def __init__(self,
path,
cls_map='arcsoft/cat_id_map.txt',
path_replace=None,
img_suffix='.jpg'):
self.path = path
self.path_replace = path_replace
self.img_suffix = img_suffix
self.txt_list = cvtools.get_files_list(self.path,
file_type='.txt',
basename=True)
# you could comment this sentence if you don't want check integrity of images and labels.
# self.img_list = cvtools.get_files_list(self.path, file_type=img_suffix)
# assert len(self.img_list) == len(self.txt_list)
self.cls_map = cvtools.read_key_value(cls_map)
self.coco_dataset = {
"info": {
"description":
"This is unstable 0.0.0 version of the 2019 Projects Data.",
"url": "http://www.arcsoft.com",
"version": "1.0",
"year": 2019,
"contributor": "arcsoft",
"date_created": cvtools.get_now_time_str()
},
"categories": [], # Not added yet
"images": [],
"annotations": []
}
self.imageID = 1
self.annID = 1
self.run_timer = cvtools.Timer()
def __init__(self,
label_root,
image_root,
classes=get_classes('dota'),
path_replace=None,
box_form='x1y1wh'):
self.label_root = label_root
self.image_root = image_root
self.path_replace = path_replace
self.box_form = box_form
self.files = []
self.files += cvtools.get_files_list(label_root, basename=True)
if cvtools._DEBUG:
self.files = self.files[:10]
self.lines = []
if isinstance(classes, str):
self.cls_map = cvtools.read_key_value(classes)
else:
self.cls_map = {name: i + 1 for i, name in enumerate(classes)}
self.coco_dataset = {
"info": {
"description": "This is stable 1.0 version of the DOTA.",
"url": "http://captain.whu.edu.cn/DOTAweb/index.html",
"version": "1.0",
"year": 2018,
"contributor": "DOTA",
"date_created": cvtools.get_time_str()
},
"categories": [],
"images": [],
"annotations": []
}
self.imageID = 1
self.annID = 1
self.run_timer = cvtools.Timer()
def __init__(
self,
label_root,
image_root,
cls_map='/home/liuchang/cvtools/cvtools/label_convert/dota/dota_v1.5_cat_id_map.txt',
path_replace=None,
box_form='x1y1wh'):
self.label_root = label_root
self.image_root = image_root
self.path_replace = path_replace
self.box_form = box_form
self.files = []
self.files += cvtools.get_files_list(label_root, basename=True)
# if cvtools._DEBUG:
# self.files = self.files[:10]
self.lines = []
self.cls_map = cvtools.read_key_value(cls_map)
self.coco_dataset = {
"info": {
"description": "This is stable 1.0 version of the DOTA.",
"url": "http://captain.whu.edu.cn/DOTAweb/index.html",
"version": "1.0",
"year": 2018,
"contributor": "DOTA",
"date_created": cvtools.get_now_time_str()
},
"categories": [],
"images": [],
"annotations": []
}
self.imageID = 1
self.annID = 1
self.run_timer = cvtools.Timer()
def __init__(self,
ann_file,
img_prefix,
img_scale,
img_norm_cfg,
multiscale_mode='value',
size_divisor=None,
proposal_file=None,
num_max_proposals=1000,
flip_ratio=0,
with_mask=True,
with_crowd=True,
with_label=True,
with_semantic_seg=False,
seg_prefix=None,
seg_scale_factor=1,
extra_aug=None,
rotate_aug=None,
rotate_test_aug=None,
resize_keep_ratio=True,
test_mode=False,
level='L1',
L2_class_map_file=None,
L3_class_map_file=None):
super(HRSCDataset, self).__init__(
ann_file=ann_file,
img_prefix=img_prefix,
img_scale=img_scale,
img_norm_cfg=img_norm_cfg,
multiscale_mode=multiscale_mode,
size_divisor=size_divisor,
proposal_file=proposal_file,
num_max_proposals=num_max_proposals,
flip_ratio=flip_ratio,
with_mask=with_mask,
with_crowd=with_crowd,
with_label=with_label,
with_semantic_seg=with_semantic_seg,
seg_prefix=seg_prefix,
seg_scale_factor=seg_scale_factor,
extra_aug=extra_aug,
rotate_aug=rotate_aug,
rotate_test_aug=rotate_test_aug,
resize_keep_ratio=resize_keep_ratio,
test_mode=test_mode)
self.level = level
self.L2_class_map = None
self.L3_class_map = None
self.L2_cat2label = None
self.L3_cat2label = None
if level == 'L1':
for cat in self.cat2label.keys():
self.cat2label[cat] = 1
elif level == 'L2':
self.L2_class_map = cvtools.read_key_value(L2_class_map_file)
self.L2_cat2label = {
cat_id: i + 1
for i, cat_id in enumerate(set(self.L2_class_map.values()))
}
ori_to_L2 = dict()
for cat, cat_id in self.L2_class_map.items():
ori_to_L2[cat] = self.L2_cat2label[cat_id]
self.cat2label = ori_to_L2
elif level == 'L3':
self.L3_class_map = cvtools.read_key_value(L3_class_map_file)
self.L3_cat2label = {
cat_id: i + 1
for i, cat_id in enumerate(set(self.L3_class_map.values()))
}
ori_to_L3 = dict()
for cat, cat_id in self.L3_class_map.items():
ori_to_L3[cat] = self.L3_cat2label[cat_id]
self.cat2label = ori_to_L3