showPatches

#!/usr/bin/env python
# remove the necessity to have .py extension

from __future__ import print_function, unicode_literals, absolute_import, division

import sys, os
import numpy as np
import matplotlib.pyplot as plt
from csbdeep.utils import Path, download_and_extract_zip_file, plot_some, normalize, normalize_mi_ma
from csbdeep.io import load_training_data, save_tiff_imagej_compatible


option_handle_list = ['--imageNumber']
option_unique_list = ['--info', '--help']
options = {}


for option_handle in option_handle_list:
    if option_handle in sys.argv:
        options[option_handle[2:]] = sys.argv[sys.argv.index(option_handle) + 1]
    else:
        options[option_handle[2:]] = None

for option_handle in option_unique_list:
    if option_handle in sys.argv:
        options[option_handle[2:]] = True
    else:
        options[option_handle[2:]] = None

if options['info'] != None or options['help'] != None:
    print("Function showPatches, this function show plot of pair patches.")
    print("Takes the image from 5 to n + 5")
    print("USAGE : showPatches [imagePath]")
    print("EX: showPatches patch.npz")
    print("")
    print("options")
    exit()


if len(sys.argv) == 1 or not os.path.exists(sys.argv[1]):
    raise ValueError("Incorrect path, the first argument must be the image path")
imagePath = sys.argv[1]


#(X_train, Y_train), (X_val,Y_val), axes = load_training_data('data_label.npz', validation_split=0.1, verbose=True)
data = np.load(imagePath)
#training images (180)

x = data['Y'][0]

print('Number of images:', len(data['X']))
print('image size      :', x.shape)

# To download :
# import matplotlib.pyplot as plt
# for i in range(5, 10):
#     img = normalize(data['X'][i], 0, 100, clip=True)
#     plt.imshow(np.squeeze(img))
#     plt.savefig("X/img" + str(i) + ".png")
#
#     img = normalize(data['Y'][i], 0, 100, clip=True)
#     plt.imshow(np.squeeze(img))
#     plt.savefig("Y/img" + str(i) + ".png")
# plt.show()


# To show patch pairs X / Y
fig=plt.figure(figsize=(8, 4))
plt.axis('off')
h = 2
w = 5
import random
for i in range(1, w + 1):
    nb = random.randrange(0, len(data['X']))

    plt.subplot(h, w, i)
    img = np.squeeze(normalize(data['X'][nb], 0, 100, clip=True))
    plt.axis('off')
    plt.imshow(img)

    plt.subplot(h, w, w + i)
    img = np.squeeze(normalize(data['Y'][nb], 0, 100, clip=True))
    plt.axis('off')
    plt.imshow(img)
    plt.suptitle('5 example patches (top row: source, bottom row: target)', fontsize='small');
plt.show()