Python datasets.imdb.imdb.__init__() Examples
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code examples of datasets.imdb.imdb.__init__().
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Example #1
| Source File: dvmm.py From RGB-N with MIT License | 6 votes |
|
def __init__(self, image_set, year, dist_path=None):
imdb.__init__(self, image_set)
self._year = year
self._image_set = image_set.split('dist_')[1]
self._dist_path = self._get_default_path() if dist_path is None \
else dist_path
self._data_path=self._dist_path
self._classes = ('__background__', # always index 0
'tamper','authentic')
self._classes = ('authentic', # always index 0
'tamper')
#self.classes =('authentic', # always index 0
#'splicing','removal')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = {'.png','.jpg','.tif','.bmp','.JPG'}
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #2
| Source File: face.py From face-py-faster-rcnn with MIT License | 6 votes |
|
def __init__(self, image_set, split, devkit_path):
imdb.__init__(self, 'wider')
self._image_set = image_set # {'train', 'test'}
self._split = split # {1, 2, ..., 10}
self._devkit_path = devkit_path # /data2/hzjiang/Data/CS2
# self._data_path = os.path.join(self._devkit_path, 'data')
self._data_path = self._devkit_path;
self._classes = ('__background__', # always index 0
'face')
self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))
self._image_ext = ['.png']
self._image_index, self._gt_roidb = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.selective_search_roidb
# Specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'top_k' : 2000}
assert os.path.exists(self._devkit_path), \
'Devkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #3
| Source File: nist.py From RGB-N with MIT License | 6 votes |
|
def __init__(self, image_set, year, dist_path=None):
imdb.__init__(self, image_set)
self._year = year
self._image_set = image_set.split('dist_')[1]
self._dist_path = self._get_default_path() if dist_path is None \
else dist_path
self._data_path=self._dist_path
self._classes = ('__background__', # always index 0
'tamper','authentic')
self._classes = ('__background__', # always index 0
'splicing','removal','manipulation')
self._classes = ('authentic', # always index 0
'tamper')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = {'.png','.jpg','.tif','.bmp','.JPG'}
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #4
| Source File: swapme.py From RGB-N with MIT License | 6 votes |
|
def __init__(self, image_set, year, dist_path=None):
imdb.__init__(self, image_set)
self._year = year
self._image_set = image_set.split('face_')[1]
self._dist_path = self._get_default_path() if dist_path is None \
else dist_path
self._data_path=self._dist_path
self._classes = ('__background__', # always index 0
'tamper','authentic')
#self._classes = ('authentic', # always index 0
#'tamper')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = {'.png','.jpg','.tif','.bmp','.JPG'}
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #5
| Source File: kaist.py From MSDS-RCNN with MIT License | 6 votes |
|
def __init__(self, image_set, modality, data_filter, imp_type, devkit_path=None):
imdb.__init__(self, 'kaist_' + image_set + '_' + modality + '_' + data_filter + imp_type)
self._image_set = image_set
self._modality = modality
if modality == 'multi':
print('set cfg.MULTI_INPUT -> True')
cfg.MULTI_INPUT = True
self._data_filter = data_filter
self._imp_type = imp_type
self._data_path = self._get_default_path()
self._classes = ('__background__', # always index 0
'person')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.png'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
assert os.path.exists(self._data_path), \
'Kaist path does not exist: {}'.format(self._data_path)
Example #6
| Source File: coco.py From RGB-N with MIT License | 6 votes |
|
def __init__(self, image_set, year, dist_path=None):
imdb.__init__(self, image_set)
self._year = year
self._image_set = image_set.split('coco_')[1]
self._dist_path = self._get_default_path() if dist_path is None \
else dist_path
self._data_path=self._dist_path
#self._data_path = os.path.join(self._dist_path, image_set)
self._classes = ('__background__', # always index 0
'tamper','authentic')
self._classes = ('authentic', # always index 0
'tamper')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
#self._image_ext = {'.jpg','.tif'}
self._image_ext = {'.png','.jpg','.tif','.bmp','.JPG'}
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #7
| Source File: dist_fake.py From RGB-N with MIT License | 6 votes |
|
def __init__(self, image_set, year, dist_path=None):
imdb.__init__(self, image_set)
self._year = year
self._image_set = image_set.split('dist_')[1]
self._dist_path = self._get_default_path() if dist_path is None \
else dist_path
self._data_path=self._dist_path
self._classes = ('__background__', # always index 0
'tamper','authentic')
self._classes = ('authentic', # always index 0
'tamper')
#self.classes =('authentic', # always index 0
#'splicing','removal')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = {'.png','.jpg','.tif','.bmp','.JPG'}
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #8
| Source File: coco.py From pytorch-faster-rcnn with MIT License | 5 votes |
|
def __init__(self, image_set, year):
imdb.__init__(self, 'coco_' + year + '_' + image_set)
# COCO specific config options
self.config = {'use_salt': True,
'cleanup': True}
# name, paths
self._year = year
self._image_set = image_set
self._data_path = osp.join(cfg.DATA_DIR, 'coco')
# load COCO API, classes, class <-> id mappings
self._COCO = COCO(self._get_ann_file())
cats = self._COCO.loadCats(self._COCO.getCatIds())
self._classes = tuple(['__background__'] + [c['name'] for c in cats])
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._class_to_coco_cat_id = dict(list(zip([c['name'] for c in cats],
self._COCO.getCatIds())))
self._image_index = self._load_image_set_index()
# Default to roidb handler
self.set_proposal_method('gt')
self.competition_mode(False)
# Some image sets are "views" (i.e. subsets) into others.
# For example, minival2014 is a random 5000 image subset of val2014.
# This mapping tells us where the view's images and proposals come from.
self._view_map = {
'minival2014': 'val2014', # 5k val2014 subset
'valminusminival2014': 'val2014', # val2014 \setminus minival2014
'test-dev2015': 'test2015',
}
coco_name = image_set + year # e.g., "val2014"
self._data_name = (self._view_map[coco_name]
if coco_name in self._view_map
else coco_name)
# Dataset splits that have ground-truth annotations (test splits
# do not have gt annotations)
self._gt_splits = ('train', 'val', 'minival')
Example #9
| Source File: coco.py From iter-reason with MIT License | 5 votes |
|
def __init__(self, image_set, year):
imdb.__init__(self, 'coco_' + year + '_' + image_set)
# COCO specific config options
self.config = {'use_crowd': False,
'use_salt': True,
'cleanup': True}
# name, paths
self._year = year
self._image_set = image_set
self._data_path = osp.join(cfg.DATA_DIR, 'coco')
# load COCO API, classes, class <-> id mappings
self._COCO = COCO(self._get_ann_file())
cats = self._COCO.loadCats(self._COCO.getCatIds())
self._classes = tuple(['__background__'] + [c['name'] for c in cats])
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._class_to_coco_cat_id = dict(list(zip([c['name'] for c in cats],
self._COCO.getCatIds())))
self._image_index = self._load_image_set_index()
# Default to roidb handler
self.set_proposal_method('gt')
# Some image sets are "views" (i.e. subsets) into others.
# For example, minival2014 is a random 5000 image subset of val2014.
# This mapping tells us where the view's images and proposals come from.
self._view_map = {
'minival2014': 'val2014', # 5k val2014 subset
'valminusminival2014': 'val2014', # val2014 \setminus minival2014
'test-dev2015': 'test2015',
}
coco_name = image_set + year # e.g., "val2014"
self._data_name = (self._view_map[coco_name]
if coco_name in self._view_map
else coco_name)
# Dataset splits that have ground-truth annotations (test splits
# do not have gt annotations)
self._gt_splits = ('train', 'val', 'minival')
Example #10
| Source File: pascal_voc.py From py-R-FCN with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.selective_search_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'use_diff' : False,
'matlab_eval' : False,
'rpn_file' : None,
'min_size' : 2}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #11
| Source File: mydataset.py From pytorch-faster-rcnn with MIT License | 5 votes |
|
def __init__(self, image_set, dataset):
name = dataset + '_' + image_set
imdb.__init__(self, name)
self._image_set = image_set
self._root_path = '/media/rgh/rgh-data/Dataset/'+dataset#.capitalize()
self._data_path = os.path.join(self._root_path, 'image', image_set)
self._parsing_label_path = os.path.join(self._root_path, 'label', image_set)
# self._classes = ('__background__', # always index 0
# 'face', 'hair', 'U-clothes', 'L-arm','R-arm',
# 'pants', 'L-leg', 'R-leg', 'dress','L-shoe',
# 'R-shoe')
self._classes = ('__background__', 'Hat', 'Hair', 'Glove', 'Sunglasses', 'Upper-clothes', 'Dress', 'Coat', 'Socks',
'Pants', 'Jumpsuits', 'Scarf', 'Skirt', 'Face', 'Left-arm', 'Right-arm', 'Left-leg', 'Right-leg',
'Left-shoe', 'Right-shoe')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._parsing_label_ext = '.png'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self.config = {'cleanup': False,
'use_diff': True,
'matlab_eval': False,
'rpn_file': None,
'min_size': 2}
assert os.path.exists(self._root_path), \
'dataset path does not exist: {}'.format(self._root_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #12
| Source File: pascal_voc_rbg.py From dafrcnn-pytorch with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': False,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #13
| Source File: pascal_voc_rbg.py From dafrcnn-pytorch with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': False,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #14
| Source File: pascal_voc.py From centerNet-deep-sort with GNU General Public License v3.0 | 5 votes |
|
def __init__(self, image_set, year, use_diff=False):
name = 'voc_' + year + '_' + image_set
if use_diff:
name += '_diff'
imdb.__init__(self, name)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path()
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': use_diff,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #15
| Source File: pascal_voc_rbg.py From DetNet_pytorch with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': False,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #16
| Source File: coco.py From DetNet_pytorch with MIT License | 5 votes |
|
def __init__(self, image_set, year):
imdb.__init__(self, 'coco_' + year + '_' + image_set)
# COCO specific config options
self.config = {'use_salt': True,
'cleanup': True}
# name, paths
self._year = year
self._image_set = image_set
self._data_path = osp.join(cfg.DATA_DIR, 'coco')
# load COCO API, classes, class <-> id mappings
self._COCO = COCO(self._get_ann_file())
cats = self._COCO.loadCats(self._COCO.getCatIds())
self._classes = tuple(['__background__'] + [c['name'] for c in cats])
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._class_to_coco_cat_id = dict(list(zip([c['name'] for c in cats],
self._COCO.getCatIds())))
self._image_index = self._load_image_set_index()
# Default to roidb handler
self.set_proposal_method('gt')
self.competition_mode(False)
# Some image sets are "views" (i.e. subsets) into others.
# For example, minival2014 is a random 5000 image subset of val2014.
# This mapping tells us where the view's images and proposals come from.
self._view_map = {
'minival2014': 'val2014', # 5k val2014 subset
'valminusminival2014': 'val2014', # val2014 \setminus minival2014
'test-dev2015': 'test2015',
'valminuscapval2014': 'val2014',
'capval2014': 'val2014',
'captest2014': 'val2014'
}
coco_name = image_set + year # e.g., "val2014"
self._data_name = (self._view_map[coco_name]
if coco_name in self._view_map
else coco_name)
# Dataset splits that have ground-truth annotations (test splits
# do not have gt annotations)
self._gt_splits = ('train', 'val', 'minival')
Example #17
| Source File: coco.py From CIOD with MIT License | 5 votes |
|
def __init__(self, image_set, year):
imdb.__init__(self, 'coco_' + year + '_' + image_set)
# COCO specific config options
self.config = {'use_salt': True,
'cleanup': True}
# name, paths
self._year = year
self._image_set = image_set
self._data_path = osp.join(cfg.DATA_DIR, 'coco')
# load COCO API, classes, class <-> id mappings
self._COCO = COCO(self._get_ann_file())
cats = self._COCO.loadCats(self._COCO.getCatIds())
self._classes = tuple(['__background__'] + [c['name'] for c in cats])
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._class_to_coco_cat_id = dict(list(zip([c['name'] for c in cats],
self._COCO.getCatIds())))
self._image_index = self._load_image_set_index()
# Default to roidb handler
self.set_proposal_method('gt')
self.competition_mode(False)
# Some image sets are "views" (i.e. subsets) into others.
# For example, minival2014 is a random 5000 image subset of val2014.
# This mapping tells us where the view's images and proposals come from.
self._view_map = {
'minival2014': 'val2014', # 5k val2014 subset
'valminusminival2014': 'val2014', # val2014 \setminus minival2014
'test-dev2015': 'test2015',
'valminuscapval2014': 'val2014',
'capval2014': 'val2014',
'captest2014': 'val2014'
}
coco_name = image_set + year # e.g., "val2014"
self._data_name = (self._view_map[coco_name]
if coco_name in self._view_map
else coco_name)
# Dataset splits that have ground-truth annotations (test splits
# do not have gt annotations)
self._gt_splits = ('train', 'val', 'minival')
Example #18
| Source File: ade.py From iter-reason with MIT License | 5 votes |
|
def __init__(self, image_set, count=5):
imdb.__init__(self, 'ade_%s_%d' % (image_set,count))
self._image_set = image_set
self._root_path = osp.join(cfg.DATA_DIR, 'ADE')
self._name_file = osp.join(self._root_path, 'objectnames.txt')
self._count_file = osp.join(self._root_path, 'objectcounts.txt')
self._anno_file = osp.join(self._root_path, self._image_set + '.txt')
with open(self._anno_file) as fid:
image_index = fid.readlines()
self._image_index = [ii.strip() for ii in image_index]
with open(self._name_file) as fid:
raw_names = fid.readlines()
self._raw_names = [n.strip().replace(' ', '_') for n in raw_names]
self._len_raw = len(self._raw_names)
with open(self._count_file) as fid:
raw_counts = fid.readlines()
self._raw_counts = np.array([int(n.strip()) for n in raw_counts])
# First class is always background
self._ade_inds = [0] + list(np.where(self._raw_counts >= count)[0])
self._classes = ['__background__']
for idx in self._ade_inds:
if idx == 0:
continue
ade_name = self._raw_names[idx]
self._classes.append(ade_name)
self._classes = tuple(self._classes)
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self.set_proposal_method('gt')
Example #19
| Source File: visual_genome.py From iter-reason with MIT License | 5 votes |
|
def __init__(self, image_set, count=5):
imdb.__init__(self, 'visual_genome_%s_%d' % (image_set, count))
self._image_set = image_set
self._root_path = osp.join(cfg.DATA_DIR, 'visual_genome')
self._name_file = osp.join(self._root_path, 'synsets.txt')
self._anno_file = osp.join(self._root_path, self._image_set + '.json')
self._image_file = osp.join(self._root_path, 'image_data.json')
with open(self._name_file) as fid:
lines = fid.readlines()
self._raw_names = []
self._raw_counts = []
for line in lines:
name, cc = line.strip().split(':')
cc = int(cc)
self._raw_names.append(name)
self._raw_counts.append(cc)
self._len_raw = len(self._raw_names)
self._raw_counts = np.array(self._raw_counts)
# First class is always background
self._vg_inds = [0] + list(np.where(self._raw_counts >= count)[0])
self._classes = ['__background__']
for idx in self._vg_inds:
if idx == 0:
continue
vg_name = self._raw_names[idx]
self._classes.append(vg_name)
self._classes = tuple(self._classes)
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self.set_proposal_method('gt')
# Call to get one
self.roidb
Example #20
| Source File: pascal_voc_rbg.py From One-Shot-Object-Detection with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': False,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #21
| Source File: coco.py From uai-sdk with Apache License 2.0 | 5 votes |
|
def __init__(self, image_set, year):
imdb.__init__(self, 'coco_' + year + '_' + image_set)
# COCO specific config options
self.config = {'top_k' : 2000,
'use_salt' : True,
'cleanup' : True,
'crowd_thresh' : 0.7,
'min_size' : 2}
# name, paths
self._year = year
self._image_set = image_set
self._data_path = osp.join(cfg.DATA_DIR, 'coco')
# load COCO API, classes, class <-> id mappings
self._COCO = COCO(self._get_ann_file())
cats = self._COCO.loadCats(self._COCO.getCatIds())
self._classes = tuple(['__background__'] + [c['name'] for c in cats])
self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))
self._class_to_coco_cat_id = dict(zip([c['name'] for c in cats],
self._COCO.getCatIds()))
self._image_index = self._load_image_set_index()
# Default to roidb handler
self.set_proposal_method('selective_search')
self.competition_mode(False)
# Some image sets are "views" (i.e. subsets) into others.
# For example, minival2014 is a random 5000 image subset of val2014.
# This mapping tells us where the view's images and proposals come from.
self._view_map = {
'minival2014' : 'val2014', # 5k val2014 subset
'valminusminival2014' : 'val2014', # val2014 \setminus minival2014
}
coco_name = image_set + year # e.g., "val2014"
self._data_name = (self._view_map[coco_name]
if self._view_map.has_key(coco_name)
else coco_name)
# Dataset splits that have ground-truth annotations (test splits
# do not have gt annotations)
self._gt_splits = ('train', 'val', 'minival')
Example #22
| Source File: pascal_voc.py From uai-sdk with Apache License 2.0 | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.selective_search_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'use_diff' : False,
'matlab_eval' : False,
'rpn_file' : None,
'min_size' : 2}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #23
| Source File: coco.py From faster-rcnn.pytorch with MIT License | 5 votes |
|
def __init__(self, image_set, year):
imdb.__init__(self, 'coco_' + year + '_' + image_set)
# COCO specific config options
self.config = {'use_salt': True,
'cleanup': True}
# name, paths
self._year = year
self._image_set = image_set
self._data_path = osp.join(cfg.DATA_DIR, 'coco')
# load COCO API, classes, class <-> id mappings
self._COCO = COCO(self._get_ann_file())
cats = self._COCO.loadCats(self._COCO.getCatIds())
self._classes = tuple(['__background__'] + [c['name'] for c in cats])
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._class_to_coco_cat_id = dict(list(zip([c['name'] for c in cats],
self._COCO.getCatIds())))
self._image_index = self._load_image_set_index()
# Default to roidb handler
self.set_proposal_method('gt')
self.competition_mode(False)
# Some image sets are "views" (i.e. subsets) into others.
# For example, minival2014 is a random 5000 image subset of val2014.
# This mapping tells us where the view's images and proposals come from.
self._view_map = {
'minival2014': 'val2014', # 5k val2014 subset
'valminusminival2014': 'val2014', # val2014 \setminus minival2014
'test-dev2015': 'test2015',
'valminuscapval2014': 'val2014',
'capval2014': 'val2014',
'captest2014': 'val2014'
}
coco_name = image_set + year # e.g., "val2014"
self._data_name = (self._view_map[coco_name]
if coco_name in self._view_map
else coco_name)
# Dataset splits that have ground-truth annotations (test splits
# do not have gt annotations)
self._gt_splits = ('train', 'val', 'minival')
Example #24
| Source File: pascal_voc_rbg.py From faster-rcnn.pytorch with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': False,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #25
| Source File: coco.py From pytorch-lighthead with MIT License | 5 votes |
|
def __init__(self, image_set, year):
imdb.__init__(self, 'coco_' + year + '_' + image_set)
# COCO specific config options
self.config = {'use_salt': True,
'cleanup': True}
# name, paths
self._year = year
self._image_set = image_set
self._data_path = osp.join(cfg.DATA_DIR, 'coco')
# load COCO API, classes, class <-> id mappings
self._COCO = COCO(self._get_ann_file())
cats = self._COCO.loadCats(self._COCO.getCatIds())
self._classes = tuple(['__background__'] + [c['name'] for c in cats])
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._class_to_coco_cat_id = dict(list(zip([c['name'] for c in cats],
self._COCO.getCatIds())))
self._image_index = self._load_image_set_index()
# Default to roidb handler
self.set_proposal_method('gt')
self.competition_mode(False)
# Some image sets are "views" (i.e. subsets) into others.
# For example, minival2014 is a random 5000 image subset of val2014.
# This mapping tells us where the view's images and proposals come from.
self._view_map = {
'minival2014': 'val2014', # 5k val2014 subset
'valminusminival2014': 'val2014', # val2014 \setminus minival2014
'test-dev2015': 'test2015',
'valminuscapval2014': 'val2014',
'capval2014': 'val2014',
'captest2014': 'val2014'
}
coco_name = image_set + year # e.g., "val2014"
self._data_name = (self._view_map[coco_name]
if coco_name in self._view_map
else coco_name)
# Dataset splits that have ground-truth annotations (test splits
# do not have gt annotations)
self._gt_splits = ('train', 'val', 'minival')
Example #26
| Source File: pascal_voc_rbg.py From pytorch-lighthead with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': False,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #27
| Source File: coco.py From Faster-RCNN_TF with MIT License | 5 votes |
|
def __init__(self, image_set, year):
imdb.__init__(self, 'coco_' + year + '_' + image_set)
# COCO specific config options
self.config = {'top_k' : 2000,
'use_salt' : True,
'cleanup' : True,
'crowd_thresh' : 0.7,
'min_size' : 2}
# name, paths
self._year = year
self._image_set = image_set
self._data_path = osp.join(cfg.DATA_DIR, 'coco')
# load COCO API, classes, class <-> id mappings
self._COCO = COCO(self._get_ann_file())
cats = self._COCO.loadCats(self._COCO.getCatIds())
self._classes = tuple(['__background__'] + [c['name'] for c in cats])
self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))
self._class_to_coco_cat_id = dict(zip([c['name'] for c in cats],
self._COCO.getCatIds()))
self._image_index = self._load_image_set_index()
# Default to roidb handler
self.set_proposal_method('selective_search')
self.competition_mode(False)
# Some image sets are "views" (i.e. subsets) into others.
# For example, minival2014 is a random 5000 image subset of val2014.
# This mapping tells us where the view's images and proposals come from.
self._view_map = {
'minival2014' : 'val2014', # 5k val2014 subset
'valminusminival2014' : 'val2014', # val2014 \setminus minival2014
}
coco_name = image_set + year # e.g., "val2014"
self._data_name = (self._view_map[coco_name]
if self._view_map.has_key(coco_name)
else coco_name)
# Dataset splits that have ground-truth annotations (test splits
# do not have gt annotations)
self._gt_splits = ('train', 'val', 'minival')
Example #28
| Source File: pascal_voc.py From Faster-RCNN_TF with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
#self._roidb_handler = self.selective_search_roidb
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'use_diff' : False,
'matlab_eval' : False,
'rpn_file' : None,
'min_size' : 2}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #29
| Source File: pascal_voc.py From Collaborative-Learning-for-Weakly-Supervised-Object-Detection with MIT License | 5 votes |
|
def __init__(self, image_set, year, use_diff=False):
name = 'voc_' + year + '_' + image_set
if use_diff:
name += '_diff'
imdb.__init__(self, name)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path()
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ( # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.selective_search_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': use_diff,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
Example #30
| Source File: pascal_voc_rbg.py From FPN_Pytorch with MIT License | 5 votes |
|
def __init__(self, image_set, year, devkit_path=None):
imdb.__init__(self, 'voc_' + year + '_' + image_set)
self._year = year
self._image_set = image_set
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'VOC' + self._year)
self._classes = ('__background__', # always index 0
'aeroplane', 'bicycle', 'bird', 'boat',
'bottle', 'bus', 'car', 'cat', 'chair',
'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant',
'sheep', 'sofa', 'train', 'tvmonitor')
self._class_to_ind = dict(list(zip(self.classes, list(range(self.num_classes)))))
self._image_ext = '.jpg'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.gt_roidb
self._salt = str(uuid.uuid4())
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup': True,
'use_salt': True,
'use_diff': False,
'matlab_eval': False,
'rpn_file': None}
assert os.path.exists(self._devkit_path), \
'VOCdevkit path does not exist: {}'.format(self._devkit_path)
assert os.path.exists(self._data_path), \
'Path does not exist: {}'.format(self._data_path)
