import os
import argparse
import numpy as np
import cv2

from Preprocessor import *

class FilePaths:
	raw = '../data/raw/'
	gray = '../data/gray/'
	gray_train = '../data/gray/train/'
	gray_test = '../data/gray/test/'
	threshed = '../data/threshed/'
	threshed_train = '../data/threshed/train/'
	threshed_test = '../data/threshed/test/'


parser = argparse.ArgumentParser(prog='train_prep',usage='%(prog)s [options] path', description='Prepare the training data by extracing the roi.')

parser.add_argument('Path', metavar='path', type=str, nargs='+', help='the path to raw images')
parser.add_argument('-d', '--divide', type=float, help='divide the images into a training set and a test set, give the proportion of test images')
parser.add_argument('--clear', action='store_true', help='clear the output directory')


args = parser.parse_args()
input_path = args.Path
# print(args)


# Print iterations progress from https://stackoverflow.com/questions/3173320/text-progress-bar-in-the-console
def printProgressBar (iteration, total, prefix = '', suffix = '', decimals = 1, length = 100, fill = '█', printEnd = "\r"):
    """
    Call in a loop to create terminal progress bar
    @params:
        iteration   - Required  : current iteration (Int)
        total       - Required  : total iterations (Int)
        prefix      - Optional  : prefix string (Str)
        suffix      - Optional  : suffix string (Str)
        decimals    - Optional  : positive number of decimals in percent complete (Int)
        length      - Optional  : character length of bar (Int)
        fill        - Optional  : bar fill character (Str)
        printEnd    - Optional  : end character (e.g. "\r", "\r\n") (Str)
    """
    percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
    filledLength = int(length * iteration // total)
    bar = fill * filledLength + '-' * (length - filledLength)
    print('\r%s |%s| %s%% %s' % (prefix, bar, percent, suffix), end = printEnd)
    # Print New Line on Complete
    if iteration == total: 
        print()

if args.divide is None and args.clear is False:
	for path in input_path:
		roi_gray, roi_thresh = extract_roi(read_img(path))
		cv2.imwrite(FilePaths.gray + os.path.basename(path), roi_gray)
		cv2.imwrite(FilePaths.threshed + os.path.basename(path), remove_border(roi_thresh))
		printProgressBar(input_path.index(path), len(input_path), prefix = 'Progress:', suffix = 'Complete')
elif args.clear:
	print("Removing all the images")
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_test))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_train))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_test))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_train))
else:
	permuted = np.random.permutation(input_path)
	index = int(len(input_path) * args.divide)
	test_path, train_path = permuted[:index], permuted[index:]
	for path in test_path:
		roi_gray, roi_thresh = extract_roi(read_img(path))
		cv2.imwrite(FilePaths.gray_test + os.path.basename(path), roi_gray)
		cv2.imwrite(FilePaths.threshed_test + os.path.basename(path), remove_border(roi_thresh))
		printProgressBar(test_path.tolist().index(path), len(input_path), prefix = 'Progress:', suffix = 'Complete')
	for path in train_path:
		roi_gray, roi_thresh = extract_roi(read_img(path))
		cv2.imwrite(FilePaths.gray_train + os.path.basename(path), roi_gray)
		cv2.imwrite(FilePaths.threshed_train + os.path.basename(path), remove_border(roi_thresh))
		printProgressBar(train_path.tolist().index(path) + len(test_path), len(input_path), prefix = 'Progress:', suffix = 'Complete')







44c2d3ad58d0e4ee5fe7c4b9feaa8a45579cd940
<mask token>


class FilePaths:
    raw = '../data/raw/'
    gray = '../data/gray/'
    gray_train = '../data/gray/train/'
    gray_test = '../data/gray/test/'
    threshed = '../data/threshed/'
    threshed_train = '../data/threshed/train/'
    threshed_test = '../data/threshed/test/'


<mask token>

<mask token>


class FilePaths:
    raw = '../data/raw/'
    gray = '../data/gray/'
    gray_train = '../data/gray/train/'
    gray_test = '../data/gray/test/'
    threshed = '../data/threshed/'
    threshed_train = '../data/threshed/train/'
    threshed_test = '../data/threshed/test/'


<mask token>
parser.add_argument('Path', metavar='path', type=str, nargs='+', help=
    'the path to raw images')
parser.add_argument('-d', '--divide', type=float, help=
    'divide the images into a training set and a test set, give the proportion of test images'
    )
parser.add_argument('--clear', action='store_true', help=
    'clear the output directory')
<mask token>


def printProgressBar(iteration, total, prefix='', suffix='', decimals=1,
    length=100, fill='█', printEnd='\r'):
    '\n    Call in a loop to create terminal progress bar\n    @params:\n        iteration   - Required  : current iteration (Int)\n        total       - Required  : total iterations (Int)\n        prefix      - Optional  : prefix string (Str)\n        suffix      - Optional  : suffix string (Str)\n        decimals    - Optional  : positive number of decimals in percent complete (Int)\n        length      - Optional  : character length of bar (Int)\n        fill        - Optional  : bar fill character (Str)\n        printEnd    - Optional  : end character (e.g. "\r", "\r\n") (Str)\n    '
    percent = ('{0:.' + str(decimals) + 'f}').format(100 * (iteration /
        float(total)))
    filledLength = int(length * iteration // total)
    bar = fill * filledLength + '-' * (length - filledLength)
    print('\r%s |%s| %s%% %s' % (prefix, bar, percent, suffix), end=printEnd)
    if iteration == total:
        print()


if args.divide is None and args.clear is False:
    for path in input_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(input_path.index(path), len(input_path), prefix=
            'Progress:', suffix='Complete')
elif args.clear:
    print('Removing all the images')
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_test))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_train))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_test))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_train))
else:
    permuted = np.random.permutation(input_path)
    index = int(len(input_path) * args.divide)
    test_path, train_path = permuted[:index], permuted[index:]
    for path in test_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray_test + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed_test + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(test_path.tolist().index(path), len(input_path),
            prefix='Progress:', suffix='Complete')
    for path in train_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray_train + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed_train + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(train_path.tolist().index(path) + len(test_path),
            len(input_path), prefix='Progress:', suffix='Complete')

<mask token>


class FilePaths:
    raw = '../data/raw/'
    gray = '../data/gray/'
    gray_train = '../data/gray/train/'
    gray_test = '../data/gray/test/'
    threshed = '../data/threshed/'
    threshed_train = '../data/threshed/train/'
    threshed_test = '../data/threshed/test/'


parser = argparse.ArgumentParser(prog='train_prep', usage=
    '%(prog)s [options] path', description=
    'Prepare the training data by extracing the roi.')
parser.add_argument('Path', metavar='path', type=str, nargs='+', help=
    'the path to raw images')
parser.add_argument('-d', '--divide', type=float, help=
    'divide the images into a training set and a test set, give the proportion of test images'
    )
parser.add_argument('--clear', action='store_true', help=
    'clear the output directory')
args = parser.parse_args()
input_path = args.Path


def printProgressBar(iteration, total, prefix='', suffix='', decimals=1,
    length=100, fill='█', printEnd='\r'):
    '\n    Call in a loop to create terminal progress bar\n    @params:\n        iteration   - Required  : current iteration (Int)\n        total       - Required  : total iterations (Int)\n        prefix      - Optional  : prefix string (Str)\n        suffix      - Optional  : suffix string (Str)\n        decimals    - Optional  : positive number of decimals in percent complete (Int)\n        length      - Optional  : character length of bar (Int)\n        fill        - Optional  : bar fill character (Str)\n        printEnd    - Optional  : end character (e.g. "\r", "\r\n") (Str)\n    '
    percent = ('{0:.' + str(decimals) + 'f}').format(100 * (iteration /
        float(total)))
    filledLength = int(length * iteration // total)
    bar = fill * filledLength + '-' * (length - filledLength)
    print('\r%s |%s| %s%% %s' % (prefix, bar, percent, suffix), end=printEnd)
    if iteration == total:
        print()


if args.divide is None and args.clear is False:
    for path in input_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(input_path.index(path), len(input_path), prefix=
            'Progress:', suffix='Complete')
elif args.clear:
    print('Removing all the images')
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_test))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_train))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_test))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_train))
else:
    permuted = np.random.permutation(input_path)
    index = int(len(input_path) * args.divide)
    test_path, train_path = permuted[:index], permuted[index:]
    for path in test_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray_test + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed_test + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(test_path.tolist().index(path), len(input_path),
            prefix='Progress:', suffix='Complete')
    for path in train_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray_train + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed_train + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(train_path.tolist().index(path) + len(test_path),
            len(input_path), prefix='Progress:', suffix='Complete')

import os
import argparse
import numpy as np
import cv2
from Preprocessor import *


class FilePaths:
    raw = '../data/raw/'
    gray = '../data/gray/'
    gray_train = '../data/gray/train/'
    gray_test = '../data/gray/test/'
    threshed = '../data/threshed/'
    threshed_train = '../data/threshed/train/'
    threshed_test = '../data/threshed/test/'


parser = argparse.ArgumentParser(prog='train_prep', usage=
    '%(prog)s [options] path', description=
    'Prepare the training data by extracing the roi.')
parser.add_argument('Path', metavar='path', type=str, nargs='+', help=
    'the path to raw images')
parser.add_argument('-d', '--divide', type=float, help=
    'divide the images into a training set and a test set, give the proportion of test images'
    )
parser.add_argument('--clear', action='store_true', help=
    'clear the output directory')
args = parser.parse_args()
input_path = args.Path


def printProgressBar(iteration, total, prefix='', suffix='', decimals=1,
    length=100, fill='█', printEnd='\r'):
    '\n    Call in a loop to create terminal progress bar\n    @params:\n        iteration   - Required  : current iteration (Int)\n        total       - Required  : total iterations (Int)\n        prefix      - Optional  : prefix string (Str)\n        suffix      - Optional  : suffix string (Str)\n        decimals    - Optional  : positive number of decimals in percent complete (Int)\n        length      - Optional  : character length of bar (Int)\n        fill        - Optional  : bar fill character (Str)\n        printEnd    - Optional  : end character (e.g. "\r", "\r\n") (Str)\n    '
    percent = ('{0:.' + str(decimals) + 'f}').format(100 * (iteration /
        float(total)))
    filledLength = int(length * iteration // total)
    bar = fill * filledLength + '-' * (length - filledLength)
    print('\r%s |%s| %s%% %s' % (prefix, bar, percent, suffix), end=printEnd)
    if iteration == total:
        print()


if args.divide is None and args.clear is False:
    for path in input_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(input_path.index(path), len(input_path), prefix=
            'Progress:', suffix='Complete')
elif args.clear:
    print('Removing all the images')
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_test))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_train))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_test))
    os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_train))
else:
    permuted = np.random.permutation(input_path)
    index = int(len(input_path) * args.divide)
    test_path, train_path = permuted[:index], permuted[index:]
    for path in test_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray_test + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed_test + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(test_path.tolist().index(path), len(input_path),
            prefix='Progress:', suffix='Complete')
    for path in train_path:
        roi_gray, roi_thresh = extract_roi(read_img(path))
        cv2.imwrite(FilePaths.gray_train + os.path.basename(path), roi_gray)
        cv2.imwrite(FilePaths.threshed_train + os.path.basename(path),
            remove_border(roi_thresh))
        printProgressBar(train_path.tolist().index(path) + len(test_path),
            len(input_path), prefix='Progress:', suffix='Complete')

import os
import argparse
import numpy as np
import cv2

from Preprocessor import *

class FilePaths:
	raw = '../data/raw/'
	gray = '../data/gray/'
	gray_train = '../data/gray/train/'
	gray_test = '../data/gray/test/'
	threshed = '../data/threshed/'
	threshed_train = '../data/threshed/train/'
	threshed_test = '../data/threshed/test/'


parser = argparse.ArgumentParser(prog='train_prep',usage='%(prog)s [options] path', description='Prepare the training data by extracing the roi.')

parser.add_argument('Path', metavar='path', type=str, nargs='+', help='the path to raw images')
parser.add_argument('-d', '--divide', type=float, help='divide the images into a training set and a test set, give the proportion of test images')
parser.add_argument('--clear', action='store_true', help='clear the output directory')


args = parser.parse_args()
input_path = args.Path
# print(args)


# Print iterations progress from https://stackoverflow.com/questions/3173320/text-progress-bar-in-the-console
def printProgressBar (iteration, total, prefix = '', suffix = '', decimals = 1, length = 100, fill = '█', printEnd = "\r"):
    """
    Call in a loop to create terminal progress bar
    @params:
        iteration   - Required  : current iteration (Int)
        total       - Required  : total iterations (Int)
        prefix      - Optional  : prefix string (Str)
        suffix      - Optional  : suffix string (Str)
        decimals    - Optional  : positive number of decimals in percent complete (Int)
        length      - Optional  : character length of bar (Int)
        fill        - Optional  : bar fill character (Str)
        printEnd    - Optional  : end character (e.g. "\r", "\r\n") (Str)
    """
    percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
    filledLength = int(length * iteration // total)
    bar = fill * filledLength + '-' * (length - filledLength)
    print('\r%s |%s| %s%% %s' % (prefix, bar, percent, suffix), end = printEnd)
    # Print New Line on Complete
    if iteration == total: 
        print()

if args.divide is None and args.clear is False:
	for path in input_path:
		roi_gray, roi_thresh = extract_roi(read_img(path))
		cv2.imwrite(FilePaths.gray + os.path.basename(path), roi_gray)
		cv2.imwrite(FilePaths.threshed + os.path.basename(path), remove_border(roi_thresh))
		printProgressBar(input_path.index(path), len(input_path), prefix = 'Progress:', suffix = 'Complete')
elif args.clear:
	print("Removing all the images")
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_test))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.gray_train))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_test))
	os.system('(cd {} && rm ./*.png)'.format(FilePaths.threshed_train))
else:
	permuted = np.random.permutation(input_path)
	index = int(len(input_path) * args.divide)
	test_path, train_path = permuted[:index], permuted[index:]
	for path in test_path:
		roi_gray, roi_thresh = extract_roi(read_img(path))
		cv2.imwrite(FilePaths.gray_test + os.path.basename(path), roi_gray)
		cv2.imwrite(FilePaths.threshed_test + os.path.basename(path), remove_border(roi_thresh))
		printProgressBar(test_path.tolist().index(path), len(input_path), prefix = 'Progress:', suffix = 'Complete')
	for path in train_path:
		roi_gray, roi_thresh = extract_roi(read_img(path))
		cv2.imwrite(FilePaths.gray_train + os.path.basename(path), roi_gray)
		cv2.imwrite(FilePaths.threshed_train + os.path.basename(path), remove_border(roi_thresh))
		printProgressBar(train_path.tolist().index(path) + len(test_path), len(input_path), prefix = 'Progress:', suffix = 'Complete')






