-
Notifications
You must be signed in to change notification settings - Fork 0
/
parser.py
158 lines (132 loc) · 7.14 KB
/
parser.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
import argparse
import os.path as osp
import os
from misc import pyutils
import random
import torch
import numpy as np
def str2bool(v):
if isinstance(v, bool):
return v
if v.lower() in ('yes', 'true', 't', 'y', '1'):
return True
elif v.lower() in ('no', 'false', 'f', 'n', '0'):
return False
else:
raise argparse.ArgumentTypeError('Boolean value expected.')
def seed_torch(seed=1):
random.seed(seed)
os.environ['PYTHONHASHSEED'] = str(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(seed) # if you are using multi-GPU.
torch.backends.cudnn.benchmark = False
torch.backends.cudnn.deterministic = True
# torch.backends.cudnn.enabled = False
def get_parser():
parser = argparse.ArgumentParser()
# Environment
# parser.add_argument("--num_workers", default=os.cpu_count()//2, type=int)
parser.add_argument("--num_workers", default=12, type=int)
parser.add_argument("--seed", default=-1, type=int, help="Set -1 to use random seed.")
# Dataset
parser.add_argument("--voc12_root", default='/path/to/VOC2012', type=str,
help="Path to VOC 2012 Devkit, must contain ./JPEGImages as subdirectory.")
parser.add_argument("--train_list", default="voc12/train_aug.txt", type=str)
parser.add_argument("--val_list", default="voc12/val.txt", type=str)
parser.add_argument("--infer_list", default="voc12/train_aug.txt", type=str,
help="voc12/train_aug.txt to train a fully supervised model, "
"voc12/train.txt or voc12/val.txt to quickly check the quality of the labels.")
parser.add_argument("--chainer_eval_set", default="train", type=str)
# Class Activation Map
parser.add_argument("--cam_network", default="net.resnet50_cam", type=str)
parser.add_argument("--feature_dim", default=2048, type=int)
parser.add_argument("--cam_crop_size", default=512, type=int)
parser.add_argument("--cam_batch_size", default=16, type=int)
parser.add_argument("--cam_num_epoches", default=5, type=int)
parser.add_argument("--cam_learning_rate", default=0.1, type=float)
parser.add_argument("--cam_weight_decay", default=1e-4, type=float)
parser.add_argument("--cam_eval_thres", default=0.15, type=float)
parser.add_argument("--cam_scales", default=(1.0, 0.5, 1.5, 2.0),
help="Multi-scale inferences")
parser.add_argument("--num_cores_eval", default=8, type=int)
# QA-CLIMS
parser.add_argument("--clims_network", default="net.resnet50_clims", type=str)
parser.add_argument("--clims_num_epoches", default=15, type=int)
parser.add_argument("--clims_learning_rate", default=0.00035, type=float)
parser.add_argument('--hyper', default='10,8,0.2', type=str)
parser.add_argument('--clip', default='ViT-L/14', type=str)
# Mining Inter-pixel Relations
parser.add_argument("--conf_fg_thres", default=0.3, type=float)
parser.add_argument("--conf_bg_thres", default=0.1, type=float)
# Inter-pixel Relation Network (IRNet)
parser.add_argument("--irn_network", default="net.resnet50_irn", type=str)
parser.add_argument("--irn_crop_size", default=512, type=int)
parser.add_argument("--irn_batch_size", default=32, type=int)
parser.add_argument("--irn_num_epoches", default=3, type=int)
parser.add_argument("--irn_learning_rate", default=0.1, type=float)
parser.add_argument("--irn_weight_decay", default=1e-4, type=float)
# Random Walk Params
parser.add_argument("--beta", default=10)
parser.add_argument("--exp_times", default=8,
help="Hyper-parameter that controls the number of random walk iterations,"
"The random walk is performed 2^{exp_times}.")
parser.add_argument("--sem_seg_bg_thres", default=0.2)
# Output Path
parser.add_argument("--work_space", default="experiments/test", type=str) # set your path
parser.add_argument("--log_name", default="sample_train_eval", type=str)
parser.add_argument("--cam_weights_name", default="res50_cam.pth", type=str)
parser.add_argument("--clims_weights_name", default="res50_qa_clims", type=str)
parser.add_argument("--irn_weights_name", default="res50_irn.pth", type=str)
parser.add_argument("--cam_out_dir", default="cam_mask", type=str)
parser.add_argument("--ir_label_out_dir", default="ir_label", type=str)
parser.add_argument("--sem_seg_out_dir", default="sem_seg", type=str)
# Step
parser.add_argument("--train_cam_pass", type=str2bool, default=False)
parser.add_argument("--train_qa_clims_pass", type=str2bool, default=False)
parser.add_argument("--make_cam_pass", type=str2bool, default=False)
parser.add_argument("--make_clims_pass", type=str2bool, default=False)
parser.add_argument("--eval_cam_pass", type=str2bool, default=False)
parser.add_argument("--cam_to_ir_label_pass", type=str2bool, default=False)
parser.add_argument("--train_irn_pass", type=str2bool, default=False)
parser.add_argument("--make_sem_seg_pass", type=str2bool, default=False)
parser.add_argument("--eval_sem_seg_pass", type=str2bool, default=False)
# DDP
parser.add_argument("--use_distributed_train",
type=str2bool, default=False)
parser.add_argument('--local_rank', default=-1, type=int,
help='DONT CHANGE! for distributed train')
# NCELoss
parser.add_argument("--nce_t", type=float, default=0.7)
# VQA
parser.add_argument("--vqa_fg_file", type=str, default='vqa/voc_vqa_fg_blip.npy')
parser.add_argument("--vqa_bg_file", type=str, default='vqa/vqa/voc_vqa_bg_blip.npy')
parser.add_argument("--vqa_fg_cache_file", type=str, default='vqa/voc_vqa_fg_blip_ViT-L-14_cache.npy')
parser.add_argument("--vqa_bg_cache_file", type=str, default='vqa/voc_vqa_bg_blip_ViT-L-14_cache.npy')
# mask-adapted CLIP
parser.add_argument("--use_mask_clip", type=str2bool, default=True)
return parser
def parse_args(parser):
args = parser.parse_args()
args.log_name = osp.join(args.work_space, args.log_name)
args.cam_weights_name = osp.join(args.work_space, args.cam_weights_name)
args.irn_weights_name = osp.join(args.work_space, args.irn_weights_name)
args.cam_out_dir = osp.join(args.work_space, args.cam_out_dir)
args.ir_label_out_dir = osp.join(args.work_space, args.ir_label_out_dir)
args.sem_seg_out_dir = osp.join(args.work_space, args.sem_seg_out_dir)
args.clims_weights_name = osp.join(args.work_space, args.clims_weights_name)
os.makedirs(args.work_space, exist_ok=True)
os.makedirs(args.cam_out_dir, exist_ok=True)
os.makedirs(args.ir_label_out_dir, exist_ok=True)
os.makedirs(args.sem_seg_out_dir, exist_ok=True)
pyutils.Logger(args.log_name + '.log')
print(vars(args))
if hasattr(args, 'mscoco_root'):
assert os.path.exists(args.mscoco_root), "MSCOCO root not found"
elif hasattr(args, 'voc12_root'):
assert os.path.exists(args.voc12_root), "VOC12 root not found"
if args.seed != -1:
seed_torch(args.seed)
print(f'[pytorch seed: {torch.initial_seed()}]')
return args