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 = 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_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 = 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 _roidb_from_proposals(self, method):
"""
Creates a roidb from pre-computed proposals of a particular methods.
"""
top_k = self.config['top_k']
cache_file = osp.join(self.cache_path, self.name +
'_{:s}_top{:d}'.format(method, top_k) +
'_roidb.pkl')
if osp.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = pickle.load(fid)
print('{:s} {:s} roidb loaded from {:s}'.format(self.name, method,
cache_file))
return roidb
if self._image_set in self._gt_splits:
gt_roidb = self.gt_roidb()
method_roidb = self._load_proposals(method, gt_roidb)
roidb = imdb.merge_roidbs(gt_roidb, method_roidb)
# Make sure we don't use proposals that are contained in crowds
roidb = _filter_crowd_proposals(roidb, self.config['crowd_thresh'])
else:
roidb = self._load_proposals(method, None)
with open(cache_file, 'wb') as fid:
pickle.dump(roidb, fid, pickle.HIGHEST_PROTOCOL)
print('wrote {:s} roidb to {:s}'.format(method, cache_file))
return roidb
def rpn_roidb(self):
gt_roidb = self.gt_roidb()
rpn_roidb = self._load_rpn_roidb(gt_roidb)
roidb = imdb.merge_roidbs(gt_roidb, rpn_roidb)
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 = imdb.merge_roidbs(gt_roidb, rpn_roidb)
else:
roidb = self._load_rpn_roidb(None)
return roidb
def region_proposal_roidb(self):
"""
Return the database of 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 + '_' + cfg.SUBCLS_NAME + '_' +
cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = cPickle.load(fid)
print('{} roidb loaded from {}'.format(self.name, cache_file))
return roidb
if self._image_set != 'test':
gt_roidb = self.gt_roidb()
print('Loading region proposal network boxes...')
model = cfg.REGION_PROPOSAL
rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
print('Region proposal network boxes loaded')
roidb = imdb.merge_roidbs(rpn_roidb, gt_roidb)
else:
print('Loading region proposal network boxes...')
model = cfg.REGION_PROPOSAL
roidb = self._load_rpn_roidb(None, model)
print('Region proposal network boxes loaded')
print('{} region proposals per image'.format(self._num_boxes_proposal /
len(self.image_index)))
with open(cache_file, 'wb') as fid:
cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)
print('wrote roidb to {}'.format(cache_file))
return roidb
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 not self._image_set.startswith('test'):
gt_roidb = self.gt_roidb()
ss_roidb = self._load_selective_search_roidb(gt_roidb)
roidb = imdb.merge_roidbs(gt_roidb, ss_roidb)
else:
roidb = self._load_selective_search_roidb(None)
# Keep max of e.g. 2000 rois
if type(self._maxNrRois) == int:
print "Only keep the first %d ROIs..." % self._maxNrRois
for i in xrange(self.num_images):
gt_overlaps = roidb[i]['gt_overlaps']
gt_overlaps = gt_overlaps.todense()[:self._maxNrRois]
gt_overlaps = scipy.sparse.csr_matrix(gt_overlaps)
roidb[i]['boxes'] = roidb[i]['boxes'][:self._maxNrRois, :]
roidb[i]['gt_classes'] = roidb[i]['gt_classes'][:self._maxNrRois]
roidb[i]['gt_overlaps'] = roidb[i]['gt_overlaps'] = gt_overlaps
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 region_proposal_roidb(self):
"""
Return the database of 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 + '_' + cfg.SUBCLS_NAME + '_' +
cfg.REGION_PROPOSAL + '_region_proposal_roidb.pkl')
if os.path.exists(cache_file):
with open(cache_file, 'rb') as fid:
roidb = pickle.load(fid)
print('{} roidb loaded from {}'.format(self.name, cache_file))
return roidb
if self._image_set != 'test':
gt_roidb = self.gt_roidb()
print('Loading region proposal network boxes...')
if self._image_set == 'trainval':
model = cfg.REGION_PROPOSAL + '_227/'
else:
model = cfg.REGION_PROPOSAL + '_125/'
rpn_roidb = self._load_rpn_roidb(gt_roidb, model)
print('Region proposal network boxes loaded')
roidb = imdb.merge_roidbs(rpn_roidb, gt_roidb)
# print 'Loading voxel pattern boxes...'
# if self._image_set == 'trainval':
# model = '3DVP_227'
# else:
# model = '3DVP_125/'
# vp_roidb = self._load_voxel_pattern_roidb(gt_roidb, model)
# print 'Voxel pattern boxes loaded'
# roidb = imdb.merge_roidbs(vp_roidb, gt_roidb)
# print 'Loading selective search boxes...'
# ss_roidb = self._load_selective_search_roidb(gt_roidb)
# print 'Selective search boxes loaded'
# print 'Loading ACF boxes...'
# acf_roidb = self._load_acf_roidb(gt_roidb)
# print 'ACF boxes loaded'
# roidb = imdb.merge_roidbs(ss_roidb, gt_roidb)
# roidb = imdb.merge_roidbs(roidb, acf_roidb)
else:
print('Loading region proposal network boxes...')
model = cfg.REGION_PROPOSAL + '_227/'
roidb = self._load_rpn_roidb(None, model)
print('Region proposal network boxes loaded')
# print 'Loading voxel pattern boxes...'
# model = '3DVP_227/'
# roidb = self._load_voxel_pattern_roidb(None, model)
# print 'Voxel pattern boxes loaded'
# print 'Loading selective search boxes...'
# roidb = self._load_selective_search_roidb(None)
# print 'Selective search boxes loaded'
# print 'Loading ACF boxes...'
# acf_roidb = self._load_acf_roidb(None)
# print 'ACF boxes loaded'
# roidb = imdb.merge_roidbs(roidb, acf_roidb)
print('{} region proposals per image'.format(self._num_boxes_proposal /
len(self.image_index)))
with open(cache_file, 'wb') as fid:
pickle.dump(roidb, fid, pickle.HIGHEST_PROTOCOL)
print('wrote roidb to {}'.format(cache_file))
return roidb
