camera.utils.display Namespace Reference

Classes
class	plotfig

Functions
def	bgr_cv (bgr, ratio=None, window_name="Image")
	Display rgb image using the OpenCV. More...
def	binary_cv (bIm, ratio=None, window_name="Binary")
	Display binary image using OpenCV display routines. More...
def	close_cv (window_name)
def	depth_cv (depth, depth_clip=0.08, ratio=None, window_name="OpenCV Display")
	Display depth image using OpenCV window. More...
def	display_dep_cv (depth, depth_clip=0.08, ratio=None, window_name="OpenCV Display")
	Display depth image using OpenCV window. More...
def	display_rgb_dep_cv (rgb, depth, depth_clip=0.08, ratio=None, window_name="OpenCV Display")
def	display_rgb_dep_plt (rgb, depth, suptitle=None, figsize=(10, 5), fh=None)
def	gray_cv (gim, ratio=None, window_name="Image")
	Display grayscale image using the OpenCV. More...
def	images_cv (list images, ratio=None, window_name="OpenCV Display")
def	rgb_binary_cv (cIm, bIm, ratio=None, window_name="Color+Binary")
	Display an RGB and binar image side-by-side using OpenCV API. More...
def	rgb_cv (rgb, ratio=None, window_name="Image")
	Display rgb image using the OpenCV. More...
def	rgb_depth_cv (rgb, depth, depth_clip=0.08, ratio=None, window_name="OpenCV Display")
def	trackpoint_binary_cv (bIm, p, ratio=None, window_name="Image")
	Display rgb image using the OpenCV. More...
def	trackpoint_cv (rgb, p, ratio=None, window_name="Image")
	Display rgb image using the OpenCV. More...
def	trackpoint_gray_cv (gIm, p, ratio=None, window_name="Image")
	Display grayscale image using the OpenCV. More...
def	trackpoints_cv (rgb, p, ratio=None, window_name="Image")
	Display rgb image using the OpenCV. More...
def	wait_cv (dur=0)
def	wait_for_confirm (Callable rgb_dep_getter, color_type="rgb", window_name="display", instruction="Press \'c\' key to select the frames. Press \'q\' to return None", capture_click=False, ratio=None)

Variables
	color
	color_type
	dep
	imgSource
	instruction
	ratio
	suptitle
	window_name

Function Documentation

bgr_cv()

def camera.utils.display.bgr_cv	(		bgr,
			ratio = None,
			window_name = "Image"
	)

Display rgb image using the OpenCV.

The rgb frame will be resized to a visualization size prior to visualization. Args: rgb (np.ndarray, (H, W, 3)): The rgb image ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

binary_cv()

def camera.utils.display.binary_cv	(		bIm,
			ratio = None,
			window_name = "Binary"
	)

Display binary image using OpenCV display routines.

The binary frame will be resized as indicated prior to visualization.

Parameters

[in]	bIm	Binary image as a numpy H x W ndarray.
[in]	ratio	Resize ratio of image to display (float, optional). Default is None = no resizing.
[in]	window_name	Window display name (Default = "Binary").

close_cv()

def camera.utils.display.close_cv

(

window_name

)

depth_cv()

def camera.utils.display.depth_cv	(		depth,
			depth_clip = 0.08,
			ratio = None,
			window_name = "OpenCV Display"
	)

Display depth image using OpenCV window.

The depth frame will be scaled to have the range 0-255. There will be no color bar for the depth

Args: depth (np.ndarray, (H, W)): The depth map depth_clip (float in [0, 1]): The depth value clipping percentage. The top and bottom extreme depth value to remove. Default to 0.0 (no clipping) ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

display_dep_cv()

def camera.utils.display.display_dep_cv	(		depth,
			depth_clip = 0.08,
			ratio = None,
			window_name = "OpenCV Display"
	)

Display depth image using OpenCV window.

The depth frame will be scaled to have the range 0-255. There will be no color bar for the depth

Args: depth (np.ndarray, (H, W)): The depth map depth_clip (float in [0, 1]): The depth value clipping percentage. The top and bottom extreme depth value to remove. Default to 0.0 (no clipping) ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

display_rgb_dep_cv()

def camera.utils.display.display_rgb_dep_cv	(		rgb,
			depth,
			depth_clip = 0.08,
			ratio = None,
			window_name = "OpenCV Display"
	)

Display the rgb and depth image using the OpenCV

The depth frame will be scaled to have the range 0-255.
The rgb and the depth frame will be resized to a visualization size and then concatenate together horizontally 
Then the concatenated image will be displayed in a same window.

There will be no color bar for the depth

Args:
    rgb (np.ndarray, (H, W, 3)): The rgb image
    depth (np.ndarray, (H, W)): The depth map
    depth_clip (float in [0, 1]): The depth value clipping percentage. The top and bottom extreme depth value to remove. Default to 0.0 (no clipping)
    ratio (float, Optional): Allow resizing the images before display.  Defaults to None, which means will perform no resizing
    window_name (sting, Optional): The window name for display. Defaults to \"OpenCV display\"

display_rgb_dep_plt()

def camera.utils.display.display_rgb_dep_plt	(		rgb,
			depth,
			suptitle = None,
			figsize = (10,5),
			fh = None
	)

Display the rgb and depth image in a same figure at two different axes
The depth will be displayed with a colorbar beside.

NOTE: This function use the matplotlib for visualization, which is SLOW.
SO it is not suitable for real-time visualization (e.g. Visualize the camera feed)

Args:
    rgb (np.ndarray, (H, W, 3)): The rgb image
    depth (np.ndarray, (H, W)): The depth map
    suptitle (str, optional): The suptitle for display. Defaults to None, which will display no suptitle
    figsize (tuple, optional): The figure size following the matplotlib style. Defaults to (10,5).
    fh (matplotlib.Figure): The figure handle. Defaults to None, which means a new figure handle will be created.

gray_cv()

def camera.utils.display.gray_cv	(		gim,
			ratio = None,
			window_name = "Image"
	)

Display grayscale image using the OpenCV.

The rgb frame will be resized to a visualization size prior to visualization. Args: rgb (np.ndarray, (H, W, 3)): The rgb image ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

images_cv()

def camera.utils.display.images_cv	(	list	images,
			ratio = None,
			window_name = "OpenCV Display"
	)

@brief  Display a set of images horizontally concatenated (side-by-side).

Args:
    images (list): A list of the OpenCV images (bgr) of the same size
    window_name (str, Optional): The window name for display. Defaults to \"OpenCV display\"

rgb_binary_cv()

def camera.utils.display.rgb_binary_cv	(		cIm,
			bIm,
			ratio = None,
			window_name = "Color+Binary"
	)

Display an RGB and binar image side-by-side using OpenCV API.

The images will be resized as indicated by the ratio and concatenated horizontally. The concatenated image is what gets displayed in the window.

Parameters

[in]	cIm	Color image (RGB).
[in]	bIm	Binary image (0/1 or logical)
[in]	ratio	Resizing ratio.
[in]	window_name	Window name for display.

rgb_cv()

def camera.utils.display.rgb_cv	(		rgb,
			ratio = None,
			window_name = "Image"
	)

Display rgb image using the OpenCV.

The rgb frame will be resized to a visualization size prior to visualization. Args: rgb (np.ndarray, (H, W, 3)): The rgb image ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

rgb_depth_cv()

def camera.utils.display.rgb_depth_cv	(		rgb,
			depth,
			depth_clip = 0.08,
			ratio = None,
			window_name = "OpenCV Display"
	)

@brief  Display rgb and depth images side-by-side using OpenCV.

Depth frame will be scaled to range [0,255].
The rgb and the depth images will be resized to visualization size, then concatenated horizontally.
The concatenated image will be displayed in a window.
There will be no color bar for the depth

Args:
    rgb (np.ndarray, (H, W, 3)): The rgb image
    depth (np.ndarray, (H, W)): The depth map
    depth_clip (float in [0, 1]): The depth value clipping percentage. The top and bottom extreme depth value to remove. Default to 0.0 (no clipping)
    ratio (float, Optional): Allow resizing the images before display.  Defaults to None, which means will perform no resizing
    window_name (sting, Optional): The window name for display. Defaults to \"OpenCV display\"

trackpoint_binary_cv()

def camera.utils.display.trackpoint_binary_cv	(		bIm,
			p,
			ratio = None,
			window_name = "Image"
	)

Display rgb image using the OpenCV.

The rgb frame will be resized to a visualization size prior to visualization. Args: rgb (np.ndarray, (H, W, 3)): The rgb image ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

trackpoint_cv()

def camera.utils.display.trackpoint_cv	(		rgb,
			p,
			ratio = None,
			window_name = "Image"
	)

Display rgb image using the OpenCV.

The rgb frame will be resized to a visualization size prior to visualization. Args: rgb (np.ndarray, (H, W, 3)): The rgb image ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

trackpoint_gray_cv()

def camera.utils.display.trackpoint_gray_cv	(		gIm,
			p,
			ratio = None,
			window_name = "Image"
	)

Display grayscale image using the OpenCV.

The rgb frame will be resized to a visualization size prior to visualization. Args: rgb (np.ndarray, (H, W, 3)): The rgb image ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

trackpoints_cv()

def camera.utils.display.trackpoints_cv	(		rgb,
			p,
			ratio = None,
			window_name = "Image"
	)

Display rgb image using the OpenCV.

The rgb frame will be resized to a visualization size prior to visualization. Args: rgb (np.ndarray, (H, W, 3)): The rgb image ratio (float, Optional): Allow resizing the images before display. Defaults to None, which means will perform no resizing window_name (sting, Optional): The window name for display. Defaults to "OpenCV display"

wait_cv()

def camera.utils.display.wait_cv

(

dur = 0

)

wait_for_confirm()

def camera.utils.display.wait_for_confirm	(	Callable	rgb_dep_getter,
			color_type = "rgb",
			window_name = "display",
			instruction = "Press \'c\' key to select the frames. Press \'q\' to return None",
			capture_click = False,
			ratio = None
	)

An interface function for letting the user select the desired frame \
    from the given sensor source. The function will display the color and the depth \
    information received from the source, and then wait for the user to confirm via keyboard. 

NOTE: can't distinguish different keys for now. So only support "press any key to confirm"

Args:
    color_dep_getter (Callable): The color and depth source. \
        Expect to get the sensor information in the np.ndarray format via: \
                    rgb, depth = color_dep_getter() \
        When there is no more info, expected to return None
    color_type (str): The color type. RGB or BGR. Will be used for visualization
    window_name (str):
    instruction ([type], optional): The instruction text printed to the user for selection. Defaults to None.
    ratio (float, Optional): Allow resizing the images before display.  Defaults to None, which means will perform no resizing

Returns:
    rgb [np.ndarray]: The rgb image confirmed by the user
    depth [np.ndarray]: The depth frame confirmed by the user

Variable Documentation

color

color

color_type

color_type

dep

dep

imgSource

imgSource

Initial value:

=  lambda : (
        (np.random.rand(100,100,3) * 255).astype(np.uint8), \
        np.random.rand(100,100)
    )

instruction

instruction

ratio

ratio

suptitle

suptitle

window_name

window_name