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')