navigate.controller.sub_controllers.camera_view.CameraViewController

class navigate.controller.sub_controllers.camera_view.CameraViewController(view, parent_controller=None)

Bases: BaseViewController

Camera View Controller Class.

__init__(view, parent_controller=None) → None

Initialize the Camera View Controller Class.

Parameters:

• view (CameraTab) – The Camera tkinter frame that contains the widgets.

• parent_controller (Controller) – The parent controller of the camera view controller.

Methods

__init__(view[, parent_controller])	Initialize the Camera View Controller Class.
add_crosshair(image)	Adds a cross-hair to the image.
apply_lut(image)	Applies a LUT to an image.
array_to_image(image)	Convert a numpy array to a PIL Image.
calculate_offset()	Calculates the offset of the image.
detect_saturation(image)	Look for any pixels at the maximum intensity allowable for the camera.
digital_zoom()	Apply digital zoom.
display_image(image)	Display an image using the LUT specified in the View.
display_mask(mask)	Display segmentation mask
down_sample_image(image)	Down-sample the data for image display according to widget size.
execute(command, *args)	This function is called when a command is passed from a child process.
flip_image(image)	Flip the image according to the flip flags.
get_absolute_position()	Gets the absolute position of the computer mouse.
get_selected_channels([microscope_state])	Get the selected microscope channels from the MicroscopeState.
identify_channel_index_and_slice()	As images arrive, identify channel index and slice.
initialize(name, data)	Sets widgets based on data given from main controller/config.
initialize_non_live_display(...)	Initialize the non-live display.
left_click(*_)	Toggles cross-hair on image upon left click event.
mark_position()	Marks the current position of the microscope in the multi-position acquisition table.
mouse_wheel(event)	Digitally zooms in or out on the image upon scroll wheel event.
move_crosshair()	Move the crosshair to a non-default position.
move_stage()	Move the stage according to the position the user clicked.
populate_image(image)	Converts image to an ImageTk.PhotoImage and populates the Tk Canvas
popup_menu(event)	Right-Click Popup Menu
process_image()	Process the image to be displayed.
refresh(width, height)	Refresh the window.
register_event_listener(event_name, ...)	Register event listener in the parent_controller
reset_display([display_flag, reset_crosshair])	Set the display back to the original digital zoom.
resize(event)	Resize the window.
scale_image_intensity(image)	Scale the data to the min/max counts, and adjust bit-depth.
set_experiment_values()	Sets values of widgets based on experiment setting
set_mask_color_table(colors)	Set up segmentation mask color table
set_mode([mode])	Sets mode of camera_view_controller.
show_verbose_info(*info)	Prints verbose information to the console
slider_update(*_)	Updates the image when the slider is moved.
toggle_min_max_buttons([display])	Checks the value of the autoscale widget.
transpose_image(image)	Transpose the image according to the flip flags.
try_to_display_image(image)	Try to display an image.
update_canvas_size()	Update the canvas size.
update_display_state(*_)	Image Display Combobox Called.
update_experiment_values()	Collects all the values of widgets
update_lut(target)	Update the LUT in the Camera View.
update_max_counts()	Update the max counts in the camera view.
update_min_max_counts([display])	Get min and max count values from the View.
update_snr()	Updates the signal-to-noise ratio.
update_transpose_state([display])	Get Flip XY widget value from the View.

Attributes

custom_events	Custom events for this controller
image_metrics	The dictionary of image metrics widgets.
display_state	The display state.
rolling_frames	The number of frames to average.
max_intensity_history	The list of maximum intensity values.
display_mask_flag	The flag for displaying the mask.
mask_color_table	The display mask flag.
ilastik_mask_ready_lock	The lock for the ilastik mask.
ilastik_seg_mask	The ilastik mask.

add_crosshair(image: ndarray) → ndarray

Adds a cross-hair to the image.

Parameters:

image (np.ndarray) – Image data.

Returns:

image – Image data with cross-hair.

Return type:

np.ndarray

apply_lut(image: ndarray) → ndarray

Applies a LUT to an image.

Red is reserved for saturated pixels. self.color_values = [‘gray’, ‘gradient’, ‘rainbow’]

Parameters:

image (np.ndarray) – Image data.

Returns:

image – Image data with LUT applied.

Return type:

np.ndarray

array_to_image(image: ndarray) → <module 'PIL.Image' from '/opt/hostedtoolcache/Python/3.9.22/x64/lib/python3.9/site-packages/PIL/Image.py'>

Convert a numpy array to a PIL Image.

If a color mask is present, it will apply the mask to the image.

Parameters:

image (np.ndarray) – Image data.

Returns:

image – A PIL Image

Return type:

Image

calculate_offset() → tuple

Calculates the offset of the image.

Returns:

• offset_x (int) – The offset of the image in x.

• offset_y (int) – The offset of the image in y.

detect_saturation(image: ndarray) → None

Look for any pixels at the maximum intensity allowable for the camera.

Note

The camera is set to 16-bit depth, so the maximum intensity is 2^16 - 1. If another camera is used, this function should be updated to reflect the maximum intensity value.

Parameters:

image (np.ndarray) – Image data.

digital_zoom() → ndarray

Apply digital zoom.

The x and y positions are between 0 and the canvas width and height respectively.

Returns:

image – Image after digital zoom applied

Return type:

np.ndarray

display_image(image: ndarray) → None

Display an image using the LUT specified in the View.

If Autoscale is selected, automatically calculates the min and max values for the data.

If Autoscale is not selected, takes the user values as specified in the min and max counts.

Parameters:

image (np.ndarray) – Image data.

display_mask(mask: ndarray) → None

Display segmentation mask

Parameters:

mask (np.ndarray) – Segmentation mask to display

down_sample_image(image: ndarray) → ndarray

Down-sample the data for image display according to widget size.

Interpolation type is cv2.INTER_LINEAR by default.

Parameters:

image (np.ndarray) – Image data.

Returns:

down_sampled_image – Down-sampled image data.

Return type:

np.ndarray

execute(command, *args)

This function is called when a command is passed from a child process.

Parameters:

• command (str) – command name

• args (tuple) – command arguments

flip_image(image: ndarray) → ndarray

Flip the image according to the flip flags.

Parameters:

image (np.ndarray) – Image data.

Returns:

image – Flipped and/or transposed image data.

Return type:

numpy.ndarray

get_absolute_position() → tuple

Gets the absolute position of the computer mouse.

Returns:

• x (int) – The x position of the mouse.

• y (int) – The y position of the mouse.

get_selected_channels(microscope_state: Optional[dict] = None) → None

Get the selected microscope channels from the MicroscopeState.

Parameters:

microscope_state (Optional[dict]) – The microscope state dictionary object.

identify_channel_index_and_slice() → tuple

As images arrive, identify channel index and slice.

Returns:

• channel_idx (int) – The channel index.

• slice_idx (int) – The slice index.

initialize(name: str, data: list)

Sets widgets based on data given from main controller/config.

Parameters:

• name (str) – ‘minmax’, ‘image’.

• data (list) – Min and max intensity values.

initialize_non_live_display(microscope_state: dict, camera_parameters: dict) → None

Initialize the non-live display.

Parameters:

• microscope_state (dict) – Microscope state.

• camera_parameters (dict) – Camera parameters.

left_click(*_) → None

Toggles cross-hair on image upon left click event.

mark_position() → None

Marks the current position of the microscope in the multi-position acquisition table.

mouse_wheel(event: Event) → None

Digitally zooms in or out on the image upon scroll wheel event.

Sets the self.zoom_value between 0.05 and 1 in .05 unit steps.

Parameters:

event (tk.Event) – num = 4 is zoom out. num = 5 is zoom in. x, y location. 0,0 is top left corner.

move_crosshair() → None

Move the crosshair to a non-default position.

move_stage() → None

Move the stage according to the position the user clicked.

populate_image(image: ndarray) → None

Converts image to an ImageTk.PhotoImage and populates the Tk Canvas

Note

When calling ImageTk.PhotoImage() to generate a new image, it will destroy what the canvas is showing, causing it to blink. This problem is solved by creating two images and alternating between them.

Parameters:

image (np.ndarray) – Image data.

popup_menu(event: Event) → None

Right-Click Popup Menu

Parameters:

event (tk.Event) – x, y location. 0,0 is top left corner.

process_image() → None

Process the image to be displayed.

Applies digital zoom, detects saturation, down-samples the image, scales the image intensity, adds a crosshair, applies the lookup table, and populates the image.

refresh(width: int, height: int) → None

Refresh the window.

Parameters:

• width (int) – Width of the window.

• height (int) – Height of the window.

register_event_listener(event_name, event_handler)

Register event listener in the parent_controller

Parameters:

• event_name (str) – event name

• event_handler (function) – event handler

reset_display(display_flag: bool = True, reset_crosshair: bool = True) → None

Set the display back to the original digital zoom.

Parameters:

• display_flag (bool) – Flag for refreshing the image display. Default True.

• reset_crosshair (bool) – Flag for resetting the crosshair. Default True.

resize(event: Event) → None

Resize the window.

Parameters:

event (tk.Event) – Tkinter event.

scale_image_intensity(image: ndarray) → ndarray

Scale the data to the min/max counts, and adjust bit-depth.

Parameters:

image (np.ndarray) – Image data.

Returns:

image – Scaled image data.

Return type:

np.ndarray

set_experiment_values()

Sets values of widgets based on experiment setting

setting_dict is a dictionary

set_mask_color_table(colors: list) → None

Set up segmentation mask color table

Parameters:

colors (list) – The list of colors to use for the segmentation mask

set_mode(mode: str = '')

Sets mode of camera_view_controller.

Parameters:

mode (str) – camera_view_controller mode.

show_verbose_info(*info)

Prints verbose information to the console

Parameters:

info (tuple) – information to be printed

slider_update(*_) → None

Updates the image when the slider is moved.

toggle_min_max_buttons(display: bool = False) → None

Checks the value of the autoscale widget.

If enabled, the min and max widgets are disabled and the image intensity is autoscaled. If disabled, miu and max widgets are enabled, and image intensity scaled.

transpose_image(image: ndarray) → ndarray

Transpose the image according to the flip flags.

Parameters:

image (np.ndarray) – Image data.

Returns:

image – Flipped and/or transposed image data.

Return type:

np.ndarray

try_to_display_image(image: ndarray) → None

Try to display an image.

In the live mode, images are automatically passed to the display function.

In the slice mode, images are passed to a spooled temporary file. However, when the same slice and channel index is acquired again, the image is updated. In all other cases, the image is only displayed upon slider events.

Parameters:

image (np.ndarray) – Image data.

update_canvas_size() → None

Update the canvas size.

update_display_state(*_) → None

Image Display Combobox Called.

Sets self.display_state to desired display format. Toggles state of slider widget. Sets number of positions.

update_experiment_values()

Collects all the values of widgets

setting_dict is a reference of experiment dictionary update the dictionary directly

update_lut(target) → None

Update the LUT in the Camera View.

When the LUT is changed in the GUI, this function is called. Updates the LUT.

update_max_counts() → None

Update the max counts in the camera view.

Function gets the number of frames to average from the VIEW.

If frames to average == 0 or 1, provides the maximum value from the last acquired data.

update_min_max_counts(display: bool = False)

Get min and max count values from the View.

When the min and max counts are toggled in the GUI, this function is called. Updates the min and max values.

Parameters:

display (bool) – Flag to display the image.

update_snr() → None

Updates the signal-to-noise ratio.

update_transpose_state(display: bool = False) → None

Get Flip XY widget value from the View.

If True, transpose the image.

apply_cross_hair

The flag for the display of the cross-hair.

Type:

bool

autoscale

The flag for autoscaling the image intensity.

Type:

bool

bit_depth

The bit depth of the image.

Type:

int

canvas

The tkinter canvas that displays the image.

Type:

tkinter.Canvas

canvas_height

The height of the canvas.

Type:

int

canvas_height_scale

The scaling factor for the height of the canvas.

Type:

int

canvas_width

The width of the canvas.

Type:

int

canvas_width_scale

The scaling factor for the width of the canvas.

Type:

int

colormap

The colormap for the image.

Type:

str

crosshair_x

Percentage of crosshair in x

Type:

float

crosshair_y

Percentage of crosshair in y

Type:

float

property custom_events

Custom events for this controller

Type:

dict

display_mask_flag

The flag for displaying the mask.

Type:

bool

display_state

The display state.

Type:

str

flip_flags

The flip flags for the camera.

Type:

dict

height

The height of the image.

Type:

int

ilastik_mask_ready_lock

The lock for the ilastik mask.

Type:

threading.Lock

ilastik_seg_mask

The ilastik mask.

Type:

numpy.ndarray

image

The image data.

Type:

numpy.ndarray

image_cache_flag

The flag for the image cache.

Type:

bool

image_count

The count of images.

Type:

int

image_metrics

The dictionary of image metrics widgets.

Type:

dict

image_mode

The imaging mode.

Type:

str

image_palette

The dictionary of image palette widgets.

Type:

dict

is_displaying_image

The lock for displaying the image.

Type:

VariableWithLock

logger

The logger for the camera view controller.

Type:

logging.Logger

mask_color_table

The display mask flag.

Type:

bool

max_counts

The maximum counts of the image.

Type:

int

max_intensity_history

The list of maximum intensity values.

Type:

list

microscope_name

The microscope name

Type:

str

min_counts

The minimum counts of the image.

Type:

int

mode

The mode of the camera view controller.

Type:

str

move_to_x

The x position of the mouse.

Type:

int

move_to_y

The y position of the mouse.

Type:

int

number_of_channels

The number of channels in the image.

Type:

int

number_of_slices

The number of slices in the image volume.

Type:

int

offset_crosshair

the flag for offsetting the crosshair

Type:

bool

original_image_height

The original height of the image.

Type:

int

original_image_width

The original width of the image.

Type:

int

parent_controller

parent controller

Type:

Controller

resize_event_id

The resize event ID.

Type:

event

rolling_frames

The number of frames to average.

Type:

int

saturated_pixels

The saturated pixels in the image.

Type:

np.ndarray

selected_channels

The selected channels being acquired.

Type:

list

slice_index

The index of the slice in the image volume.

Type:

int

stack_cycling_mode

The stack cycling mode.

Type:

str

tk_image

The tkinter image.

Type:

ImageTk.PhotoImage

tk_image2

The tkinter image 2.

Type:

ImageTk.PhotoImage

total_images_per_volume

The total number of images per volume.

Type:

int

transpose

The flag for transposing the image.

Type:

bool

view

GUI view

Type:

tkinter.Tk

width

The width of the canvas.

Type:

int

zoom_height

The zoom scale of the image.

Type:

float

zoom_offset

The zoom offset of the image.

Type:

numpy.ndarray

zoom_rect

The zoom rectangle of the image.

Type:

numpy.ndarray

zoom_scale

The zoom scale of the image.

Type:

float

zoom_value

The zoom value of the image.

Type:

float

zoom_width

The zoom width of the image.

Type:

int