tlancon

// Requirements:
// Trainable Weka Segmentation

// The list of files to use for training must be described in a text file,
// with each line containing the full path to one image.

listOfImages = File.openDialog("Choose a file with a list of images:");
imagesString = File.openAsString(listOfImages);
images = split(imagesString, "\n");
for (i=0; i<images.length; i++) {

tlancon

def copy_lut(from_layer, to_layer, opacity=False):
    """
    Copies the visualization properties from one layer to another in napari.
    
    Only the colormap, contrast limits, and gamma values are included by default.
    
    The opacity can be optionally copied as well.
    
    Blending and interpolation are ignored.
    

tlancon

import os
import napari
from skimage.io import imread, imsave

def napari_count_tfpn(screenshot_file, point_size=20, save_screenshot=True):
    """
    Opens a napari window and initializes three points layers:
        - "True Positives" with green points
        - "False Positives" with red points
        - "False Negatives" with yellow points

tlancon

# Inspired by https://gist.github.com/JeffPaine/3083347
# Access full state names using us_states.keys()
# Access all state abbreviations using us_states.values()
us_states = {
	'Alabama': 'AL',
	'Alaska': 'AK',
	'Arizona': 'AZ',
	'Arkansas': 'AR',
	'California': 'CA',
	'Colorado': 'CO',