def get_coco(args):
from symimdb.coco import coco
if not args.imageset:
args.imageset = 'train2017'
args.rcnn_num_classes = len(coco.classes)
isets = args.imageset.split('+')
roidb = []
for iset in isets:
imdb = coco(iset, 'data', 'data/coco')
imdb.filter_roidb()
imdb.append_flipped_images()
roidb.extend(imdb.roidb)
return roidb
def get_coco(args):
from symimdb.coco import coco
if not args.imageset:
args.imageset = 'train2017'
args.rcnn_num_classes = len(coco.classes)
isets = args.imageset.split('+')
roidb = []
for iset in isets:
imdb = coco(iset, 'data', 'data/coco')
imdb.filter_roidb()
imdb.append_flipped_images()
roidb.extend(imdb.roidb)
return roidb
def get_coco(system_dict):
from symimdb.coco import coco
if not system_dict["imageset"]:
system_dict["imageset"] = 'train2017'
isets = system_dict["imageset"].split('+')
roidb = []
for iset in isets:
imdb = coco(iset, system_dict["dataset_root"], system_dict["dataset_dir"])
system_dict["rcnn_num_classes"] = len(imdb.classes)
imdb.filter_roidb()
imdb.append_flipped_images()
roidb.extend(imdb.roidb)
return roidb
def get_coco(system_dict):
'''
Internal function: Get coco dataset as per dataset params
Args:
system_dict (dict): Dictionary of all the parameters selected for training
Returns:
list: List of all the images and labels in coco-db format
'''
from symimdb.coco import coco
if not system_dict["imageset"]:
system_dict["imageset"] = 'train2017'
isets = system_dict["imageset"].split('+')
roidb = []
for iset in isets:
imdb = coco(iset, system_dict["dataset_root"], system_dict["dataset_dir"])
system_dict["rcnn_num_classes"] = len(imdb.classes)
imdb.filter_roidb()
imdb.append_flipped_images()
roidb.extend(imdb.roidb)
return roidb
def get_coco(args):
from symimdb.coco import coco
if not args.imageset:
args.imageset = 'val2017'
args.rcnn_num_classes = len(coco.classes)
return coco(args.imageset, 'data', 'data/coco')
def get_coco(args):
from symimdb.coco import coco
if not args.imageset:
args.imageset = 'val2017'
args.rcnn_num_classes = len(coco.classes)
return coco(args.imageset, 'data', 'data/coco')
