-
Notifications
You must be signed in to change notification settings - Fork 0
/
makeValidation.py
122 lines (95 loc) · 3.8 KB
/
makeValidation.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
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
import os
from auxilary.utils import readConfig, createDir, readJson
import shutil
from tqdm import tqdm
import argparse
import random
from natsort import natsorted
def arg_init():
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, default='none', help='Path to the config file.')
return parser.parse_args()
def makeVal(config):
log = config["log"]
splitRatio = config["splitRatio"]
trainDir = config["trainDataset"]
valDir = config["valDataset"]
augDir = config["augmented_dir"]
f = open(log+'augmentationLog.txt', 'r')
fStr = f.read()
f.close()
fStr = fStr.strip().split("\n")
numImages = len(fStr) // 2
valLen = round(numImages * (1-splitRatio))
""" print(fStr)
print(numImages)
print(valLen) """
createDir([trainDir, valDir])
print("Making Validation Files")
counter = 1
#cwd = os.getcwd()
for i in range(numImages-valLen, numImages):
shutil.move(f"{augDir}{i}.png", f"{valDir}{counter}.png")
shutil.move(f"{augDir}{i}_label.png", f"{valDir}{counter}_label.png")
#shutil.move(f"{augDir}{i}_label_b.png", f"{valDir}{counter}_label_b.png")
counter += 1
#subprocess.run(f"mv data/augmentated/{fStr[i]} data/val/{fStr[i]}")
#subprocess.run(f"mv data/augmentated/ data/train/")
os.rename(augDir, trainDir)
print("Validation Dataset Creation Completed")
def mergeVal(config):
trainDir = config["trainDataset"]
valDir = config["valDataset"]
count = len(os.listdir(trainDir))//2
for i in tqdm(range(1, len(os.listdir(valDir))//2+1)):
#print(f"{valDir}{i}.png", f"{trainDir}{count+i-1}.png")
shutil.move(f"{valDir}{i}.png", f"{trainDir}{count+i-1}.png")
shutil.move(f"{valDir}{i}_label.png", f"{trainDir}{count+i-1}_label.png")
def makeVal2(config):
splitRatio = config["splitRatio"]
trainDir = config["trainDataset"]
valDir = config["valDataset"]
numImages = len(os.listdir(trainDir))//2
valLen = round(numImages * (1-splitRatio))
print(f"valLen: {valLen}")
# pick random images
random.seed(42)
valImages = random.sample(range(numImages), valLen)
for i in tqdm(valImages):
shutil.move(f"{trainDir}{i}.png", f"{valDir}{i}.png")
shutil.move(f"{trainDir}{i}_label.png", f"{valDir}{i}_label.png")
def organiseDataset(config):
trainDir = config["trainDataset"]
valDir = config["valDataset"]
trainImages = os.listdir(trainDir)
valImages = os.listdir(valDir)
i = 0
for imagePath in tqdm(natsorted(trainImages)):
#print(f"{trainDir}{imagePath}", f"{trainDir}{i}.png")
#print(f"{trainDir}{imagePath.split('.')[0]}_label.png", f"{trainDir}{i}_label.png")
if not imagePath.endswith("_label.png"):
os.rename(f"{trainDir}{imagePath}", f"{trainDir}{i}.png")
os.rename(f"{trainDir}{imagePath.split('.')[0]}_label.png", f"{trainDir}{i}_label.png")
i+=1
print(len(trainImages))
def makeTest3(config):
testOutDir = config["testDataset"]
createDir([testOutDir])
metadataTest = readJson(config["to_be_aug"]+"metadataTest.json")
for imageidx, imagePath in tqdm(enumerate(metadataTest["images"])):
new_imagePath = os.path.join(testOutDir, str(imageidx)+".png")
new_labelPath = os.path.join(testOutDir, str(imageidx)+"_label.png")
shutil.copy(imagePath, new_imagePath)
shutil.copy(metadataTest["labels"][imageidx], new_labelPath)
print("Test Dataset Creation Completed")
if __name__ == '__main__':
args = arg_init()
if args.config == "none":
print("Please provide a config file")
exit(0)
config = readConfig(args.config)
#makeVal(config)
#makeTest(config)
mergeVal(config)
#makeVal2(config)
#organiseDataset(config)