-
Notifications
You must be signed in to change notification settings - Fork 0
/
dataset_generator.py
58 lines (52 loc) · 1.92 KB
/
dataset_generator.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
import barcode
import random as rd
import numpy as np
import os
import glob
import cv2
from barcode.writer import ImageWriter
from tensorflow.python.keras.utils import to_categorical
from parameters import *
from transform_utils import TransformUtils
#First, delete everything in ./dataset
cwd = os.getcwd()
path = os.path.join(cwd, generation_folder)
os.chdir(path)
for image_path in glob.glob("*.png"):
file_path = os.path.join(path, image_path)
os.unlink(file_path)
if os.path.exists(os.path.join(path, 'labels.txt')) :
os.unlink(os.path.join(path, 'labels.txt'))
os.chdir("../")
coder = barcode.get_barcode_class(barcode_type)
T = TransformUtils(w=WIDTH, h=HEIGHT)
labels = np.array([np.zeros((nb_img, 10), dtype=np.bool_)] *10)
for k in range(nb_img):
nb = rd.randint(0, max_barcode_number)
nb_digits = len(str(max_barcode_number))
nb = str(nb).zfill(nb_digits)
barcode = coder(nb, ImageWriter(), add_checksum=False)
barcode.save("./" +generation_folder+'/temp', options=barcode_options)
temp = cv2.imread("./" +generation_folder+'/temp.png', cv2.IMREAD_GRAYSCALE)
##########################################################
################### DATA AUGMENTATION ####################
##########################################################
if rd.random()<0.5 :
temp = T.updown(temp)
temp = T.occlusion(temp)
temp = T.translation(temp)
temp = T.rotation(temp)
if rd.random()<0.66:
if rd.random()<0.5:
temp = T.darken(temp)
else:
temp = T.brighten(temp)
##########################################################
cv2.imwrite(os.path.join(path, "cb-" + str(k) + ".png"), temp)
nb_arr = np.array(list(nb))
vect = []
for d in range(nb_arr.shape[0]):
cat = to_categorical(nb_arr[d], 10)
labels[d][k] = cat
np.save("./" + generation_folder + "/labels", labels)
os.unlink("./" + generation_folder + "/temp.png")