args = parse_args()
arg_net = args.network_name
train_datset_name = args.train_dataset_name # 测试数据集名称
val_dataset_name = args.val_dataset_name # 验证数据集名称
set_cfgs = [
'ANCHOR_SCALES',
'[8,16,32]',
'ANCHOR_RATIOS',
'[0.5,1,2]',
'TRAIN.STEPSIZE',
'[50000]',
]
project_path = os.path.abspath('.')
pre_train_weight = project_path + "/data/pre_train_weight/" + arg_net + ".ckpt"
cfg_from_file(project_path + "/experiments/cfgs/" + arg_net +
".yml") #载入参数配置
cfg_from_list(set_cfgs) #修改参数配置
print('Using config:')
pprint.pprint(cfg)
# roidb：所有训练图片的gt_boxes
# imdb：训练数据集的相关信息：包括类别列表，所有的图片名称的索引，数据集名称等等
imdb, roidb = combined_roidb("gridsum_car_train")
print(roidb[0]['boxes'])
print(roidb[0])
print('{:d} roidb entries'.format(len(roidb)))
# output directory where the models are saved
output_dir = get_output_dir(imdb, "")
print('Output will be saved to `{:s}`'.format(output_dir))
# tensorboard directory where the summaries are saved during training
tb_dir = get_output_tb_dir(imdb, "")
roidb.extend(r)
tmp = get_imdb(imdb_names.split('+')[1])
imdb = lib.datasets.imdb.imdb(imdb_names, tmp.classes)
else:
imdb = get_imdb(imdb_names)
return imdb, roidb
if __name__ == '__main__':
args = parse_args()
print('Called with args:')
print(args)
if args.cfg_file is not None:
cfg_from_file(args.cfg_file)
if args.set_cfgs is not None:
cfg_from_list(args.set_cfgs)
print('Using config:')
pprint.pprint(cfg)
np.random.seed(cfg.RNG_SEED)
# train set
imdb, roidb = combined_roidb(args.imdb_name)
print('{:d} roidb entries'.format(len(roidb)))
# output directory where the models are saved
output_dir = get_output_dir(imdb, args.tag)
print('Output will be saved to `{:s}`'.format(output_dir))
if __name__ == '__main__':
args = parse_args()
test_dataset_name = args.test_dataset_name #测试数据集名称
set_cfgs = [
'ANCHOR_SCALES', '[8,16,32]', 'ANCHOR_RATIOS', '[0.5,1,2]',
'TRAIN.STEPSIZE', '[50000]'
]
project_path = os.path.abspath('.')
#测试迭代训练好的参数路径
test_iter_weight_path = os.path.join(
project_path, "output", args.network_name, args.train_dataset_name,
args.network_name + "_faster_rcnn_iter_" + args.iter_number + ".ckpt")
cfg_from_file(project_path + "/experiments/cfgs/" + args.network_name +
".yml") # 载入参数配置
cfg_from_list(set_cfgs) #修改参数配置
print('Using config:')
pprint.pprint(cfg)
# if has model, get the name from it
# if does not, then just use the initialization weights
filename = 'default/' + args.network_name
imdb = get_imdb(test_dataset_name)
#配置Session参数
tfconfig = tf.ConfigProto(allow_soft_placement=True)
tfconfig.gpu_options.allow_growth = True
# init session
