/
config.py
190 lines (174 loc) · 4.72 KB
/
config.py
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# directory settings
data_sets = {
'root_dir': "template_files/train_test_data",
'dates': ['2019_04_30', '2019_05_28'],
'cam_anno': [False, False],
}
train_sets = {
'root_dir': "template_files/train_test_data",
'dates': ['2019_04_30'],
'seqs': [
['2019_04_30_pbms002'],
], # 'seqs' is two list corresponding to 'dates', include all seqs if None
'cam_anno': [False],
}
valid_sets = {
'root_dir': "template_files/train_test_data",
'dates': ['2019_05_28'],
'seqs': [
['2019_05_28_pm2s012']
], # 'seqs' is two list corresponding to 'dates', include all seqs if None
}
test_sets = {
'root_dir': "template_files/train_test_data",
'dates': ['2019_05_28'],
'seqs': [
['2019_05_28_pm2s012']
], # 'seqs' is two list corresponding to 'dates', include all seqs if None
}
# class settings
n_class = 3
class_table = {
0: 'pedestrian',
1: 'cyclist',
2: 'car',
# 3: 'van',
# 4: 'truck',
}
class_ids = {
'pedestrian': 0,
'cyclist': 1,
'car': 2,
'truck': 2, # TODO: due to detection model bug
'train': 2,
'noise': -1000,
}
confmap_sigmas = {
'pedestrian': 15,
'cyclist': 20,
'car': 30,
# 'van': 12,
# 'truck': 20,
}
confmap_sigmas_interval = {
'pedestrian': [5, 15],
'cyclist': [8, 20],
'car': [10, 30],
# 'van': 12,
# 'truck': 20,
}
confmap_length = {
'pedestrian': 1,
'cyclist': 2,
'car': 3,
# 'van': 12,
# 'truck': 20,
}
object_sizes = {
'pedestrian': 0.5,
'cyclist': 1.0,
'car': 3.0,
}
# calibration
t_cl2cr = [0.35, 0, 0]
t_cl2rh = [0.11, -0.05, 0.06]
t_cl2rv = [0.21, -0.05, 0.06]
# parameter settings
camera_configs = {
'image_width': 1440,
'image_height': 1080,
'frame_rate': 30,
# 'image_folder': 'images_0',
# 'image_folder': 'images_hist_0',
'image_folder': 'images',
'time_stamp_name': 'timestamps.txt',
# 'time_stamp_name': 'timestamps_0.txt',
'frame_expo': 0,
# 'frame_expo': 40,
'start_time_name': 'start_time.txt',
}
radar_configs = {
'ramap_rsize': 128, # RAMap range size
'ramap_asize': 128, # RAMap angle size
'ramap_vsize': 128, # RAMap angle size
'frame_rate': 30,
'crop_num': 3, # crop some indices in range domain
'n_chirps': 255, # number of chirps in one frame
'sample_freq': 4e6,
'sweep_slope': 21.0017e12,
'data_type': 'RISEP', # 'RI': real + imaginary, 'AP': amplitude + phase
'ramap_rsize_label': 122, # TODO: to be updated
'ramap_asize_label': 121, # TODO: to be updated
'ra_min_label': -60, # min radar angle
'ra_max_label': 60, # max radar angle
'rr_min': 1.0, # min radar range (fixed)
'rr_max': 25.0, # max radar range (fixed)
'ra_min': -90, # min radar angle (fixed)
'ra_max': 90, # max radar angle (fixed)
'ramap_folder': 'WIN_HEATMAP',
}
# network settings
rodnet_configs = {
'data_folder': 'WIN_PROC_MAT_DATA',
# 'label_folder': 'dets_3d',
'label_folder': 'dets_refine',
'n_epoch': 100,
'batch_size': 3,
'learning_rate': 1e-5,
'lr_step': 5, # lr will decrease 10 times after lr_step epoches
'win_size': 16,
'input_rsize': 128,
'input_asize': 128,
'rr_min': 1.0, # min radar range
'rr_max': 24.0, # max radar range
'ra_min': -90.0, # min radar angle
'ra_max': 90.0, # max radar angle
'rr_min_eval': 1.0, # min radar range
'rr_max_eval': 20.0, # max radar range
'ra_min_eval': -60.0, # min radar angle
'ra_max_eval': 60.0, # max radar angle
'max_dets': 20,
'peak_thres': 0.2,
'ols_thres': 0.2,
'stacked_num': 2,
'test_stride': 8,
}
semi_loss_err_reg = {
# index unit
'level1': 30,
'level2': 60,
'level3': 80,
}
# correct error region for level 1
err_cor_reg_l1 = {
'top': 3,
'bot': 3,
}
# correct error region for level 2
err_cor_reg_l2 = {
'top': 3,
'bot': 25,
}
# correct error region for level 3
err_cor_reg_l3 = {
'top': 3,
'bot': 35,
}
# for the old data
mean1 = -5.052344347731883e-05
std1 = 0.029227407344111892
# for the new data
mean2 = -5.087775336050677e-05
std2 = 0.03159186371634542
# for the new data
mean1_rv = 0.038192792357185736
std1_rv = 0.16754211919064926
# for the new data
mean2_rv = 0.05788228918531949
std2_rv = 0.18304037677587492
# for the new data
mean1_va = 0.06261547148605366
std1_va = 0.08709724872133341
# for the new data
mean2_va = 0.09291138048788067
std2_va = 0.11100713809079792