ms_camera_model package

Submodules

ms_camera_model.data_comparison module

Multispectral Camera Model - Data Comparison

  • Description: Classes and their methods used for comparing real MS data with modeled data

  • Author: Tomas Vacek

class ms_camera_model.data_comparison.DataComparator(ms_img_data, modeled_img_data)[source]

Bases: object

Parameters:
compare_band_ratios(set_areas_globaly=True)[source]

Compare band ratios of real MS image data with modeled MS image data

Parameters:

set_areas_globaly (bool)

Return type:

tuple[list[float], list[float]]

ms_camera_model.errors module

Multispectral Camera Model - Custom Errors

  • Description: Custom error definitions to improve readability and make debugging easier

  • Author: Tomas Vacek

exception ms_camera_model.errors.ImageDataIncompatible[source]

Bases: Exception

Image Data isn’t incompatible

exception ms_camera_model.errors.IncompatibleBandChoice[source]

Bases: Exception

Chosen bands are not compatible with this method

exception ms_camera_model.errors.NoImageData[source]

Bases: Exception

Provided ImageData instance doesn’t contain img_data

exception ms_camera_model.errors.NoProvidedArea[source]

Bases: Exception

No area was provided

exception ms_camera_model.errors.NoProvidedFilepaths[source]

Bases: Exception

No filepaths were provided

ms_camera_model.filter_sensor module

Multispectral Camera Model - Filters and Sensors

  • Description: Dataclasses and their methods for filters and sensors

  • Author: Tomas Vacek

class ms_camera_model.filter_sensor.FilterSensorUnit(filter_spec, sensor_spec)[source]

Bases: object

Combination of filter and sensor

Parameters:
calculate_combined_attenuation()[source]

Calculate combined attenuation of filter and sensor based on their transmission and qe (quantum efficiency) curve

Return type:

None

combined_attenuation: ndarray
filter_spec: FilterSpecs
classmethod from_excel(filename_filter, filename_sensor)[source]

Load filter transmission and sensor spectral sensitivity from Excel file

Parameters:

  • filename_filter (str) – Filename or path to the filter xlsx file

  • filename_sensor (str) – Filename or path to the sensor xlsx file

Return type:

FilterSensorUnit

interpolate_to_hs_data(hs_band_centers)[source]

Interpolate the provided filter and sensor data to hyperspectral data

Parameters:

hs_band_centers (list[float] | None)

Return type:

FilterSensorUnit

sensor_spec: SensorSpecs
class ms_camera_model.filter_sensor.FilterSpecs(filter_transmission, name='Generic', supplier='Generic', band_center=0, band_width=0)[source]

Bases: object

Filter specification

Parameters:

  • filter_transmission (ndarray)

  • name (str)

  • supplier (str)

  • band_center (int)

  • band_width (int)

band_center: int = 0
band_width: int = 0
filter_transmission: ndarray
name: str = 'Generic'
supplier: str = 'Generic'
class ms_camera_model.filter_sensor.SensorSpecs(sensor_qe_curve, name='Generic', supplier='Generic', sensor_type='CMOS')[source]

Bases: object

Sensor specification

Parameters:

  • sensor_qe_curve (ndarray)

  • name (str)

  • supplier (str)

  • sensor_type (str)

name: str = 'Generic'
sensor_qe_curve: ndarray
sensor_type: str = 'CMOS'
supplier: str = 'Generic'

ms_camera_model.image_data module

Multispectral Camera Model - Image Data

  • Description: Dataclasses and their methods for image data

  • Author: Tomas Vacek

class ms_camera_model.image_data.HyperspectralImageData(img_data, band_centers=None, nbands=None)[source]

Bases: ImageData

Hyperspectral Image Data - imported from hyperspectral data file

Method import_hs_img:

Import hyperspectral cube into img_data, band_centers and nbands

Parameters:

  • img_data (ndarray)

  • band_centers (list[float] | None)

  • nbands (int | None)

classmethod import_hs_img(filepath)[source]

Import hyperspectral cube as ImageData class instance

Parameters:

filepath (str) – path to the hyperspectral image file

Raises:

NoImageData – when spectral fails to load the image

Return type:

HyperspectralImageData

class ms_camera_model.image_data.ImageData(img_data, band_centers=None, nbands=None)[source]

Bases: object

Image Data class

Parameters:

  • img_data (ndarray) – np.ndarray of image data with shape (rows, cols, bands)

  • band_centers (list[float] | None) – list of floats storing the center of each band in the img_data array

  • nbands (int | None) – number of bands in the img_data array

Method __add__:

add two ImageData classes

Method imshow:

view the img_data as an RGB interpretation of selected bands or as a brightness plot

Method vector_normalize:

use vector normalization on the img_data

Method mean_spectrum_area:

calculate mean spectrum for a select area

Method plot_area_spectrum:

visualize the mean spectrum of an area

Method register_images:

register img_data of another ImageData class instance against this instance

band_centers: list[float] | None = None
img_data: ndarray
imshow(bands=None)[source]

View image as an RGB interpretation of selected bands or as a brightness plot

Parameters:

bands (list[int] | None) – list of band numbers, if the list is not provided, brightness plot will be used instead

Raises:

IncompatibleBandChoice – if ‘bands’ is not [], len(bands) != 3 or the number is out-of-bounds

Return type:

None

static mean_spectrum_area(img, corner_coords)[source]

Calculate mean over spectral bands for select area

Parameters:

  • img (ndarray) – image data

  • corner_coords (list[int]) – coordinates of corners of the area in format [ulx, uly, lrx, lry]

Return type:

ndarray

nbands: int | None = None
normalize_img_data()[source]

Normalize image data

Return type:

None

plot_area_spectrum(coordinates)[source]

Plot spectrum of pixels

Parameters:

coordinates (list[int]) – list[ulx, uly, lrx, lry] - ulx means upper left x, lry means lower right y, etc.

Return type:

None

register_bands(other, band_mask_paths_ref=None, band_mask_paths_src=None)[source]

Register img_data of another ImageData class instance against this instance

Parameters:

  • other (ImageData | int) – ImageData class instance that is being registered against this one

  • band_mask_paths_ref (list[str | None] | None) – list of mask file paths for reference images

  • band_mask_paths_src (list[str | None] | None) – list of mask file paths for source images

Raises:

ImageDataIncompatible – if the number of bands differs in self and other

Return type:

ImageData | None

vector_normalize()[source]

Normalize img data

Return type:

None

class ms_camera_model.image_data.MultispectralImageData(img_data, band_centers=None, nbands=None)[source]

Bases: ImageData

Multispectral Image Data - loaded from real MS camera

Method import_altum_pt_ms_imgs:

method for import of images from MicaSense Altum-PT camera

Method import_ms_imgs:

method for import of generic multispectral images

Method check_filepaths:

method which checks that filepaths are a non-empty list and are strings

Parameters:

  • img_data (ndarray)

  • band_centers (list[float] | None)

  • nbands (int | None)

static check_filepaths(filepaths)[source]

Check that provided list of filepaths is usable

Parameters:

filepaths (list[str]) – list of filepaths

Raises:

  • TypeError – when provided paths aren’t in list

  • TypeError – when provided paths aren’t strings

  • NoProvidedFilepaths – when there are no provided filepaths

Return type:

None

classmethod import_altum_pt_ms_imgs(filepaths, panel_calibration, panel_location)[source]

Import and pre-process Altum PT images

Parameters:

  • filepaths (list[str]) – list of filepaths to the multispectral images, their order determines order in the final array

  • panel_calibration (dict[str, float]) – panel_calibration data of used MicaSense CRP

  • panel_location (list[list[int]]) – panel_location information format [[ulx, uly, lrx, lry], [ulx, …]]

Raises:

  • NoProvidedArea – when the provided area of the CRP is None or empty

  • Exception – when the length of filepaths and panel_locations doesn’t match

  • TypeError – when provided paths aren’t in list

  • TypeError – when provided paths aren’t strings

  • NoProvidedFilepaths – when there are no provided filepaths

Return type:

MultispectralImageData

classmethod import_ms_imgs(filepaths)[source]

Import multispectral images as a np.ndarray

Parameters:

filepaths (list[str]) – list of filepaths to the multispectral images, their order determines order in the final array

Raises:

  • TypeError – when provided paths aren’t in list

  • TypeError – when provided paths aren’t strings

  • NoProvidedFilepaths – when there are no provided filepaths

Return type:

MultispectralImageData

ms_camera_model.model module

Multispectral Camera Model - Simulation Model

  • Description: Simulated model of a multispectral camera. Takes in hyperspectral data and colour filter specs. Outputs multispectral data

  • Author: Tomas Vacek

class ms_camera_model.model.MultispectralCameraModel(hs_data, filter_sensor_units)[source]

Bases: object

Multispectral camera model

Parameters:

  • hs_data (HyperspectralImageData) – HyperspectralImageData class instance

  • filter_sensor_units (list[FilterSensorUnit]) – list of FilterSensorUnit class instances

  • out_data – simulated multispectral image data as ImageData class instance

corrected_filter_sensor_units: list[FilterSensorUnit]
filter_sensor_units: list[FilterSensorUnit]
hs_data: HyperspectralImageData
out_data: ImageData
run_simulation()[source]

Match filter_sensor_units specs with hs_data band_centers and calculate out_data

Returns:

Returns resulting simulated ImageData

Return type:

ImageData

Module contents

Multispectral Camera Model - Simulation Model

Simulated model of a multispectral camera. Takes in hyperspectral data and colour filter specs. Outputs multispectral data

class ms_camera_model.DataComparator(ms_img_data, modeled_img_data)[source]

Bases: object

Parameters:
compare_band_ratios(set_areas_globaly=True)[source]

Compare band ratios of real MS image data with modeled MS image data

Parameters:

set_areas_globaly (bool)

Return type:

tuple[list[float], list[float]]

class ms_camera_model.FilterSensorUnit(filter_spec, sensor_spec)[source]

Bases: object

Combination of filter and sensor

Parameters:
calculate_combined_attenuation()[source]

Calculate combined attenuation of filter and sensor based on their transmission and qe (quantum efficiency) curve

Return type:

None

combined_attenuation: ndarray
filter_spec: FilterSpecs
classmethod from_excel(filename_filter, filename_sensor)[source]

Load filter transmission and sensor spectral sensitivity from Excel file

Parameters:

  • filename_filter (str) – Filename or path to the filter xlsx file

  • filename_sensor (str) – Filename or path to the sensor xlsx file

Return type:

FilterSensorUnit

interpolate_to_hs_data(hs_band_centers)[source]

Interpolate the provided filter and sensor data to hyperspectral data

Parameters:

hs_band_centers (list[float] | None)

Return type:

FilterSensorUnit

sensor_spec: SensorSpecs
class ms_camera_model.FilterSpecs(filter_transmission, name='Generic', supplier='Generic', band_center=0, band_width=0)[source]

Bases: object

Filter specification

Parameters:

  • filter_transmission (ndarray)

  • name (str)

  • supplier (str)

  • band_center (int)

  • band_width (int)

band_center: int = 0
band_width: int = 0
filter_transmission: ndarray
name: str = 'Generic'
supplier: str = 'Generic'
class ms_camera_model.HyperspectralImageData(img_data, band_centers=None, nbands=None)[source]

Bases: ImageData

Hyperspectral Image Data - imported from hyperspectral data file

Method import_hs_img:

Import hyperspectral cube into img_data, band_centers and nbands

Parameters:

  • img_data (ndarray)

  • band_centers (list[float] | None)

  • nbands (int | None)

classmethod import_hs_img(filepath)[source]

Import hyperspectral cube as ImageData class instance

Parameters:

filepath (str) – path to the hyperspectral image file

Raises:

NoImageData – when spectral fails to load the image

Return type:

HyperspectralImageData

class ms_camera_model.ImageData(img_data, band_centers=None, nbands=None)[source]

Bases: object

Image Data class

Parameters:

  • img_data (ndarray) – np.ndarray of image data with shape (rows, cols, bands)

  • band_centers (list[float] | None) – list of floats storing the center of each band in the img_data array

  • nbands (int | None) – number of bands in the img_data array

Method __add__:

add two ImageData classes

Method imshow:

view the img_data as an RGB interpretation of selected bands or as a brightness plot

Method vector_normalize:

use vector normalization on the img_data

Method mean_spectrum_area:

calculate mean spectrum for a select area

Method plot_area_spectrum:

visualize the mean spectrum of an area

Method register_images:

register img_data of another ImageData class instance against this instance

band_centers: list[float] | None = None
img_data: ndarray
imshow(bands=None)[source]

View image as an RGB interpretation of selected bands or as a brightness plot

Parameters:

bands (list[int] | None) – list of band numbers, if the list is not provided, brightness plot will be used instead

Raises:

IncompatibleBandChoice – if ‘bands’ is not [], len(bands) != 3 or the number is out-of-bounds

Return type:

None

static mean_spectrum_area(img, corner_coords)[source]

Calculate mean over spectral bands for select area

Parameters:

  • img (ndarray) – image data

  • corner_coords (list[int]) – coordinates of corners of the area in format [ulx, uly, lrx, lry]

Return type:

ndarray

nbands: int | None = None
normalize_img_data()[source]

Normalize image data

Return type:

None

plot_area_spectrum(coordinates)[source]

Plot spectrum of pixels

Parameters:

coordinates (list[int]) – list[ulx, uly, lrx, lry] - ulx means upper left x, lry means lower right y, etc.

Return type:

None

register_bands(other, band_mask_paths_ref=None, band_mask_paths_src=None)[source]

Register img_data of another ImageData class instance against this instance

Parameters:

  • other (ImageData | int) – ImageData class instance that is being registered against this one

  • band_mask_paths_ref (list[str | None] | None) – list of mask file paths for reference images

  • band_mask_paths_src (list[str | None] | None) – list of mask file paths for source images

Raises:

ImageDataIncompatible – if the number of bands differs in self and other

Return type:

ImageData | None

vector_normalize()[source]

Normalize img data

Return type:

None

class ms_camera_model.MultispectralCameraModel(hs_data, filter_sensor_units)[source]

Bases: object

Multispectral camera model

Parameters:

  • hs_data (HyperspectralImageData) – HyperspectralImageData class instance

  • filter_sensor_units (list[FilterSensorUnit]) – list of FilterSensorUnit class instances

  • out_data – simulated multispectral image data as ImageData class instance

corrected_filter_sensor_units: list[FilterSensorUnit]
filter_sensor_units: list[FilterSensorUnit]
hs_data: HyperspectralImageData
out_data: ImageData
run_simulation()[source]

Match filter_sensor_units specs with hs_data band_centers and calculate out_data

Returns:

Returns resulting simulated ImageData

Return type:

ImageData

class ms_camera_model.MultispectralImageData(img_data, band_centers=None, nbands=None)[source]

Bases: ImageData

Multispectral Image Data - loaded from real MS camera

Method import_altum_pt_ms_imgs:

method for import of images from MicaSense Altum-PT camera

Method import_ms_imgs:

method for import of generic multispectral images

Method check_filepaths:

method which checks that filepaths are a non-empty list and are strings

Parameters:

  • img_data (ndarray)

  • band_centers (list[float] | None)

  • nbands (int | None)

static check_filepaths(filepaths)[source]

Check that provided list of filepaths is usable

Parameters:

filepaths (list[str]) – list of filepaths

Raises:

  • TypeError – when provided paths aren’t in list

  • TypeError – when provided paths aren’t strings

  • NoProvidedFilepaths – when there are no provided filepaths

Return type:

None

classmethod import_altum_pt_ms_imgs(filepaths, panel_calibration, panel_location)[source]

Import and pre-process Altum PT images

Parameters:

  • filepaths (list[str]) – list of filepaths to the multispectral images, their order determines order in the final array

  • panel_calibration (dict[str, float]) – panel_calibration data of used MicaSense CRP

  • panel_location (list[list[int]]) – panel_location information format [[ulx, uly, lrx, lry], [ulx, …]]

Raises:

  • NoProvidedArea – when the provided area of the CRP is None or empty

  • Exception – when the length of filepaths and panel_locations doesn’t match

  • TypeError – when provided paths aren’t in list

  • TypeError – when provided paths aren’t strings

  • NoProvidedFilepaths – when there are no provided filepaths

Return type:

MultispectralImageData

classmethod import_ms_imgs(filepaths)[source]

Import multispectral images as a np.ndarray

Parameters:

filepaths (list[str]) – list of filepaths to the multispectral images, their order determines order in the final array

Raises:

  • TypeError – when provided paths aren’t in list

  • TypeError – when provided paths aren’t strings

  • NoProvidedFilepaths – when there are no provided filepaths

Return type:

MultispectralImageData

class ms_camera_model.SensorSpecs(sensor_qe_curve, name='Generic', supplier='Generic', sensor_type='CMOS')[source]

Bases: object

Sensor specification

Parameters:

  • sensor_qe_curve (ndarray)

  • name (str)

  • supplier (str)

  • sensor_type (str)

name: str = 'Generic'
sensor_qe_curve: ndarray
sensor_type: str = 'CMOS'
supplier: str = 'Generic'