-
Notifications
You must be signed in to change notification settings - Fork 8
/
test.py
69 lines (54 loc) · 2.15 KB
/
test.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
"""
This code is modified from Hao Luo's repository.
Paper: Bag of Tricks and A Strong Baseline for Deep Person Re-identification
https://github.com/michuanhaohao/reid-strong-baseline
-------------------------------------------------------------------------------
Edited by Binh X. Nguyen and Binh D. Nguyen
Paper: Graph-based Person Signature for Person Re-Identifications
https://github.com/aioz-ai/CVPRW21_GPS
"""
import argparse
import os
import sys
from os import mkdir
from torch.backends import cudnn
sys.path.append('.')
from config import cfg
from data import make_data_loader
from engine.inference import inference
from modeling import build_model
from utils.logger import setup_logger
def main():
parser = argparse.ArgumentParser(description="ReID Baseline Inference")
parser.add_argument(
"--config_file", default="", help="path to config file", type=str
)
parser.add_argument("opts", help="Modify config options using the command-line", default=None,
nargs=argparse.REMAINDER)
args = parser.parse_args()
num_gpus = int(os.environ["WORLD_SIZE"]) if "WORLD_SIZE" in os.environ else 1
if args.config_file != "":
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
cfg.freeze()
output_dir = cfg.OUTPUT_DIR
if output_dir and not os.path.exists(output_dir):
mkdir(output_dir)
logger = setup_logger("reid_baseline", output_dir, 0)
logger.info("Using {} GPUS".format(num_gpus))
logger.info(args)
if args.config_file != "":
logger.info("Loaded configuration file {}".format(args.config_file))
with open(args.config_file, 'r') as cf:
config_str = "\n" + cf.read()
logger.info(config_str)
logger.info("Running with config:\n{}".format(cfg))
if cfg.MODEL.DEVICE == "cuda":
os.environ['CUDA_VISIBLE_DEVICES'] = cfg.MODEL.DEVICE_ID
cudnn.benchmark = True
train_loader, val_loader, num_query, num_classes = make_data_loader(cfg)
model = build_model(cfg, num_classes)
model.load_param(cfg.TEST.WEIGHT)
inference(cfg, model, val_loader, num_query)
if __name__ == '__main__':
main()