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Unverified Commit 7f977ea3 authored by Au1ong's avatar Au1ong Committed by GitHub
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Add pyramid data augmentation which mentioned in SE-SSD (#751) 



* add pyramid augmentation

* add pyramid augmentation

* format the modified file
Co-authored-by: default avatarShaoshuai Shi <shaoshuaics@gmail.com>
parent a991105c
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Showing with 506 additions and 100 deletions
pcdet/datasets/augmentor/augmentor_utils.py
View file @ 7f977ea3
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pcdet/datasets/augmentor/data_augmentor.py
View file @ 7f977ea3
......@@ -11,18 +11,18 @@ class DataAugmentor(object):
self.root_path = root_path
self.class_names = class_names
self.logger = logger
self.data_augmentor_queue = []
aug_config_list = augmentor_configs if isinstance(augmentor_configs, list) \
else augmentor_configs.AUG_CONFIG_LIST
for cur_cfg in aug_config_list:
if not isinstance(augmentor_configs, list):
if cur_cfg.NAME in augmentor_configs.DISABLE_AUG_LIST:
continue
cur_augmentor = getattr(self, cur_cfg.NAME)(config=cur_cfg)
self.data_augmentor_queue.append(cur_augmentor)
def gt_sampling(self, config=None):
db_sampler = database_sampler.DataBaseSampler(
root_path=self.root_path,
......@@ -31,15 +31,15 @@ class DataAugmentor(object):
logger=self.logger
)
return db_sampler
def __getstate__(self):
d = dict(self.__dict__)
del d['logger']
return d
def __setstate__(self, d):
self.__dict__.update(d)
def random_world_flip(self, data_dict=None, config=None):
if data_dict is None:
return partial(self.random_world_flip, config=config)
......@@ -49,11 +49,11 @@ class DataAugmentor(object):
gt_boxes, points = getattr(augmentor_utils, 'random_flip_along_%s' % cur_axis)(
gt_boxes, points,
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_world_rotation(self, data_dict=None, config=None):
if data_dict is None:
return partial(self.random_world_rotation, config=config)
......@@ -63,22 +63,22 @@ class DataAugmentor(object):
gt_boxes, points = augmentor_utils.global_rotation(
data_dict['gt_boxes'], data_dict['points'], rot_range=rot_range
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_world_scaling(self, data_dict=None, config=None):
if data_dict is None:
return partial(self.random_world_scaling, config=config)
gt_boxes, points = augmentor_utils.global_scaling(
data_dict['gt_boxes'], data_dict['points'], config['WORLD_SCALE_RANGE']
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_image_flip(self, data_dict=None, config=None):
if data_dict is None:
return partial(self.random_image_flip, config=config)
......@@ -92,12 +92,12 @@ class DataAugmentor(object):
images, depth_maps, gt_boxes = getattr(augmentor_utils, 'random_image_flip_%s' % cur_axis)(
images, depth_maps, gt_boxes, calib,
)
data_dict['images'] = images
data_dict['depth_maps'] = depth_maps
data_dict['gt_boxes'] = gt_boxes
return data_dict
def random_world_translation(self, data_dict=None, config=None):
"""
Please check the correctness of it before using.
......@@ -111,11 +111,11 @@ class DataAugmentor(object):
gt_boxes, points = getattr(augmentor_utils, 'random_translation_along_%s' % cur_axis)(
gt_boxes, points, offset_range,
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_local_translation(self, data_dict=None, config=None):
"""
Please check the correctness of it before using.
......@@ -129,11 +129,11 @@ class DataAugmentor(object):
gt_boxes, points = getattr(augmentor_utils, 'random_local_translation_along_%s' % cur_axis)(
gt_boxes, points, offset_range,
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_local_rotation(self, data_dict=None, config=None):
"""
Please check the correctness of it before using.
......@@ -146,11 +146,11 @@ class DataAugmentor(object):
gt_boxes, points = augmentor_utils.local_rotation(
data_dict['gt_boxes'], data_dict['points'], rot_range=rot_range
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_local_scaling(self, data_dict=None, config=None):
"""
Please check the correctness of it before using.
......@@ -160,18 +160,18 @@ class DataAugmentor(object):
gt_boxes, points = augmentor_utils.local_scaling(
data_dict['gt_boxes'], data_dict['points'], config['LOCAL_SCALE_RANGE']
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_world_frustum_dropout(self, data_dict=None, config=None):
"""
Please check the correctness of it before using.
"""
if data_dict is None:
return partial(self.random_world_frustum_dropout, config=config)
intensity_range = config['INTENSITY_RANGE']
gt_boxes, points = data_dict['gt_boxes'], data_dict['points']
for direction in config['DIRECTION']:
......@@ -179,18 +179,18 @@ class DataAugmentor(object):
gt_boxes, points = getattr(augmentor_utils, 'global_frustum_dropout_%s' % direction)(
gt_boxes, points, intensity_range,
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_local_frustum_dropout(self, data_dict=None, config=None):
"""
Please check the correctness of it before using.
"""
if data_dict is None:
return partial(self.random_local_frustum_dropout, config=config)
intensity_range = config['INTENSITY_RANGE']
gt_boxes, points = data_dict['gt_boxes'], data_dict['points']
for direction in config['DIRECTION']:
......@@ -198,11 +198,34 @@ class DataAugmentor(object):
gt_boxes, points = getattr(augmentor_utils, 'local_frustum_dropout_%s' % direction)(
gt_boxes, points, intensity_range,
)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def random_local_pyramid_aug(self, data_dict=None, config=None):
"""
Refer to the paper:
SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud
"""
if data_dict is None:
return partial(self.random_local_pyramid_aug, config=config)
gt_boxes, points = data_dict['gt_boxes'], data_dict['points']
gt_boxes, points, pyramids = augmentor_utils.local_pyramid_dropout(gt_boxes, points, config['DROP_PROB'])
gt_boxes, points, pyramids = augmentor_utils.local_pyramid_sparsify(gt_boxes, points,
config['SPARSIFY_PROB'],
config['SPARSIFY_MAX_NUM'],
pyramids)
gt_boxes, points = augmentor_utils.local_pyramid_swap(gt_boxes, points,
config['SWAP_PROB'],
config['SWAP_MAX_NUM'],
pyramids)
data_dict['gt_boxes'] = gt_boxes
data_dict['points'] = points
return data_dict
def forward(self, data_dict):
"""
Args:
......@@ -216,7 +239,7 @@ class DataAugmentor(object):
"""
for cur_augmentor in self.data_augmentor_queue:
data_dict = cur_augmentor(data_dict=data_dict)
data_dict['gt_boxes'][:, 6] = common_utils.limit_period(
data_dict['gt_boxes'][:, 6], offset=0.5, period=2 * np.pi
)
......@@ -230,6 +253,6 @@ class DataAugmentor(object):
data_dict['gt_names'] = data_dict['gt_names'][gt_boxes_mask]
if 'gt_boxes2d' in data_dict:
data_dict['gt_boxes2d'] = data_dict['gt_boxes2d'][gt_boxes_mask]
data_dict.pop('gt_boxes_mask')
return data_dict
\ No newline at end of file
return data_dict
tools/cfgs/kitti_models/pointpillar_pyramid_aug.yaml 0 → 100644
View file @ 7f977ea3
CLASS_NAMES: ['Car', 'Pedestrian', 'Cyclist']
DATA_CONFIG:
_BASE_CONFIG_: cfgs/dataset_configs/kitti_dataset.yaml
POINT_CLOUD_RANGE: [0, -39.68, -3, 69.12, 39.68, 1]
DATA_PROCESSOR:
- NAME: mask_points_and_boxes_outside_range
REMOVE_OUTSIDE_BOXES: True
- NAME: shuffle_points
SHUFFLE_ENABLED: {
'train': True,
'test': False
}
- NAME: transform_points_to_voxels
VOXEL_SIZE: [0.16, 0.16, 4]
MAX_POINTS_PER_VOXEL: 32
MAX_NUMBER_OF_VOXELS: {
'train': 16000,
'test': 40000
}
DATA_AUGMENTOR:
DISABLE_AUG_LIST: ['placeholder']
AUG_CONFIG_LIST:
- NAME: gt_sampling
USE_ROAD_PLANE: True
DB_INFO_PATH:
- kitti_dbinfos_train.pkl
PREPARE: {
filter_by_min_points: ['Car:5', 'Pedestrian:5', 'Cyclist:5'],
filter_by_difficulty: [-1],
}
SAMPLE_GROUPS: ['Car:15','Pedestrian:15', 'Cyclist:15']
NUM_POINT_FEATURES: 4
DATABASE_WITH_FAKELIDAR: False
REMOVE_EXTRA_WIDTH: [0.0, 0.0, 0.0]
LIMIT_WHOLE_SCENE: False
- NAME: random_world_flip
ALONG_AXIS_LIST: ['x']
- NAME: random_world_rotation
WORLD_ROT_ANGLE: [-0.78539816, 0.78539816]
- NAME: random_world_scaling
WORLD_SCALE_RANGE: [0.95, 1.05]
- NAME: random_local_pyramid_aug
DROP_PROB: 0.25
SPARSIFY_PROB: 0.05
SPARSIFY_MAX_NUM: 50
SWAP_PROB: 0.1
SWAP_MAX_NUM: 50
MODEL:
NAME: PointPillar
VFE:
NAME: PillarVFE
WITH_DISTANCE: False
USE_ABSLOTE_XYZ: True
USE_NORM: True
NUM_FILTERS: [64]
MAP_TO_BEV:
NAME: PointPillarScatter
NUM_BEV_FEATURES: 64
BACKBONE_2D:
NAME: BaseBEVBackbone
LAYER_NUMS: [3, 5, 5]
LAYER_STRIDES: [2, 2, 2]
NUM_FILTERS: [64, 128, 256]
UPSAMPLE_STRIDES: [1, 2, 4]
NUM_UPSAMPLE_FILTERS: [128, 128, 128]
DENSE_HEAD:
NAME: AnchorHeadSingle
CLASS_AGNOSTIC: False
USE_DIRECTION_CLASSIFIER: True
DIR_OFFSET: 0.78539
DIR_LIMIT_OFFSET: 0.0
NUM_DIR_BINS: 2
ANCHOR_GENERATOR_CONFIG: [
{
'class_name': 'Car',
'anchor_sizes': [[3.9, 1.6, 1.56]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-1.78],
'align_center': False,
'feature_map_stride': 2,
'matched_threshold': 0.6,
'unmatched_threshold': 0.45
},
{
'class_name': 'Pedestrian',
'anchor_sizes': [[0.8, 0.6, 1.73]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 2,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
},
{
'class_name': 'Cyclist',
'anchor_sizes': [[1.76, 0.6, 1.73]],
'anchor_rotations': [0, 1.57],
'anchor_bottom_heights': [-0.6],
'align_center': False,
'feature_map_stride': 2,
'matched_threshold': 0.5,
'unmatched_threshold': 0.35
}
]
TARGET_ASSIGNER_CONFIG:
NAME: AxisAlignedTargetAssigner
POS_FRACTION: -1.0
SAMPLE_SIZE: 512
NORM_BY_NUM_EXAMPLES: False
MATCH_HEIGHT: False
BOX_CODER: ResidualCoder
LOSS_CONFIG:
LOSS_WEIGHTS: {
'cls_weight': 1.0,
'loc_weight': 2.0,
'dir_weight': 0.2,
'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: 0.01
NMS_PRE_MAXSIZE: 4096
NMS_POST_MAXSIZE: 500
OPTIMIZATION:
BATCH_SIZE_PER_GPU: 4
NUM_EPOCHS: 80
OPTIMIZER: adam_onecycle
LR: 0.003
WEIGHT_DECAY: 0.01
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
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