!10924 deeplabv3 bugfix: 1. add CPU training usage in readme file; 2. add dataset list file genrate script.
From: @caojian05 Reviewed-by: @wuxuejian,@oacjiewen Signed-off-by: @wuxuejianpull/10924/MERGE
mindspore-ci-bot
4 years ago
committed by
Gitee
commit
c5532bcdf0
@ -0,0 +1,142 @@
|
||||
import argparse
|
||||
import os
|
||||
|
||||
import numpy as np
|
||||
import scipy.io
|
||||
from PIL import Image
|
||||
|
||||
parser = argparse.ArgumentParser('dataset list generator')
|
||||
parser.add_argument("--data_dir", type=str, default='./', help='where dataset stored.')
|
||||
|
||||
args, _ = parser.parse_known_args()
|
||||
|
||||
data_dir = args.data_dir
|
||||
print("Data dir is:", data_dir)
|
||||
|
||||
#
|
||||
VOC_IMG_DIR = os.path.join(data_dir, 'VOCdevkit/VOC2012/JPEGImages')
|
||||
VOC_ANNO_DIR = os.path.join(data_dir, 'VOCdevkit/VOC2012/SegmentationClass')
|
||||
VOC_ANNO_GRAY_DIR = os.path.join(data_dir, 'VOCdevkit/VOC2012/SegmentationClassGray')
|
||||
VOC_TRAIN_TXT = os.path.join(data_dir, 'VOCdevkit/VOC2012/ImageSets/Segmentation/train.txt')
|
||||
VOC_VAL_TXT = os.path.join(data_dir, 'VOCdevkit/VOC2012/ImageSets/Segmentation/val.txt')
|
||||
|
||||
SBD_ANNO_DIR = os.path.join(data_dir, 'benchmark_RELEASE/dataset/cls')
|
||||
SBD_IMG_DIR = os.path.join(data_dir, 'benchmark_RELEASE/dataset/img')
|
||||
SBD_ANNO_PNG_DIR = os.path.join(data_dir, 'benchmark_RELEASE/dataset/cls_png')
|
||||
SBD_ANNO_GRAY_DIR = os.path.join(data_dir, 'benchmark_RELEASE/dataset/cls_png_gray')
|
||||
SBD_TRAIN_TXT = os.path.join(data_dir, 'benchmark_RELEASE/dataset/train.txt')
|
||||
SBD_VAL_TXT = os.path.join(data_dir, 'benchmark_RELEASE/dataset/val.txt')
|
||||
|
||||
VOC_TRAIN_LST_TXT = os.path.join(data_dir, 'voc_train_lst.txt')
|
||||
VOC_VAL_LST_TXT = os.path.join(data_dir, 'voc_val_lst.txt')
|
||||
VOC_AUG_TRAIN_LST_TXT = os.path.join(data_dir, 'vocaug_train_lst.txt')
|
||||
|
||||
|
||||
def __get_data_list(data_list_file):
|
||||
with open(data_list_file, mode='r') as f:
|
||||
return f.readlines()
|
||||
|
||||
|
||||
def conv_voc_colorpng_to_graypng():
|
||||
if not os.path.exists(VOC_ANNO_GRAY_DIR):
|
||||
os.makedirs(VOC_ANNO_GRAY_DIR)
|
||||
|
||||
for ann in os.listdir(VOC_ANNO_DIR):
|
||||
ann_im = Image.open(os.path.join(VOC_ANNO_DIR, ann))
|
||||
ann_im = Image.fromarray(np.array(ann_im))
|
||||
ann_im.save(os.path.join(VOC_ANNO_GRAY_DIR, ann))
|
||||
|
||||
|
||||
def __gen_palette(cls_nums=256):
|
||||
palette = np.zeros((cls_nums, 3), dtype=np.uint8)
|
||||
for i in range(cls_nums):
|
||||
lbl = i
|
||||
j = 0
|
||||
while lbl:
|
||||
palette[i, 0] |= (((lbl >> 0) & 1) << (7 - j))
|
||||
palette[i, 1] |= (((lbl >> 1) & 1) << (7 - j))
|
||||
palette[i, 2] |= (((lbl >> 2) & 1) << (7 - j))
|
||||
lbl >>= 3
|
||||
j += 1
|
||||
return palette.flatten()
|
||||
|
||||
|
||||
def conv_sbd_mat_to_png():
|
||||
if not os.path.exists(SBD_ANNO_PNG_DIR):
|
||||
os.makedirs(SBD_ANNO_PNG_DIR)
|
||||
if not os.path.exists(SBD_ANNO_GRAY_DIR):
|
||||
os.makedirs(SBD_ANNO_GRAY_DIR)
|
||||
|
||||
palette = __gen_palette()
|
||||
for an in os.listdir(SBD_ANNO_DIR):
|
||||
img_id = an[:-4]
|
||||
mat = scipy.io.loadmat(os.path.join(SBD_ANNO_DIR, an))
|
||||
anno = mat['GTcls'][0]['Segmentation'][0].astype(np.uint8)
|
||||
anno_png = Image.fromarray(anno)
|
||||
# save to gray png
|
||||
anno_png.save(os.path.join(SBD_ANNO_GRAY_DIR, img_id + '.png'))
|
||||
# save to color png use palette
|
||||
anno_png.putpalette(palette)
|
||||
anno_png.save(os.path.join(SBD_ANNO_PNG_DIR, img_id + '.png'))
|
||||
|
||||
|
||||
def create_voc_train_lst_txt():
|
||||
voc_train_data_lst = __get_data_list(VOC_TRAIN_TXT)
|
||||
with open(VOC_TRAIN_LST_TXT, mode='w') as f:
|
||||
for id_ in voc_train_data_lst:
|
||||
id_ = id_.strip()
|
||||
img_ = os.path.join(VOC_IMG_DIR, id_ + '.jpg')
|
||||
anno_ = os.path.join(VOC_ANNO_GRAY_DIR, id_ + '.png')
|
||||
f.write(img_ + ' ' + anno_ + '\n')
|
||||
|
||||
|
||||
def create_voc_val_lst_txt():
|
||||
voc_val_data_lst = __get_data_list(VOC_VAL_TXT)
|
||||
with open(VOC_VAL_LST_TXT, mode='w') as f:
|
||||
for id_ in voc_val_data_lst:
|
||||
id_ = id_.strip()
|
||||
img_ = os.path.join(VOC_IMG_DIR, id_ + '.jpg')
|
||||
anno_ = os.path.join(VOC_ANNO_GRAY_DIR, id_ + '.png')
|
||||
f.write(img_ + ' ' + anno_ + '\n')
|
||||
|
||||
|
||||
def create_voc_train_aug_lst_txt():
|
||||
voc_train_data_lst = __get_data_list(VOC_TRAIN_TXT)
|
||||
voc_val_data_lst = __get_data_list(VOC_VAL_TXT)
|
||||
|
||||
sbd_train_data_lst = __get_data_list(SBD_TRAIN_TXT)
|
||||
sbd_val_data_lst = __get_data_list(SBD_VAL_TXT)
|
||||
|
||||
with open(VOC_AUG_TRAIN_LST_TXT, mode='w') as f:
|
||||
for id_ in sbd_train_data_lst + sbd_val_data_lst:
|
||||
if id_ in voc_train_data_lst + voc_val_data_lst:
|
||||
continue
|
||||
id_ = id_.strip()
|
||||
img_ = os.path.join(SBD_ANNO_DIR, id_ + '.jpg')
|
||||
anno_ = os.path.join(SBD_ANNO_GRAY_DIR, id_ + '.png')
|
||||
f.write(img_ + ' ' + anno_ + '\n')
|
||||
|
||||
for id_ in voc_train_data_lst:
|
||||
id_ = id_.strip()
|
||||
img_ = os.path.join(VOC_IMG_DIR, id_ + '.jpg')
|
||||
anno_ = os.path.join(VOC_ANNO_GRAY_DIR, id_ + '.png')
|
||||
f.write(img_ + ' ' + anno_ + '\n')
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
print('converting voc color png to gray png ...')
|
||||
conv_voc_colorpng_to_graypng()
|
||||
print('converting done.')
|
||||
|
||||
create_voc_train_lst_txt()
|
||||
print('generating voc train list success.')
|
||||
|
||||
create_voc_val_lst_txt()
|
||||
print('generating voc val list success.')
|
||||
|
||||
print('converting sbd annotations to png ...')
|
||||
conv_sbd_mat_to_png()
|
||||
print('converting done')
|
||||
|
||||
create_voc_train_aug_lst_txt()
|
||||
print('generating voc train aug list success.')
|
||||
Loading…
Reference in new issue