run_createImagePairs.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)
    args = parser.parse_args()
    config = Config
    if args.tissue:
        config.diagnosis = [args.tissue]

    if args.outputFolder:
        config.outputFolder = args.outputFolder

    if args.scale:
        config.scale=int(args.scale)

    if args.tissue == 'Ganglioneuroma':
        n_freq = 20
    else:
        n_freq = 30
    print("Scale: " + args.scale)

    print(config.diagnosis)
    print(config.outputFolder)
    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(tools.getLocalDataPath(elem[1],1),tools.getLocalDataPath(groundtruth_path[0],3))
        test.readFromPath(ids_images[index], ids_masks[index],type='uint16')
        enhanced_images = tools.enhanceImage(test,flip_left_right=True,flip_up_down=True,deform=False)
        for index,img in enumerate(enhanced_images):
            annotated_nuclei.addObjectImage(img,useBorderObjects=config.useBorderObjects)

    # Create the image pairs
    tools.createPix2pixDataset(annotated_nuclei,config,n_freq = n_freq,tissue=args.tissue)

    e=1

main()