Trait RetinaTrait

pub trait RetinaTrait: AlgorithmTrait + RetinaTraitConst {
    // Required method
    fn as_raw_mut_Retina(&mut self) -> *mut c_void;

    // Provided methods
    fn get_input_size(&mut self) -> Result<Size> { ... }
    fn get_output_size(&mut self) -> Result<Size> { ... }
    fn setup_from_file(
        &mut self,
        retina_parameter_file: &str,
        apply_default_setup_on_failure: bool,
    ) -> Result<()> { ... }
    fn setup_from_file_def(&mut self) -> Result<()> { ... }
    fn setup_from_storage(
        &mut self,
        fs: &mut impl FileStorageTrait,
        apply_default_setup_on_failure: bool,
    ) -> Result<()> { ... }
    fn setup_from_storage_def(
        &mut self,
        fs: &mut impl FileStorageTrait,
    ) -> Result<()> { ... }
    fn setup(
        &mut self,
        new_parameters: impl RetinaParametersTrait,
    ) -> Result<()> { ... }
    fn get_parameters(&mut self) -> Result<RetinaParameters> { ... }
    fn print_setup(&mut self) -> Result<String> { ... }
    fn setup_op_land_ipl_parvo_channel(
        &mut self,
        color_mode: bool,
        normalise_output: bool,
        photoreceptors_local_adaptation_sensitivity: f32,
        photoreceptors_temporal_constant: f32,
        photoreceptors_spatial_constant: f32,
        horizontal_cells_gain: f32,
        hcells_temporal_constant: f32,
        hcells_spatial_constant: f32,
        ganglion_cells_sensitivity: f32,
    ) -> Result<()> { ... }
    fn setup_op_land_ipl_parvo_channel_def(&mut self) -> Result<()> { ... }
    fn setup_ipl_magno_channel(
        &mut self,
        normalise_output: bool,
        parasol_cells_beta: f32,
        parasol_cells_tau: f32,
        parasol_cells_k: f32,
        amacrin_cells_temporal_cut_frequency: f32,
        v0_compression_parameter: f32,
        local_adaptintegration_tau: f32,
        local_adaptintegration_k: f32,
    ) -> Result<()> { ... }
    fn setup_ipl_magno_channel_def(&mut self) -> Result<()> { ... }
    fn run(&mut self, input_image: &impl ToInputArray) -> Result<()> { ... }
    fn apply_fast_tone_mapping(
        &mut self,
        input_image: &impl ToInputArray,
        output_tone_mapped_image: &mut impl ToOutputArray,
    ) -> Result<()> { ... }
    fn get_parvo(
        &mut self,
        retina_output_parvo: &mut impl ToOutputArray,
    ) -> Result<()> { ... }
    fn get_parvo_raw_to(
        &mut self,
        retina_output_parvo: &mut impl ToOutputArray,
    ) -> Result<()> { ... }
    fn get_magno(
        &mut self,
        retina_output_magno: &mut impl ToOutputArray,
    ) -> Result<()> { ... }
    fn get_magno_raw_to(
        &mut self,
        retina_output_magno: &mut impl ToOutputArray,
    ) -> Result<()> { ... }
    fn set_color_saturation(
        &mut self,
        saturate_colors: bool,
        color_saturation_value: f32,
    ) -> Result<()> { ... }
    fn set_color_saturation_def(&mut self) -> Result<()> { ... }
    fn clear_buffers(&mut self) -> Result<()> { ... }
    fn activate_moving_contours_processing(
        &mut self,
        activate: bool,
    ) -> Result<()> { ... }
    fn activate_contours_processing(&mut self, activate: bool) -> Result<()> { ... }
}

Mutable methods for crate::bioinspired::Retina

Required Methods

fn as_raw_mut_Retina(&mut self) -> *mut c_void

Provided Methods

fn get_input_size(&mut self) -> Result<Size>

Retreive retina input buffer size

Returns

the retina input buffer size

fn get_output_size(&mut self) -> Result<Size>

Retreive retina output buffer size that can be different from the input if a spatial log transformation is applied

Returns

the retina output buffer size

fn setup_from_file( &mut self, retina_parameter_file: &str, apply_default_setup_on_failure: bool, ) -> Result<()>

Try to open an XML retina parameters file to adjust current retina instance setup

• if the xml file does not exist, then default setup is applied
• warning, Exceptions are thrown if read XML file is not valid

Parameters

• retinaParameterFile: the parameters filename
• applyDefaultSetupOnFailure: set to true if an error must be thrown on error

You can retrieve the current parameters structure using the method Retina::getParameters and update it before running method Retina::setup.

C++ default parameters

• retina_parameter_file: “”
• apply_default_setup_on_failure: true

fn setup_from_file_def(&mut self) -> Result<()>

Try to open an XML retina parameters file to adjust current retina instance setup

• if the xml file does not exist, then default setup is applied
• warning, Exceptions are thrown if read XML file is not valid

Parameters

• retinaParameterFile: the parameters filename
• applyDefaultSetupOnFailure: set to true if an error must be thrown on error

You can retrieve the current parameters structure using the method Retina::getParameters and update it before running method Retina::setup.

Note

This alternative version of RetinaTrait::setup_from_file function uses the following default values for its arguments:

• retina_parameter_file: “”
• apply_default_setup_on_failure: true

fn setup_from_storage( &mut self, fs: &mut impl FileStorageTrait, apply_default_setup_on_failure: bool, ) -> Result<()>

Try to open an XML retina parameters file to adjust current retina instance setup

• if the xml file does not exist, then default setup is applied
• warning, Exceptions are thrown if read XML file is not valid

Parameters

• retinaParameterFile: the parameters filename
• applyDefaultSetupOnFailure: set to true if an error must be thrown on error

You can retrieve the current parameters structure using the method Retina::getParameters and update it before running method Retina::setup.

Overloaded parameters

• fs: the open Filestorage which contains retina parameters
• applyDefaultSetupOnFailure: set to true if an error must be thrown on error

C++ default parameters

• apply_default_setup_on_failure: true

fn setup_from_storage_def( &mut self, fs: &mut impl FileStorageTrait, ) -> Result<()>

@overload

Parameters

• fs: the open Filestorage which contains retina parameters
• applyDefaultSetupOnFailure: set to true if an error must be thrown on error

Note

This alternative version of RetinaTrait::setup_from_storage function uses the following default values for its arguments:

• apply_default_setup_on_failure: true

fn setup(&mut self, new_parameters: impl RetinaParametersTrait) -> Result<()>

Try to open an XML retina parameters file to adjust current retina instance setup

• if the xml file does not exist, then default setup is applied
• warning, Exceptions are thrown if read XML file is not valid

Parameters

• retinaParameterFile: the parameters filename
• applyDefaultSetupOnFailure: set to true if an error must be thrown on error

You can retrieve the current parameters structure using the method Retina::getParameters and update it before running method Retina::setup.

Overloaded parameters

• newParameters: a parameters structures updated with the new target configuration.

fn get_parameters(&mut self) -> Result<RetinaParameters>

Returns

the current parameters setup

fn print_setup(&mut self) -> Result<String>

Outputs a string showing the used parameters setup

Returns

a string which contains formated parameters information

fn setup_op_land_ipl_parvo_channel( &mut self, color_mode: bool, normalise_output: bool, photoreceptors_local_adaptation_sensitivity: f32, photoreceptors_temporal_constant: f32, photoreceptors_spatial_constant: f32, horizontal_cells_gain: f32, hcells_temporal_constant: f32, hcells_spatial_constant: f32, ganglion_cells_sensitivity: f32, ) -> Result<()>

Setup the OPL and IPL parvo channels (see biologocal model)

OPL is referred as Outer Plexiform Layer of the retina, it allows the spatio-temporal filtering which withens the spectrum and reduces spatio-temporal noise while attenuating global luminance (low frequency energy) IPL parvo is the OPL next processing stage, it refers to a part of the Inner Plexiform layer of the retina, it allows high contours sensitivity in foveal vision. See reference papers for more informations. for more informations, please have a look at the paper Benoit A., Caplier A., Durette B., Herault, J., “USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING”, Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011

Parameters

• colorMode: specifies if (true) color is processed of not (false) to then processing gray level image
• normaliseOutput: specifies if (true) output is rescaled between 0 and 255 of not (false)
• photoreceptorsLocalAdaptationSensitivity: the photoreceptors sensitivity renage is 0-1 (more log compression effect when value increases)
• photoreceptorsTemporalConstant: the time constant of the first order low pass filter of the photoreceptors, use it to cut high temporal frequencies (noise or fast motion), unit is frames, typical value is 1 frame
• photoreceptorsSpatialConstant: the spatial constant of the first order low pass filter of the photoreceptors, use it to cut high spatial frequencies (noise or thick contours), unit is pixels, typical value is 1 pixel
• horizontalCellsGain: gain of the horizontal cells network, if 0, then the mean value of the output is zero, if the parameter is near 1, then, the luminance is not filtered and is still reachable at the output, typicall value is 0
• HcellsTemporalConstant: the time constant of the first order low pass filter of the horizontal cells, use it to cut low temporal frequencies (local luminance variations), unit is frames, typical value is 1 frame, as the photoreceptors
• HcellsSpatialConstant: the spatial constant of the first order low pass filter of the horizontal cells, use it to cut low spatial frequencies (local luminance), unit is pixels, typical value is 5 pixel, this value is also used for local contrast computing when computing the local contrast adaptation at the ganglion cells level (Inner Plexiform Layer parvocellular channel model)
• ganglionCellsSensitivity: the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity… and the output saturates faster, recommended value: 0.7

C++ default parameters

• color_mode: true
• normalise_output: true
• photoreceptors_local_adaptation_sensitivity: 0.7f
• photoreceptors_temporal_constant: 0.5f
• photoreceptors_spatial_constant: 0.53f
• horizontal_cells_gain: 0.f
• hcells_temporal_constant: 1.f
• hcells_spatial_constant: 7.f
• ganglion_cells_sensitivity: 0.7f

fn setup_op_land_ipl_parvo_channel_def(&mut self) -> Result<()>

Setup the OPL and IPL parvo channels (see biologocal model)

OPL is referred as Outer Plexiform Layer of the retina, it allows the spatio-temporal filtering which withens the spectrum and reduces spatio-temporal noise while attenuating global luminance (low frequency energy) IPL parvo is the OPL next processing stage, it refers to a part of the Inner Plexiform layer of the retina, it allows high contours sensitivity in foveal vision. See reference papers for more informations. for more informations, please have a look at the paper Benoit A., Caplier A., Durette B., Herault, J., “USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING”, Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011

Parameters

• colorMode: specifies if (true) color is processed of not (false) to then processing gray level image
• normaliseOutput: specifies if (true) output is rescaled between 0 and 255 of not (false)
• photoreceptorsLocalAdaptationSensitivity: the photoreceptors sensitivity renage is 0-1 (more log compression effect when value increases)
• photoreceptorsTemporalConstant: the time constant of the first order low pass filter of the photoreceptors, use it to cut high temporal frequencies (noise or fast motion), unit is frames, typical value is 1 frame
• photoreceptorsSpatialConstant: the spatial constant of the first order low pass filter of the photoreceptors, use it to cut high spatial frequencies (noise or thick contours), unit is pixels, typical value is 1 pixel
• horizontalCellsGain: gain of the horizontal cells network, if 0, then the mean value of the output is zero, if the parameter is near 1, then, the luminance is not filtered and is still reachable at the output, typicall value is 0
• HcellsTemporalConstant: the time constant of the first order low pass filter of the horizontal cells, use it to cut low temporal frequencies (local luminance variations), unit is frames, typical value is 1 frame, as the photoreceptors
• HcellsSpatialConstant: the spatial constant of the first order low pass filter of the horizontal cells, use it to cut low spatial frequencies (local luminance), unit is pixels, typical value is 5 pixel, this value is also used for local contrast computing when computing the local contrast adaptation at the ganglion cells level (Inner Plexiform Layer parvocellular channel model)
• ganglionCellsSensitivity: the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity… and the output saturates faster, recommended value: 0.7

Note

This alternative version of RetinaTrait::setup_op_land_ipl_parvo_channel function uses the following default values for its arguments:

• color_mode: true
• normalise_output: true
• photoreceptors_local_adaptation_sensitivity: 0.7f
• photoreceptors_temporal_constant: 0.5f
• photoreceptors_spatial_constant: 0.53f
• horizontal_cells_gain: 0.f
• hcells_temporal_constant: 1.f
• hcells_spatial_constant: 7.f
• ganglion_cells_sensitivity: 0.7f

fn setup_ipl_magno_channel( &mut self, normalise_output: bool, parasol_cells_beta: f32, parasol_cells_tau: f32, parasol_cells_k: f32, amacrin_cells_temporal_cut_frequency: f32, v0_compression_parameter: f32, local_adaptintegration_tau: f32, local_adaptintegration_k: f32, ) -> Result<()>

Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel

this channel processes signals output from OPL processing stage in peripheral vision, it allows motion information enhancement. It is decorrelated from the details channel. See reference papers for more details.

Parameters

• normaliseOutput: specifies if (true) output is rescaled between 0 and 255 of not (false)
• parasolCells_beta: the low pass filter gain used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), typical value is 0
• parasolCells_tau: the low pass filter time constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is frame, typical value is 0 (immediate response)
• parasolCells_k: the low pass filter spatial constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is pixels, typical value is 5
• amacrinCellsTemporalCutFrequency: the time constant of the first order high pass fiter of the magnocellular way (motion information channel), unit is frames, typical value is 1.2
• V0CompressionParameter: the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity… and the output saturates faster, recommended value: 0.95
• localAdaptintegration_tau: specifies the temporal constant of the low pas filter involved in the computation of the local “motion mean” for the local adaptation computation
• localAdaptintegration_k: specifies the spatial constant of the low pas filter involved in the computation of the local “motion mean” for the local adaptation computation

C++ default parameters

• normalise_output: true
• parasol_cells_beta: 0.f
• parasol_cells_tau: 0.f
• parasol_cells_k: 7.f
• amacrin_cells_temporal_cut_frequency: 1.2f
• v0_compression_parameter: 0.95f
• local_adaptintegration_tau: 0.f
• local_adaptintegration_k: 7.f

fn setup_ipl_magno_channel_def(&mut self) -> Result<()>

Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel

this channel processes signals output from OPL processing stage in peripheral vision, it allows motion information enhancement. It is decorrelated from the details channel. See reference papers for more details.

Parameters

• normaliseOutput: specifies if (true) output is rescaled between 0 and 255 of not (false)
• parasolCells_beta: the low pass filter gain used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), typical value is 0
• parasolCells_tau: the low pass filter time constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is frame, typical value is 0 (immediate response)
• parasolCells_k: the low pass filter spatial constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is pixels, typical value is 5
• amacrinCellsTemporalCutFrequency: the time constant of the first order high pass fiter of the magnocellular way (motion information channel), unit is frames, typical value is 1.2
• V0CompressionParameter: the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity… and the output saturates faster, recommended value: 0.95
• localAdaptintegration_tau: specifies the temporal constant of the low pas filter involved in the computation of the local “motion mean” for the local adaptation computation
• localAdaptintegration_k: specifies the spatial constant of the low pas filter involved in the computation of the local “motion mean” for the local adaptation computation

Note

This alternative version of RetinaTrait::setup_ipl_magno_channel function uses the following default values for its arguments:

• normalise_output: true
• parasol_cells_beta: 0.f
• parasol_cells_tau: 0.f
• parasol_cells_k: 7.f
• amacrin_cells_temporal_cut_frequency: 1.2f
• v0_compression_parameter: 0.95f
• local_adaptintegration_tau: 0.f
• local_adaptintegration_k: 7.f

fn run(&mut self, input_image: &impl ToInputArray) -> Result<()>

Method which allows retina to be applied on an input image,

after run, encapsulated retina module is ready to deliver its outputs using dedicated acccessors, see getParvo and getMagno methods

Parameters

• inputImage: the input Mat image to be processed, can be gray level or BGR coded in any format (from 8bit to 16bits)

fn apply_fast_tone_mapping( &mut self, input_image: &impl ToInputArray, output_tone_mapped_image: &mut impl ToOutputArray, ) -> Result<()>

Method which processes an image in the aim to correct its luminance correct backlight problems, enhance details in shadows.

This method is designed to perform High Dynamic Range image tone mapping (compress >8bit/pixel images to 8bit/pixel). This is a simplified version of the Retina Parvocellular model (simplified version of the run/getParvo methods call) since it does not include the spatio-temporal filter modelling the Outer Plexiform Layer of the retina that performs spectral whitening and many other stuff. However, it works great for tone mapping and in a faster way.

Check the demos and experiments section to see examples and the way to perform tone mapping using the original retina model and the method.

Parameters

• inputImage: the input image to process (should be coded in float format : CV_32F, CV_32FC1, CV_32F_C3, CV_32F_C4, the 4th channel won’t be considered).
• outputToneMappedImage: the output 8bit/channel tone mapped image (CV_8U or CV_8UC3 format).

fn get_parvo( &mut self, retina_output_parvo: &mut impl ToOutputArray, ) -> Result<()>

Accessor of the details channel of the retina (models foveal vision).

Warning, getParvoRAW methods return buffers that are not rescaled within range [0;255] while the non RAW method allows a normalized matrix to be retrieved.

Parameters

• retinaOutput_parvo: the output buffer (reallocated if necessary), format can be :
• a Mat, this output is rescaled for standard 8bits image processing use in OpenCV
• RAW methods actually return a 1D matrix (encoding is R1, R2, … Rn, G1, G2, …, Gn, B1, B2, …Bn), this output is the original retina filter model output, without any quantification or rescaling.

See also

getParvoRAW

fn get_parvo_raw_to( &mut self, retina_output_parvo: &mut impl ToOutputArray, ) -> Result<()>

Accessor of the details channel of the retina (models foveal vision).

See also

getParvo

fn get_magno( &mut self, retina_output_magno: &mut impl ToOutputArray, ) -> Result<()>

Accessor of the motion channel of the retina (models peripheral vision).

Warning, getMagnoRAW methods return buffers that are not rescaled within range [0;255] while the non RAW method allows a normalized matrix to be retrieved.

Parameters

• retinaOutput_magno: the output buffer (reallocated if necessary), format can be :
• a Mat, this output is rescaled for standard 8bits image processing use in OpenCV
• RAW methods actually return a 1D matrix (encoding is M1, M2,… Mn), this output is the original retina filter model output, without any quantification or rescaling.

See also

getMagnoRAW

fn get_magno_raw_to( &mut self, retina_output_magno: &mut impl ToOutputArray, ) -> Result<()>

Accessor of the motion channel of the retina (models peripheral vision).

See also

getMagno

fn set_color_saturation( &mut self, saturate_colors: bool, color_saturation_value: f32, ) -> Result<()>

Activate color saturation as the final step of the color demultiplexing process -> this saturation is a sigmoide function applied to each channel of the demultiplexed image.

Parameters

• saturateColors: boolean that activates color saturation (if true) or desactivate (if false)
• colorSaturationValue: the saturation factor : a simple factor applied on the chrominance buffers

C++ default parameters

• saturate_colors: true
• color_saturation_value: 4.0f

fn set_color_saturation_def(&mut self) -> Result<()>

Activate color saturation as the final step of the color demultiplexing process -> this saturation is a sigmoide function applied to each channel of the demultiplexed image.

Parameters

• saturateColors: boolean that activates color saturation (if true) or desactivate (if false)
• colorSaturationValue: the saturation factor : a simple factor applied on the chrominance buffers

Note

This alternative version of RetinaTrait::set_color_saturation function uses the following default values for its arguments:

• saturate_colors: true
• color_saturation_value: 4.0f

fn clear_buffers(&mut self) -> Result<()>

Clears all retina buffers

(equivalent to opening the eyes after a long period of eye close ;o) whatchout the temporal transition occuring just after this method call.

fn activate_moving_contours_processing(&mut self, activate: bool) -> Result<()>

Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated

Parameters

• activate: true if Magnocellular output should be activated, false if not… if activated, the Magnocellular output can be retrieved using the getMagno methods

fn activate_contours_processing(&mut self, activate: bool) -> Result<()>

Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated

Parameters

• activate: true if Parvocellular (contours information extraction) output should be activated, false if not… if activated, the Parvocellular output can be retrieved using the Retina::getParvo methods

Dyn Compatibility

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementors

impl RetinaTrait for BoxedRefMut<'_, Retina>

impl RetinaTrait for Ptr<Retina>

impl RetinaTrait for Retina