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opts.py
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# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
import argparse
import os
import os.path as osp
class opts(object):
"""
Defines options for experiment settings, system settings, logging, model params,
input config, training config, testing config, and tracking params.
"""
def __init__(
self,
load_model: str = "",
gpus=[0, 1],
save_all: bool = False,
arch: str = "dla_34",
head_conv: int = -1,
input_h: int = -1,
input_w: int = -1,
lr: float = 1e-4,
lr_step=[20, 27],
num_epochs: int = 30,
num_iters: int = -1,
val_intervals: int = 5,
conf_thres: float = 0.6,
det_thres: float = 0.3,
nms_thres: float = 0.4,
track_buffer: int = 30,
min_box_area: float = 200,
reid_dim: int = 512,
root_dir: str = os.getcwd(),
) -> None:
# Set defaults for parameters which are less important
self.task = "mot"
self.dataset = "jde"
self.resume = False
self.exp_id = "default"
self.test = False
self.num_workers = 8
self.not_cuda_benchmark = False
self.seed = 317
self.print_iter = 0
self.hide_data_time = False
self.metric = "loss"
self.vis_thresh = 0.5
self.pad = 31
self.num_stacks = 1
self.down_ratio = 4
self.input_res = -1
self.num_iters = -1
self.trainval = False
self.K = 128
self.not_prefetch_test = True
self.keep_res = False
self.fix_res = not self.keep_res
self.test_mot16 = False
self.val_mot15 = False
self.test_mot15 = False
self.val_mot16 = False
self.test_mot16 = False
self.val_mot17 = False
self.val_mot20 = False
self.test_mot20 = False
self.input_video = ""
self.output_format = "video"
self.output_root = ""
self.data_cfg = ""
self.data_dir = ""
self.mse_loss = False
self.hm_gauss = 8
self.reg_loss = "l1"
self.hm_weight = 1
self.off_weight = 1
self.wh_weight = 0.1
self.id_loss = "ce"
self.id_weight = 1
self.norm_wh = False
self.dense_wh = False
self.cat_spec_wh = False
self.not_reg_offset = False
self.reg_offset = not self.not_reg_offset
# Set/overwrite defaults for parameters which are more important
self.load_model = load_model
self.gpus = gpus
self.save_all = save_all
self.arch = arch
self.set_head_conv(head_conv)
self.input_h = input_h
self.input_w = input_w
self.lr = lr
self.lr_step = lr_step
self.num_epochs = num_epochs
self.val_intervals = val_intervals
self.conf_thres = conf_thres
self.det_thres = det_thres
self.nms_thres = nms_thres
self.track_buffer = track_buffer
self.min_box_area = min_box_area
self.reid_dim = reid_dim
# init
self._init_root_dir(root_dir)
self._init_batch_sizes(batch_size=12, master_batch_size=-1)
self._init_dataset_info()
def _init_root_dir(self, value):
self.root_dir = value
self.exp_dir = osp.join(self.root_dir, "exp", self.task)
self.save_dir = osp.join(self.exp_dir, self.exp_id)
self.debug_dir = osp.join(self.save_dir, "debug")
def _init_batch_sizes(self, batch_size, master_batch_size) -> None:
self.batch_size = batch_size
self.master_batch_size = (
master_batch_size
if master_batch_size != -1
else self.batch_size // len(self.gpus)
)
rest_batch_size = self.batch_size - self.master_batch_size
self.chunk_sizes = [self.master_batch_size]
for i in range(len(self.gpus) - 1):
chunk = rest_batch_size // (len(self.gpus) - 1)
if i < rest_batch_size % (len(self.gpus) - 1):
chunk += 1
self.chunk_sizes.append(chunk)
def _init_dataset_info(self) -> None:
default_dataset_info = {
"mot": {
"default_resolution": [608, 1088],
"num_classes": 1,
"mean": [0.408, 0.447, 0.470],
"std": [0.289, 0.274, 0.278],
"dataset": "jde",
"nID": 14455,
}
}
class Struct:
def __init__(self, entries):
for k, v in entries.items():
self.__setattr__(k, v)
dataset = Struct(default_dataset_info[self.task])
self.dataset = dataset.dataset
self.update_dataset_info_and_set_heads(dataset)
def update_dataset_res(self, input_h, input_w) -> None:
self.input_h = input_h
self.input_w = input_w
self.output_h = self.input_h // self.down_ratio
self.output_w = self.input_w // self.down_ratio
self.input_res = max(self.input_h, self.input_w)
self.output_res = max(self.output_h, self.output_w)
def update_dataset_info_and_set_heads(self, dataset) -> None:
input_h, input_w = dataset.default_resolution
self.mean, self.std = dataset.mean, dataset.std
self.num_classes = dataset.num_classes
# input_h(w): input_h overrides input_res overrides dataset default
input_h = self.input_res if self.input_res > 0 else input_h
input_w = self.input_res if self.input_res > 0 else input_w
self.input_h = self.input_h if self.input_h > 0 else input_h
self.input_w = self.input_w if self.input_w > 0 else input_w
self.output_h = self.input_h // self.down_ratio
self.output_w = self.input_w // self.down_ratio
self.input_res = max(self.input_h, self.input_w)
self.output_res = max(self.output_h, self.output_w)
if self.task == "mot":
self.heads = {
"hm": self.num_classes,
"wh": 2 if not self.cat_spec_wh else 2 * self.num_classes,
"id": self.reid_dim,
}
if self.reg_offset:
self.heads.update({"reg": 2})
self.nID = dataset.nID
self.img_size = (self.input_w, self.input_h)
else:
assert 0, "task not defined"
def set_gpus(self, value):
gpus_list = [int(gpu) for gpu in value.split(",")]
self.gpus = (
[i for i in range(len(gpus_list))] if gpus_list[0] >= 0 else [-1]
)
self.gpus_str = value
def set_head_conv(self, value):
h = value if value != -1 else 256
self.head_conv = h