def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
python类imdb()的实例源码
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def combined_roidb(imdb_names):
def get_roidb(imdb_name):
imdb = get_imdb(imdb_name)
print 'Loaded dataset `{:s}` for training'.format(imdb.name)
roidb = get_training_roidb(imdb)
return roidb
roidbs = [get_roidb(s) for s in imdb_names.split('+')]
roidb = roidbs[0]
if len(roidbs) > 1:
for r in roidbs[1:]:
roidb.extend(r)
imdb = datasets.imdb(imdb_names)
else:
imdb = get_imdb(imdb_names)
return imdb, roidb
pascal_voc2.py 文件源码
项目：Automatic_Group_Photography_Enhancement
作者: Yuliang-Zou
项目源码
文件源码
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def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
pascal3d.py 文件源码
项目：Automatic_Group_Photography_Enhancement
作者: Yuliang-Zou
项目源码
文件源码
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def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def __init__(self, image_set, devkit_path=None):
datasets.imdb.__init__(self,image_set)#imageset ?train test
self._image_set = image_set
self._devkit_path = devkit_path
self._data_path = os.path.join(self._devkit_path)
self._classes = ('__background__','car','person','bike', 'truck', 'van', 'tram', 'misc')#????
self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))#????{'__background__':'0','car':'1'}
if self._image_set=='KakouTrain':
self._image_index = self._load_image_set_index('KITTI_train_list.txt')#??????
elif self._image_set=='KakouTest':
self._image_index = self._load_image_set_index('KITTI_val_list.txt')#??????
# Default to roidb handler
self._roidb_handler = self.selective_search_roidb
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'top_k' : 2000,
'use_diff' : 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)
def selective_search_roidb(self):#????
cache_file = os.path.join(self.cache_path,self.name + '_selective_search_roidb.pkl')
if os.path.exists(cache_file): #???cache_file???????.pkl??
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
if self._image_set !='KakouTest':
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
else:
roidb = self._load_selective_search_roidb(None)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def selective_search_IJCV_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
'{:s}_selective_search_IJCV_top_{:d}_roidb.pkl'.
format(self.name, self.config['top_k']))
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_IJCV_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def __init__(self, image_set, year, devkit_path=None):
datasets.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 = ('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
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'use_diff' : False,
'top_k' : 2000}
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)
def selective_search_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
self.name + '_selective_search_roidb.pkl')
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
if int(self._year) == 2007 or self._image_set != 'test':
gt_roidb = self.gt_roidb()
# ss_roidb = self._load_selective_search_roidb(gt_roidb)
# roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
roidb = self._load_selective_search_roidb(gt_roidb)
else:
roidb = self._load_selective_search_roidb(None)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def __init__(self, image_set, year, devkit_path=None, image_type = 'images'):
datasets.imdb.__init__(self, 'nyud2_' + image_type + '_' + year + '_' + image_set)
self._year = year
self._devkit_path = self._get_default_path() if devkit_path is None \
else devkit_path
self._data_path = os.path.join(self._devkit_path, 'data')
self._classes = ('__background__', # always index 0
'bathtub', 'bed', 'bookshelf', 'box', 'chair', 'counter', 'desk',
'door', 'dresser', 'garbage-bin', 'lamp', 'monitor', 'night-stand',
'pillow', 'sink', 'sofa', 'table', 'television', 'toilet');
self._class_to_ind = dict(zip(self.classes, xrange(self.num_classes)))
self._image_type = image_type;
self._image_set = image_set;
self._image_ext = '.png'
self._image_index = self._load_image_set_index()
# Default to roidb handler
self._roidb_handler = self.mcg_roidb
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'top_k' : 2000}
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)
def mcg_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
self.name + '_mcg_roidb.pkl')
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
if True:
gt_roidb = self.gt_roidb()
ss_roidb = self._load_mcg_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
else:
roidb = self._load_mcg_roidb(None)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote mcg roidb to {}'.format(cache_file)
return roidb
def __init__(self, image_set, year, devkit_path=None):
datasets.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
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'top_k' : 2000}
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)
def selective_search_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
self.name + '_selective_search_roidb.pkl')
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
if int(self._year) == 2007 or self._image_set != 'test':
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
else:
roidb = self._load_selective_search_roidb(None)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def __init__(self, image_set, year, devkit_path=None):
datasets.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
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True,
'top_k' : 2000,
'use_diff' : 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)
def selective_search_roidb(self):
"""
Return the database of selective search regions of interest.
Ground-truth ROIs are also included.
This function loads/saves from/to a cache file to speed up future calls.
"""
cache_file = os.path.join(self.cache_path,
self.name + '_selective_search_roidb.pkl')
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print '{} ss roidb loaded from {}'.format(self.name, cache_file)
return roidb
if int(self._year) == 2007 or self._image_set != 'test':
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)
else:
roidb = self._load_selective_search_roidb(None)
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print 'wrote ss roidb to {}'.format(cache_file)
return roidb
def rpn_roidb(self):
if int(self._year) == 2007 or self._image_set != 'test':
gt_roidb = self.gt_roidb()
rpn_roidb = self._load_rpn_roidb(gt_roidb)
roidb = datasets.imdb.merge_roidbs(gt_roidb, rpn_roidb)
else:
roidb = self._load_rpn_roidb(None)
return roidb
def __init__(self, image_set, year, devkit_path=None):
datasets.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.gt_roidb
self._comp_id = 'comp4'
# PASCAL specific config options
self.config = {'cleanup' : True,
'use_salt' : True}
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)
