-
Notifications
You must be signed in to change notification settings - Fork 71
/
voxel_rcnn_post_SN_feat_3.yaml
260 lines (214 loc) · 6.87 KB
/
voxel_rcnn_post_SN_feat_3.yaml
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
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
CLASS_NAMES: ['Vehicle']
DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/waymo/DA/da_waymo_dataset.yaml
DATA_CONFIG_TAR:
_BASE_CONFIG_: cfgs/dataset_configs/kitti/DA/da_kitti_dataset.yaml
TARGET: True
FOV_POINTS_ONLY: False
USE_PSEUDO_LABEL: True
CLASS_NAMES: ['Car']
SHIFT_COOR: [0.0, 0.0, 1.6]
DATA_AUGMENTOR:
DISABLE_AUG_LIST: [ 'placeholder' ] # Although the target domain uses the random_object_scaling data augmentation, the method is only used for PSEUDO-LABELED DATA
AUG_CONFIG_LIST:
- NAME: normalize_object_size
SIZE_RES: [ -0.91, -0.49, -0.26 ]
- NAME: random_object_rotation
ROT_PROB: 0.8
ROT_UNIFORM_NOISE: [ -0.38539816, 0.38539816 ]
- NAME: random_world_flip
ALONG_AXIS_LIST: [ 'x', 'y' ]
- NAME: random_world_rotation
WORLD_ROT_ANGLE: [ -0.78539816, 0.78539816 ]
- NAME: random_world_scaling
WORLD_SCALE_RANGE: [ 0.97, 1.03 ]
MODEL:
NAME: VoxelRCNN
VFE:
NAME: DynMeanVFE
BACKBONE_3D:
NAME: VoxelBackBone8x
MAP_TO_BEV:
NAME: HeightCompression
NUM_BEV_FEATURES: 256
BACKBONE_2D:
NAME: BaseBEVBackbone
LAYER_NUMS: [5, 5]
LAYER_STRIDES: [1, 2]
NUM_FILTERS: [128, 256]
UPSAMPLE_STRIDES: [1, 2]
NUM_UPSAMPLE_FILTERS: [256, 256]
DENSE_HEAD:
NAME: CenterHead
CLASS_AGNOSTIC: False
CLASS_NAMES_EACH_HEAD: [
[ 'Vehicle', 'Car' ]
]
SHARED_CONV_CHANNEL: 64
USE_BIAS_BEFORE_NORM: True
NUM_HM_CONV: 2
SEPARATE_HEAD_CFG:
HEAD_ORDER: [ 'center', 'center_z', 'dim', 'rot' ]
HEAD_DICT: {
'center': { 'out_channels': 2, 'num_conv': 2 },
'center_z': { 'out_channels': 1, 'num_conv': 2 },
'dim': { 'out_channels': 3, 'num_conv': 2 },
'rot': { 'out_channels': 2, 'num_conv': 2 },
}
TARGET_ASSIGNER_CONFIG:
FEATURE_MAP_STRIDE: 8
NUM_MAX_OBJS: 500
GAUSSIAN_OVERLAP: 0.1
MIN_RADIUS: 2
LOSS_CONFIG:
LOSS_WEIGHTS: {
'cls_weight': 1.0,
'loc_weight': 2.0,
'code_weights': [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ]
}
POST_PROCESSING:
SCORE_THRESH: 0.1
POST_CENTER_LIMIT_RANGE: [ -75.2, -75.2, -2, 75.2, 75.2, 4 ]
MAX_OBJ_PER_SAMPLE: 500
NMS_CONFIG:
NMS_TYPE: nms_gpu
NMS_THRESH: 0.7
NMS_PRE_MAXSIZE: 4096
NMS_POST_MAXSIZE: 500
ROI_HEAD:
NAME: VoxelRCNNHead
CLASS_AGNOSTIC: True
SHARED_FC: [256, 256]
CLS_FC: [256, 256]
REG_FC: [256, 256]
DP_RATIO: 0.3
NMS_CONFIG:
TRAIN:
NMS_TYPE: nms_gpu
MULTI_CLASSES_NMS: False
NMS_PRE_MAXSIZE: 9000
NMS_POST_MAXSIZE: 512
NMS_THRESH: 0.8
TEST:
NMS_TYPE: nms_gpu
MULTI_CLASSES_NMS: False
NMS_PRE_MAXSIZE: 1024
NMS_POST_MAXSIZE: 100
NMS_THRESH: 0.7
# NMS_PRE_MAXSIZE: 4096
# NMS_POST_MAXSIZE: 300
# NMS_THRESH: 0.85
ROI_GRID_POOL:
FEATURES_SOURCE: ['x_conv2', 'x_conv3', 'x_conv4']
PRE_MLP: True
GRID_SIZE: 6
POOL_LAYERS:
x_conv2:
MLPS: [ [ 64, 64 ] ]
QUERY_RANGES: [ [ 3, 3, 2 ] ]
POOL_RADIUS: [ 0.4 ]
NSAMPLE: [ 16 ]
POOL_METHOD: max_pool
x_conv3:
MLPS: [ [ 64, 64 ] ]
QUERY_RANGES: [ [ 3, 3, 2 ] ]
POOL_RADIUS: [ 0.8 ]
NSAMPLE: [ 16 ]
POOL_METHOD: max_pool
x_conv4:
MLPS: [ [ 64, 64 ] ]
QUERY_RANGES: [ [ 3, 3, 2 ] ]
POOL_RADIUS: [ 1.6 ]
NSAMPLE: [ 16 ]
POOL_METHOD: max_pool
TARGET_CONFIG:
BOX_CODER: ResidualCoder
ROI_PER_IMAGE: 128
FG_RATIO: 0.5
SAMPLE_ROI_BY_EACH_CLASS: True
CLS_SCORE_TYPE: roi_iou
CLS_FG_THRESH: 0.75
CLS_BG_THRESH: 0.25
CLS_BG_THRESH_LO: 0.1
HARD_BG_RATIO: 0.8
REG_FG_THRESH: 0.55
LOSS_CONFIG:
CLS_LOSS: BinaryCrossEntropy
REG_LOSS: smooth-l1
CORNER_LOSS_REGULARIZATION: True
LOSS_WEIGHTS: {
'rcnn_cls_weight': 1.0,
'rcnn_reg_weight': 1.0,
'rcnn_corner_weight': 1.0,
'code_weights': [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
}
POST_PROCESSING:
RECALL_THRESH_LIST: [0.3, 0.5, 0.7]
SCORE_THRESH: 0.1
OUTPUT_RAW_SCORE: False
EVAL_METRIC: kitti
NMS_CONFIG:
MULTI_CLASSES_NMS: False
NMS_TYPE: nms_gpu
NMS_THRESH: 0.1
NMS_PRE_MAXSIZE: 4096
NMS_POST_MAXSIZE: 500
OPTIMIZATION:
BATCH_SIZE_PER_GPU: 4
NUM_EPOCHS: 8
OPTIMIZER: adam_onecycle
LR: 0.0005
WEIGHT_DECAY: 0.001
MOMENTUM: 0.9
MOMS: [0.95, 0.85]
PCT_START: 0.4
DIV_FACTOR: 10
DECAY_STEP_LIST: [35, 45]
LR_DECAY: 0.1
LR_CLIP: 0.0000001
LR_WARMUP: False
WARMUP_EPOCH: 1
GRAD_NORM_CLIP: 10
SELF_TRAIN:
SRC:
USE_DATA: False
USE_GRAD: False
LOSS_WEIGHT: 1.0
TAR:
USE_DATA: True
LOSS_WEIGHT: 1.0
SCORE_THRESH: [0.65]
NEG_THRESH: [0.20]
UPDATE_PSEUDO_LABEL: [0, 1]
UPDATE_PSEUDO_LABEL_INTERVAL: 5
INIT_PS: None
PROG_AUG:
ENABLED: True
UPDATE_AUG: [1, 5, 10, 15]
SCALE: 1.1
D_CFG:
DISABLE_AUG_LIST: [ 'placeholder' ]
AUG_CONFIG_LIST:
- NAME: random_object_rotation
ROT_PROB: 0.8
ROT_UNIFORM_NOISE: [ -0.38539816, 0.38539816 ]
- NAME: random_world_flip
ALONG_AXIS_LIST: [ 'x', 'y' ]
- NAME: random_world_rotation
WORLD_ROT_ANGLE: [ -0.78539816, 0.78539816 ]
- NAME: random_world_scaling
WORLD_SCALE_RANGE: [ 0.97, 1.03 ]
MEMORY_ENSEMBLE:
ENABLED: False
NAME: consistency_ensemble
IOU_THRESH: 0.1
NMS_CONFIG:
NMS_TYPE: nms_gpu
MULTI_CLASSES_NMS: False
NMS_PRE_MAXSIZE: 512
NMS_POST_MAXSIZE: 100
NMS_THRESH: 0.1
MEMORY_VOTING:
ENABLED: False
IGNORE_THRESH: 2
RM_THRESH: 3