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import argparse
def make_parser():
parser = argparse.ArgumentParser("OC-SORT parameters")
parser.add_argument("--expn", type=str, default=None)
parser.add_argument("-n", "--name", type=str, default=None, help="model name")
# distributed
parser.add_argument( "--dist-backend", default="nccl", type=str, help="distributed backend")
parser.add_argument("--output_dir", type=str, default="evaldata/trackers/mot_challenge")
parser.add_argument("--dist-url", default=None, type=str, help="url used to set up distributed training")
parser.add_argument("-b", "--batch-size", type=int, default=64, help="batch size")
parser.add_argument("-d", "--devices", default=None, type=int, help="device for training")
parser.add_argument("--local_rank", default=0, type=int, help="local rank for dist training")
parser.add_argument( "--num_machines", default=1, type=int, help="num of node for training")
parser.add_argument("--machine_rank", default=0, type=int, help="node rank for multi-node training")
parser.add_argument(
"-f", "--exp_file",
default=None,
type=str,
help="pls input your expriment description file",
)
parser.add_argument(
"--fp16", dest="fp16",
default=False,
action="store_true",
help="Adopting mix precision evaluating.",
)
parser.add_argument("--fuse", dest="fuse", default=False, action="store_true", help="Fuse conv and bn for testing.",)
parser.add_argument("--trt", dest="trt", default=False, action="store_true", help="Using TensorRT model for testing.",)
parser.add_argument("--test", dest="test", default=False, action="store_true", help="Evaluating on test-dev set.",)
parser.add_argument("--speed", dest="speed", default=False, action="store_true", help="speed test only.",)
parser.add_argument("opts", help="Modify config options using the command-line", default=None, nargs=argparse.REMAINDER,)
# det args
parser.add_argument("-c", "--ckpt", default=None, type=str, help="ckpt for eval")
parser.add_argument("--conf", default=0.1, type=float, help="test conf")
parser.add_argument("--nms", default=0.7, type=float, help="test nms threshold")
parser.add_argument("--tsize", default=None, type=int, help="test img size")
parser.add_argument("--seed", default=None, type=int, help="eval seed")
# tracking args
parser.add_argument("--track_thresh", type=float, default=0.6, help="detection confidence threshold")
parser.add_argument("--iou_thresh", type=float, default=0.3, help="the iou threshold in Sort for matching")
parser.add_argument("--min_hits", type=int, default=3, help="min hits to create track in SORT")
parser.add_argument("--inertia", type=float, default=0.2, help="the weight of VDC term in cost matrix")
parser.add_argument("--deltat", type=int, default=3, help="time step difference to estimate direction")
parser.add_argument("--track_buffer", type=int, default=30, help="the frames for keep lost tracks")
parser.add_argument("--match_thresh", type=float, default=0.9, help="matching threshold for tracking")
parser.add_argument('--min-box-area', type=float, default=100, help='filter out tiny boxes')
parser.add_argument("--gt-type", type=str, default="_val_half", help="suffix to find the gt annotation")
parser.add_argument("--mot20", dest="mot20", default=False, action="store_true", help="test mot20.")
parser.add_argument("--public", action="store_true", help="use public detection")
parser.add_argument('--asso', default="iou", help="similarity function: iou/giou/diou/ciou/ctdis")
parser.add_argument("--use_byte", dest="use_byte", default=False, action="store_true", help="use byte in tracking.")
parser.add_argument("--TCM_first_step", default=False, action="store_true", help="use TCM in first step.")
parser.add_argument("--TCM_byte_step", default=False, action="store_true", help="use TCM in byte step.")
parser.add_argument("--TCM_first_step_weight", type=float, default=1.0, help="TCM first step weight")
parser.add_argument("--TCM_byte_step_weight", type=float, default=1.0, help="TCM second step weight")
parser.add_argument("--with_reid", default=False, action="store_true", help="use ReID.")
# for fast reid
parser.add_argument("--EG_weight_high_score", default=0.0, type=float, help="weight of appearance cost matrix when using EG")
parser.add_argument("--EG_weight_low_score", default=0.0, type=float, help="weight of appearance cost matrix when using EG")
parser.add_argument("--low_thresh", default=0.1, type=float, help="threshold of low score detections for BYTE")
parser.add_argument("--high_score_matching_thresh", default=0.8, type=float, help="matching threshold for detections with high score")
parser.add_argument("--low_score_matching_thresh", default=0.5, type=float, help="matching threshold for detections with low score")
parser.add_argument("--alpha", default=0.8, type=float, help="momentum of embedding update")
parser.add_argument("--with_fastreid", dest="with_fastreid", default=False, action="store_true", help="use FastReID flag.")
parser.add_argument("--fast_reid_config", dest="fast_reid_config", default=r"fast_reid/configs/CUHKSYSU_DanceTrack/sbs_S50.yml", type=str, help="reid config file path")
parser.add_argument("--fast_reid_weights", dest="fast_reid_weights", default=r"fast_reid/logs/CUHKSYSU_DanceTrack/sbs_S50/model_final.pth", type=str, help="reid weight path")
parser.add_argument("--with_longterm_reid", dest="with_longterm_reid", default=False, action="store_true", help="use long-term reid features for association.")
parser.add_argument("--longterm_reid_weight", default=0.0, type=float, help="weight of appearance cost matrix when using long term reid features in 1st stage association")
parser.add_argument("--longterm_reid_weight_low", default=0.0, type=float, help="weight of appearance cost matrix when using long term reid features in 2nd stage association")
parser.add_argument("--with_longterm_reid_correction", dest="with_longterm_reid_correction", default=False, action="store_true", help="use long-term reid features for association correction.")
parser.add_argument("--longterm_reid_correction_thresh", default=1.0, type=float, help="threshold of correction when using long term reid features in 1st stage association")
parser.add_argument("--longterm_reid_correction_thresh_low", default=1.0, type=float, help="threshold of correction when using long term reid features in 2nd stage association")
parser.add_argument("--longterm_bank_length", type=int, default=30, help="max length of reid feat bank")
parser.add_argument("--adapfs", dest="adapfs", default=False, action="store_true", help="Adaptive Feature Smoothing.")
# ECC for CMC
parser.add_argument("--ECC", dest="ECC", default=False, action="store_true", help="use ECC for CMC.")
# for kitti/bdd100k inference with public detections
parser.add_argument('--raw_results_path', type=str, default="exps/permatrack_kitti_test/",
help="path to the raw tracking results from other tracks")
parser.add_argument('--out_path', type=str, help="path to save output results")
parser.add_argument("--dataset", type=str, default="mot17", help="kitti or bdd")
parser.add_argument("--hp", action="store_true", help="use head padding to add the missing objects during \
initializing the tracks (offline).")
# for demo video
parser.add_argument("--demo_type", default="image", help="demo type, eg. image, video and webcam")
parser.add_argument( "--path", default="./videos/demo.mp4", help="path to images or video")
parser.add_argument("--demo_dancetrack", default=False, action="store_true",
help="only for dancetrack demo, replace timestamp with dancetrack sequence name.")
parser.add_argument("--camid", type=int, default=0, help="webcam demo camera id")
parser.add_argument(
"--save_result",
action="store_true",
help="whether to save the inference result of image/video",
)
parser.add_argument(
"--aspect_ratio_thresh", type=float, default=1.6,
help="threshold for filtering out boxes of which aspect ratio are above the given value."
)
parser.add_argument('--min_box_area', type=float, default=10, help='filter out tiny boxes')
parser.add_argument(
"--device",
default="gpu",
type=str,
help="device to run our model, can either be cpu or gpu",
)
return parser
def args_merge_params_form_exp(args,exp):
for k, v in exp.__dict__.items():
if k in args.__dict__:
(args.__dict__)[k] = v |