navigate.controller.sub_controllers.camera_view.BaseViewController

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

Bases: GUIController, ABaseViewController

Base View Controller Class.

__init__(view, parent_controller=None) → None

Initialize the Camera View Controller Class.

Parameters:

• view (tkinter.Frame) – The 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.
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_mode([mode])	Sets mode of camera_view_controller.
show_verbose_info(*info)	Prints verbose information to the console
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_experiment_values()	Collects all the values of widgets
update_lut(target)	Update the LUT 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 the controller
image_mode	The imaging mode.
apply_cross_hair	The flag for the display of the cross-hair.
autoscale	The flag for autoscaling the image intensity.
bit_depth	The bit depth of the image.
canvas	The tkinter canvas that displays the image.
width	The width of the canvas.
height	The height of the image.
canvas_height	The height of the canvas.
canvas_height_scale	The scaling factor for the height of the canvas.
canvas_width	The width of the canvas.
canvas_width_scale	The scaling factor for the width of the canvas.
colormap	The colormap for the image.
mode	The mode of the camera view controller.
microscope_name	The microscope name
flip_flags	The flip flags for the camera.
image	The image data.
image_cache_flag	The flag for the image cache.
image_count	The count of images.
is_displaying_image	The lock for displaying the image.
logger	The logger for the camera view controller.
max_counts	The maximum counts of the image.
min_counts	The minimum counts of the image.
number_of_channels	The number of channels in the image.
number_of_slices	The number of slices in the image volume.
original_image_height	The original height of the image.
original_image_width	The original width of the image.
resize_event_id	The resize event ID.
saturated_pixels	The saturated pixels in the image.
selected_channels	The selected channels being acquired.
slice_index	The index of the slice in the image volume.
stack_cycling_mode	The stack cycling mode.
tk_image	The tkinter image.
tk_image2	The tkinter image 2.
total_images_per_volume	The total number of images per volume.
transpose	The flag for transposing the image.
zoom_height	The zoom scale of the image.
zoom_offset	The zoom offset of the image.
zoom_rect	The zoom rectangle of the image.
zoom_scale	The zoom scale of the image.
zoom_value	The zoom value of the image.
zoom_width	The zoom width of the image.
image_palette	The dictionary of image palette widgets.
move_to_x	The x position of the mouse.
move_to_y	The y position of the mouse.
crosshair_x	Percentage of crosshair in x
crosshair_y	Percentage of crosshair in y
offset_crosshair	the flag for offsetting the crosshair

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

Parameters:

image (numpy.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.

Parameters:

image (np.ndarray) – Image data.

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, data) → None

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_mode(mode: str = '') → None

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

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.

Note

This function is called when an image is acquired. The image is passed to the display function. If the display function is already displaying an image, the function will return. Thus, if imaging is faster than the display, the display will skip frames.

Parameters:

image (np.ndarray) – Image data.

update_canvas_size() → None

Update the canvas size.

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_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 the controller

flip_flags

The flip flags for the camera.

Type:

dict

height

The height of the image.

Type:

int

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_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

max_counts

The maximum counts of the image.

Type:

int

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

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