/
argument.py
64 lines (53 loc) · 1.81 KB
/
argument.py
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import argparse
class TEST:
def __init__(self):
self.local_rank = 0
self.lr = 0.0001
self.l2 = 0.00001
self.batch = 3
self.epoch = 400000
self.n_save_sample = 5
self.ckpt = ''
self.path = 'D:/datasets/Image/COCO/annotations_trainval2017'
self.checkpoint = 'checkpoint/epoch-1301.pt'
def get_argparser():
parser = argparse.ArgumentParser()
parser.add_argument('--local_rank', type=int, default=0)
parser.add_argument('--lr', type=float, default=0.001)
parser.add_argument('--l2', type=float, default=0.0001)
parser.add_argument('--batch', type=int, default=16)
parser.add_argument('--epoch', type=int, default=24)
parser.add_argument('--n_save_sample', type=int, default=5)
parser.add_argument('--ckpt', type=str)
parser.add_argument('path', type=str)
return parser
def get_args():
# parser = get_argparser()
# args = parser.parse_args()
args = TEST() # Cheating for code test
args.feat_channels = [0, 0, 512, 768, 1024]
args.out_channel = 256
args.use_p5 = True
args.n_class = 33
args.n_conv = 4
args.prior = 0.01
args.threshold = 0.5
args.top_n = 1000
args.nms_threshold = 0.6
args.post_top_n = 100
args.min_size = 0
args.fpn_strides = [8, 16, 32, 64, 128]
args.gamma = 2.0
args.alpha = 0.25
args.sizes = [[-1, 64], [64, 128], [128, 256], [256, 512], [512, 100000000]]
args.train_min_size_range = (640, 800)
args.train_max_size = 1333
args.test_min_size = 800
args.test_max_size = 1333
args.pixel_mean = [0.40789654, 0.44719302, 0.47026115]
args.pixel_std = [0.28863828, 0.27408164, 0.27809835]
args.size_divisible = 32
args.center_sample = True
args.pos_radius = 1.5
args.iou_loss_type = 'giou'
return args