line 215 of file retina_svl_custom_elaboration.c.

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detection()

sb_t_err detection

(

void

)

Detection on resized images.

1. Get the solution information.
2. Load the Retina project from solution file
3. Load the image.
4. Create the roi
5. Elaborate the image.
6. Get the results.
7. Destroy the handles.

Definition at line 354 of file retina_svl_custom_elaboration.c.

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execute_svl()

sb_t_err execute_svl

(

void

)

Execute svl.

1. Get the solution information.
2. Load the project.
3. Reset a previous SVL.
4. Set SVL parameters and connect the callbacks.
   • Set the allowed images file extensions
   • Set the goodness target
   • Set the pre_elaboration callback to process each image before svl
   • Set the command callback to process user commands
   • Set the progress callback to manage the progress notification
   • Set the user data to store the user data
5. Run SVL.
6. Get training results.
7. Save SVL.
8. Destroy the handles.

Definition at line 304 of file retina_svl_custom_elaboration.c.

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main()

int main

(

void

)

In the following the list of the program steps:

• Initialization

1. Initialization of the SqueezeBrains library.
2. Wait until the license is active.

• SVL with custom image elaboration

1. Create Retina project file.
2. Add samples to images.
3. Execute SVL.

• Detection with custom image elaboration

1. Destroy the handle.

• Release the library.

Definition at line 168 of file retina_svl_custom_elaboration.c.

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set_samples()

sb_t_err set_samples

(

SB_HANDLE

retina

)

Set samples.

1. Add samples to images.
2. Destroy the handle.

Definition at line 243 of file retina_svl_custom_elaboration.c.

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