run_createNaturalTiles.py

from Classes.Config import Config
from Classes.Helper import Tools
from Classes.Image import AnnotatedImage,AnnotatedObjectSet, ArtificialAnnotatedImage
from matplotlib import pyplot as plt
import os
import argparse
import glob

def main():
    parser = argparse.ArgumentParser(description='Train model.')
    parser.add_argument('--tissue', help='select tissue to train.', default=None)
    parser.add_argument('--inputFolder', help='Select input folder.', default=None)
    parser.add_argument('--outputFolder', help='select output folder', default=None)
    parser.add_argument('--scale', help='select output folder', default=None)
    parser.add_argument('--mode', help='select output folder', default='train')
    parser.add_argument('--resultsfile', help='select output folder', default=None)
    parser.add_argument('--overlap', help='select output folder', default=None)
    args = parser.parse_args()
    config = Config
    if args.tissue:
        config.diagnosis = [args.tissue]

    if args.outputFolder:
        config.outputFolder = args.outputFolder
    if args.scale == '1':
        config.scale=True
    if args.mode:
        config.mode=args.mode
    if args.resultsfile:
        config.resultsfile=args.resultsfile
    if args.overlap:
        config.overlap=int(args.overlap)

    print(config.diagnosis)
    print(config.outputFolder)
    print(config.scale)
    tools = Tools()

    annotated_nuclei = AnnotatedObjectSet()
    ids_images = glob.glob(os.path.join(args.inputFolder,config.diagnosis[0],'images','*.tif'))
    ids_masks = glob.glob(os.path.join(args.inputFolder, config.diagnosis[0], 'masks', '*.tif'))

    # Create dataset for training the pix2pix-network based on image pairs
    #for index,elem in enumerate(ids_paths):
    for index, elem in enumerate(ids_images):
        test = AnnotatedImage()
        test.readFromPath(ids_images[index], ids_masks[index],type='uint16')
        #enhanced_images = tools.enhanceImage(test,flip_left_right=True,flip_up_down=True,deform=True)
        #for index,img in enumerate(enhanced_images):
        #    annotated_nuclei.addObjectImage(img,useBorderObjects=config.useBorderObjects)
        annotated_nuclei.addObjectImage(test, useBorderObjects=config.useBorderObjects,path_to_img=ids_images[index])
    # Create and save the image tiles
    tools.createAndSaveTiles(annotated_nuclei,config)

main()