Canny edge detection folder

operators.image.canny_edge_detection_folder(client, input_folder='/input_folder', output_folder='/output_folder', sigma=1.0, low_threshold=0.1, high_threshold=0.2, values_subset='', worker_instance_type='x2large', manager_instance_type='small', extension_input_file='.tif', extension_output_file='.tif', skip_existing_files=False)

Perform Canny edge detection on a georeferenced image and save the detected edges as a raster.

canny_edge_detection_folder(client,

input_folder=’/input_folder’,

output_folder=’/output_folder’,

sigma=1.0,

low_threshold=0.1,

high_threshold=0.2,

values_subset=’’,

worker_instance_type=’x2large’,

manager_instance_type=”small”,

extension_input_folder=”.tif”,

extension_output_folder=”.tif”,

skip_existing_files = False )

Parameters:

• sigma – Standard deviation of the Gaussian filter

• low_threshold – Low threshold for hysteresis

• high_threshold – High threshold for hysteresis

• values_subset – Subset of values to extract contours from, all values by default

• input_folder – Input image folder

• output_folder – Output edge raster folder

• worker_instance_type – cloud instance type of worker nodes

• manager_instance_type – cloud instance type of manager node

• extension_input_folder – File extension of files in folder for input_folder

• extension_output_folder – File extension of files in folder for output_folder

• skip_existing_files – skip files that already exist in the output folder