niryo_libraries.niryo_robot_vision.image

module documentation

Undocumented

Function	`add_annotation_to_image`	Add Annotation to an image
Function	`biggest_contour_finder`	Undocumented
Function	`biggest_contours_finder`	Function to find the biggest contour in an binary image
Function	`compress_image`	Compress OpenCV image
Function	`concat_imgs`	Concat multiple images along 1 axis
Function	`debug_markers`	Display detected markers on an image
Function	`debug_threshold_color`	Return masked image to see the effect of color threshold
Function	`draw_contours`	Draw a list of contour on an image and return the drawing image
Function	`extract_img_from_ros_msg`	Take a ROS CompressedImage message and return the image uncompressed
Function	`extract_img_workspace`	Extract working area from an image thanks to 4 Niryo's markers
Function	`get_contour_angle`	Return orientation of a contour according to the smallest side in order to be well oriented for gripper
Function	`get_contour_barycenter`	Return barycenter of an OpenCV Contour
Function	`improve_mask`	Improve binary mask with morphological operation
Function	`morphological_transformations`	Take black & white image and apply morphological transformation
Function	`relative_pos_from_pixels`	Transform a pixels position to a relative position
Function	`resize_img`	Resize an image. The user should precise only width or height if he wants to keep image's ratio
Function	`show_and_check_close`	Display an image and check whether the user want to close
Function	`show_and_wait_close`	Display an image and wait that the user close it
Function	`show_img`	Display an image during a certain time
Function	`threshold_blue`	Threshold hsv image of blue component :param img_hsv: hsv image to be threshold :type img_hsv: numpy.array :param blue_img: threshold img :rtype: numpy.array
Function	`threshold_green`	Threshold hsv image of green component :param img_hsv: hsv image to be threshold :type img_hsv: numpy.array :param green_img: threshold img :rtype: numpy.array
Function	`threshold_hsv`	Take BGR image (OpenCV imread result) and return thresholded image according to values on HSV (Hue, Saturation, Value) Pixel will worth 1 if a pixel has a value between min_v and max_v for all channels...
Function	`threshold_red`	Threshold hsv image of red component :param img_hsv: hsv image to be threshold :type img_hsv: numpy.array :param red_img: threshold img :rtype: numpy.array
Function	`uncompress_image`	Take a compressed img and return an OpenCV image
Function	`undistort_image`	Use camera intrinsics to undistort raw image
Variable	`keys_leave`	Undocumented

def add_annotation_to_image(img, text, write_on_top=True): ¶

Add Annotation to an image

Parameters
img:numpy.array	Image
text:str	text string
write_on_top:bool	if you write the text on top
Returns
numpy.array	img with text written on it

def biggest_contour_finder(img): ¶

Undocumented

def biggest_contours_finder(img, nb_contours_max=3): ¶

Function to find the biggest contour in an binary image

Parameters
img:numpy.array	Binary Image
nb_contours_max:int	maximal number of contours which will be returned
Returns
list[OpenCV Contour]	biggest contours found

def compress_image(img, quality=90): ¶

Compress OpenCV image

Parameters
img:numpy.array	OpenCV Image
quality:int	integer between 1 - 100. The higher it is, the less information will be lost, but the heavier the compressed image will be
Returns
bool, str	status & string representing compressed image

def concat_imgs(tuple_imgs, axis=1): ¶

Concat multiple images along 1 axis

Parameters
tuple_imgs:tuple[numpy.array]	tuple of images
axis:int	0 means vertically and 1 means horizontally
Returns
numpy.array	Concat image

def debug_markers(img, workspace_ratio=1.0): ¶

Display detected markers on an image

Parameters
img:numpy.array	OpenCV image which contain Niryo's markers
workspace_ratio:float	Ratio between the width and the height of the area represented by the markers
Returns
numpy.array	(status, annotated image)

def debug_threshold_color(img, color_hsv): ¶

Return masked image to see the effect of color threshold

Parameters
img:numpy.array	OpenCV image
color_hsv:ColorHSV	Color used for debug
Returns
numpy.array	Masked image

def draw_contours(img, contours): ¶

Draw a list of contour on an image and return the drawing image

Parameters
img:numpy.array	Image
contours:list[OpenCV Contour]	contours list
Returns
numpy.array	Image with drawing

def extract_img_from_ros_msg(ros_msg): ¶

Take a ROS CompressedImage message and return the image uncompressed

Parameters
ros_msg::sensor_msgs:`CompressedImage`	a ROS CompressedImage
Returns
numpy.array	image uncompressed

def extract_img_workspace(img, workspace_ratio=1.0): ¶

Extract working area from an image thanks to 4 Niryo's markers

Parameters
img:numpy.array	OpenCV image which contain 4 Niryo's markers
workspace_ratio:float	Ratio between the width and the height of the area represented by the markers
Returns
numpy.array	extracted and warped working area image

def get_contour_angle(contour): ¶

Return orientation of a contour according to the smallest side in order to be well oriented for gripper

Parameters
contour:OpenCV Contour	contour
Returns
float	Angle in radians

def get_contour_barycenter(contour): ¶

Return barycenter of an OpenCV Contour

Parameters
contour:OpenCV Contour
Returns
int, int	Barycenter X, Barycenter Y

def improve_mask(mask): ¶

Improve binary mask with morphological operation

Parameters
mask:numpy.array	input mask to improve
Returns
numpy.array	mask improved

def morphological_transformations(im_thresh, morpho_type=MorphoType.CLOSE, kernel_shape=(5, 5), kernel_type=KernelType.ELLIPSE): ¶

Take black & white image and apply morphological transformation

Parameters
im_thresh:numpy.array	Black & White Image
morpho_type:MorphoType	CLOSE/OPEN/ERODE/DILATE => See on OpenCV/Google if you do not know these words
kernel_shape:tuple[float]	tuple corresponding to the size of the kernel
kernel_type:KernelType	RECT/ELLIPSE/CROSS => see on OpenCV
Returns
numpy.array	image after processing

def relative_pos_from_pixels(img, x_pixels, y_pixels): ¶

Transform a pixels position to a relative position

Parameters
img:numpy.array	Image where the object is detected
x_pixels:int	coordinate X
y_pixels:int	coordinate Y
Returns
float, float	X relative, Y relative

def resize_img(img, width=None, height=None, inter=cv2.INTER_AREA): ¶

Resize an image. The user should precise only width or height if he wants to keep image's ratio

Parameters
img:numpy.array	OpenCV Image
width:int	Target Width
height:int	Target Height
inter:long	OpenCV interpolation flag
Returns
numpy.array	resized image

def show_and_check_close(window_name, img): ¶

Display an image and check whether the user want to close

Parameters
window_name:str	window's name
img:numpy.array	Image
Returns
bool	boolean indicating if the user wanted to leave

def show_and_wait_close(window_name, img): ¶

Display an image and wait that the user close it

Parameters
window_name:str	window's name
img:numpy.array	Image
Returns
None	None

def show_img(window_name, img, wait_ms=1): ¶

Display an image during a certain time

Parameters
window_name:str	window's name
img:numpy.array	Image
wait_ms:int	Wait time in milliseconds
Returns
int	value of the key pressed during the display

def threshold_blue(img_hsv): ¶

Threshold hsv image of blue component :param img_hsv: hsv image to be threshold :type img_hsv: numpy.array :param blue_img: threshold img :rtype: numpy.array

def threshold_green(img_hsv): ¶

Threshold hsv image of green component :param img_hsv: hsv image to be threshold :type img_hsv: numpy.array :param green_img: threshold img :rtype: numpy.array

def threshold_hsv(img, color_hsv): ¶

Take BGR image (OpenCV imread result) and return thresholded image according to values on HSV (Hue, Saturation, Value) Pixel will worth 1 if a pixel has a value between min_v and max_v for all channels

Parameters
img:numpy.array	image BGR if rgb_space = False
color_hsv	Undocumented
Returns
numpy.array	threshold image

def threshold_red(img_hsv): ¶

Threshold hsv image of red component :param img_hsv: hsv image to be threshold :type img_hsv: numpy.array :param red_img: threshold img :rtype: numpy.array

def uncompress_image(compressed_image): ¶

Take a compressed img and return an OpenCV image

Parameters
compressed_image:str	compressed image
Returns
numpy.array	OpenCV image

def undistort_image(img, mtx, dist): ¶

Use camera intrinsics to undistort raw image

Parameters
img:numpy.array	Raw Image
mtx:list[list[float]]	Camera Intrinsics matrix
dist:list[list[float]]	Distortion Coefficient
Returns
numpy.array	Undistorted image

keys_leave = ¶

Undocumented

niryo_libraries.niryo_robot_vision.image_functions

`niryo_libraries.niryo_robot_vision.image_functions`