-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathconfig.py
135 lines (114 loc) · 4.3 KB
/
config.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
from easydict import EasyDict as edict
__cfg__ = edict()
# for dataset dir
__cfg__.DATA_DIR = 'DATA_DIR/T_DATA'
__cfg__.KITTY_EVAL_SCRIPT = "kitti_eval/launch_test.sh"
__cfg__.CALIB_DIR = ''
# selected object
__cfg__.DETECT_OBJECT = 'Car' # Pedestrian/Cyclist
__cfg__.NUM_ANCHORS_PER_CELL = 2
if __cfg__.DETECT_OBJECT == 'Car':
__cfg__.MAX_POINT_NUMBER = 35
__cfg__.Z_MIN = -3
__cfg__.Z_MAX = 1
__cfg__.Y_MIN = -40
__cfg__.Y_MAX = 40
__cfg__.X_MIN = 0
__cfg__.X_MAX = 70.4
__cfg__.VOXEL_X_SIZE = 0.2
__cfg__.VOXEL_Y_SIZE = 0.2
__cfg__.VOXEL_Z_SIZE = 0.4
__cfg__.VOXEL_POINT_COUNT = 35
__cfg__.INPUT_WIDTH = int((__cfg__.X_MAX - __cfg__.X_MIN) / __cfg__.VOXEL_X_SIZE)
__cfg__.INPUT_HEIGHT = int((__cfg__.Y_MAX - __cfg__.Y_MIN) / __cfg__.VOXEL_Y_SIZE)
__cfg__.INPUT_DEPTH = int((__cfg__.Z_MAX - __cfg__.Z_MIN) / __cfg__.VOXEL_Z_SIZE)
__cfg__.LIDAR_COORD = [0, 40, 3]
__cfg__.FEATURE_RATIO = 2
__cfg__.FEATURE_WIDTH = int(__cfg__.INPUT_WIDTH / __cfg__.FEATURE_RATIO)
__cfg__.FEATURE_HEIGHT = int(__cfg__.INPUT_HEIGHT / __cfg__.FEATURE_RATIO)
else:
__cfg__.MAX_POINT_NUMBER = 45
__cfg__.Z_MIN = -3
__cfg__.Z_MAX = 1
__cfg__.Y_MIN = -20
__cfg__.Y_MAX = 20
__cfg__.X_MIN = 0
__cfg__.X_MAX = 48
__cfg__.VOXEL_X_SIZE = 0.2
__cfg__.VOXEL_Y_SIZE = 0.2
__cfg__.VOXEL_POINT_COUNT = 45
__cfg__.INPUT_WIDTH = int((__cfg__.X_MAX - __cfg__.X_MIN) / __cfg__.VOXEL_X_SIZE)
__cfg__.INPUT_HEIGHT = int((__cfg__.Y_MAX - __cfg__.Y_MIN) / __cfg__.VOXEL_Y_SIZE)
__cfg__.INPUT_DEPTH = int((__cfg__.Z_MAX - __cfg__.Z_MIN) / __cfg__.VOXEL_Z_SIZE)
__cfg__.FEATURE_RATIO = 2
__cfg__.LIDAR_COORD = [0, 20, 3]
__cfg__.FEATURE_WIDTH = int(__cfg__.INPUT_WIDTH / __cfg__.FEATURE_RATIO)
__cfg__.FEATURE_HEIGHT = int(__cfg__.INPUT_HEIGHT / __cfg__.FEATURE_RATIO)
__cfg__.SCENE_SIZE = [__cfg__.Z_MAX - __cfg__.Z_MIN, __cfg__.Y_MAX- __cfg__.Y_MIN, __cfg__.X_MAX - __cfg__.X_MIN]
__cfg__.VOXEL_SIZE = [__cfg__.VOXEL_Z_SIZE, __cfg__.VOXEL_Y_SIZE, __cfg__.VOXEL_X_SIZE]
__cfg__.GRID_SIZE = [int(A/B) for A,B in zip(__cfg__.SCENE_SIZE, __cfg__.VOXEL_SIZE)]
__cfg__.MAP_SHAPE = [__cfg__.FEATURE_HEIGHT, __cfg__.FEATURE_WIDTH]
__cfg__.IMG_WIDTH = 2048
__cfg__.IMG_HEIGHT = 618
__cfg__.IMG_CHANNEL = 3
# set the log image scale factor
__cfg__.BV_LOG_FACTOR = 4
# For the VFE layer
__cfg__.VFE_OUT_DIMS = [32,128]
__cfg__.VFE_FINAl_OUT_DIM = 128
# # cal mean from train set
# __cfg__.MATRIX_P2 = ([[719.787081, 0., 608.463003, 44.9538775],
# [0., 719.787081, 174.545111, 0.1066855],
# [0., 0., 1., 3.0106472e-03],
# [0., 0., 0., 0]])
# # cal mean from train set
# __cfg__.MATRIX_T_VELO_2_CAM = ([
# [7.49916597e-03, -9.99971248e-01, -8.65110297e-04, -6.71807577e-03],
# [1.18652889e-02, 9.54520517e-04, -9.99910318e-01, -7.33152811e-02],
# [9.99882833e-01, 7.49141178e-03, 1.18719929e-02, -2.78557062e-01],
# [0, 0, 0, 1]
# ])
# # cal mean from train set
# __cfg__.MATRIX_R_RECT_0 = ([
# [0.99992475, 0.00975976, -0.00734152, 0],
# [-0.0097913, 0.99994262, -0.00430371, 0],
# [0.00729911, 0.0043753, 0.99996319, 0],
# [0, 0, 0, 1]
# ])
__cfg__.MATRIX_R_RECT_0 = ([
[1, 0, 0, 0],
[0, 1, 0, 0],
[0, 0, 1, 0],
[0, 0, 0, 1]
])
# Faster-RCNN/SSD Hyper params
if __cfg__.DETECT_OBJECT == 'Car':
# car anchor
__cfg__.ANCHOR_L = 3.9
__cfg__.ANCHOR_W = 1.6
__cfg__.ANCHOR_H = 1.56
__cfg__.ANCHOR_Z = -1.0 - __cfg__.ANCHOR_H/2
__cfg__.RPN_POS_IOU = 0.6
__cfg__.RPN_NEG_IOU = 0.45
elif __cfg__.DETECT_OBJECT == 'Pedestrian':
# pedestrian anchor
__cfg__.ANCHOR_L = 0.8
__cfg__.ANCHOR_W = 0.6
__cfg__.ANCHOR_H = 1.73
__cfg__.ANCHOR_Z = -0.6 - __cfg__.ANCHOR_H/2
__cfg__.RPN_POS_IOU = 0.5
__cfg__.RPN_NEG_IOU = 0.35
if __cfg__.DETECT_OBJECT == 'Cyclist':
# cyclist anchor
__cfg__.ANCHOR_L = 1.76
__cfg__.ANCHOR_W = 0.6
__cfg__.ANCHOR_H = 1.73
__cfg__.ANCHOR_Z = -0.6 - __cfg__.ANCHOR_H/2
__cfg__.RPN_POS_IOU = 0.5
__cfg__.RPN_NEG_IOU = 0.35
# for rpn nms
__cfg__.RPN_NMS_POST_TOPK = 20
__cfg__.RPN_NMS_THRESH = 0.1
__cfg__.RPN_SCORE_THRESH = 0.96
__cfg__.CORNER2CENTER_AVG = True # average version or max version
cfg = __cfg__