repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_s3dis_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.datasets import S3DISDataset, S3DISSegDataset
def test_getitem():
np.random.seed(0)
root_path = './tests/data/s3dis/'
ann_file = './tests/data/s3dis/s3dis_infos.pkl'
class_names = ('table', 'cha... | 13,524 | 37.864943 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_sunrgbd_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.datasets import SUNRGBDDataset
def _generate_sunrgbd_dataset_config():
root_path = './tests/data/sunrgbd'
ann_file = './tests/data/sunrgbd/sunrgbd_infos.pkl'
class_names = ('bed', 'table', 'sofa', '... | 13,290 | 40.534375 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_nuscene_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import tempfile
import torch
from mmdet3d.datasets import NuScenesDataset
def test_getitem():
np.random.seed(0)
point_cloud_range = [-50, -50, -5, 50, 50, 3]
file_client_args = dict(backend='disk')
class_names = [
'car', 'truc... | 4,308 | 35.82906 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_lyft_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import tempfile
import torch
from mmdet3d.datasets import LyftDataset
def test_getitem():
np.random.seed(0)
torch.manual_seed(0)
root_path = './tests/data/lyft'
ann_file = './tests/data/lyft/lyft_infos.pkl'
class_names... | 7,590 | 43.652941 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_pipelines/test_outdoor_pipeline.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.bbox import LiDARInstance3DBoxes
from mmdet3d.datasets.pipelines import Compose
def test_outdoor_aug_pipeline():
point_cloud_range = [0, -40, -3, 70.4, 40, 1]
class_names = ['Car']
np.random.seed(0)
tra... | 10,243 | 39.650794 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_pipelines/test_indoor_pipeline.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import torch
from os import path as osp
from mmdet3d.core.bbox import DepthInstance3DBoxes
from mmdet3d.datasets.pipelines import Compose
def test_scannet_pipeline():
class_names = ('cabinet', 'bed', 'chair', 'sofa', 'table', 'door',
... | 12,922 | 38.519878 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_pipelines/test_augmentations/test_transforms_3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pytest
import torch
from mmdet3d.core import (Box3DMode, CameraInstance3DBoxes,
DepthInstance3DBoxes, LiDARInstance3DBoxes)
from mmdet3d.core.bbox import Coord3DMode
from mmdet3d.core.points import DepthPoin... | 31,331 | 40.554377 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_pipelines/test_augmentations/test_test_augment_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.points import DepthPoints
from mmdet3d.datasets.pipelines import MultiScaleFlipAug3D
def test_multi_scale_flip_aug_3D():
np.random.seed(0)
transforms = [{
'type': 'GlobalRotScaleTrans',
'rot_rang... | 2,269 | 35.031746 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_pipelines/test_loadings/test_load_images_from_multi_views.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmcv.parallel import DataContainer
from mmdet3d.datasets.pipelines import (DefaultFormatBundle,
LoadMultiViewImageFromFiles)
def test_load_multi_view_image_from_files():
multi_view_img_loa... | 1,768 | 36.638298 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_assigners.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Tests the Assigner objects.
CommandLine:
pytest tests/test_utils/test_assigner.py
xdoctest tests/test_utils/test_assigner.py zero
"""
import torch
from mmdet3d.core.bbox.assigners import MaxIoUAssigner
def test_max_iou_assigner():
self = MaxIoUAssigner(... | 4,301 | 27.490066 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_samplers.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.core.bbox.assigners import MaxIoUAssigner
from mmdet3d.core.bbox.samplers import IoUNegPiecewiseSampler
def test_iou_piecewise_sampler():
if not torch.cuda.is_available():
pytest.skip()
assigner = MaxIoUAssigner(
... | 1,732 | 37.511111 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_nms.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
def test_aligned_3d_nms():
from mmdet3d.core.post_processing import aligned_3d_nms
boxes = torch.tensor([[1.2261, 0.6679, -1.2678, 2.6547, 1.0428, 0.1000],
[5.0919, 0.6512, 0.7238, 5.4821, 1.2451, 2.1095... | 4,077 | 52.657895 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_bbox_coders.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.core.bbox import DepthInstance3DBoxes, LiDARInstance3DBoxes
from mmdet.core import build_bbox_coder
def test_partial_bin_based_box_coder():
box_coder_cfg = dict(
type='PartialBinBasedBBoxCoder',
num_sizes=10,
num_di... | 17,332 | 47.825352 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_points.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.points import (BasePoints, CameraPoints, DepthPoints,
LiDARPoints)
def test_base_points():
# test empty initialization
empty_boxes = []
points = BasePoints(empt... | 50,955 | 45.450319 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_coord_3d_mode.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.bbox import (CameraInstance3DBoxes, Coord3DMode,
DepthInstance3DBoxes, LiDARInstance3DBoxes)
from mmdet3d.core.points import CameraPoints, DepthPoints, LiDARPoints
def test_points_conversi... | 15,980 | 49.572785 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_box3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
import unittest
from mmdet3d.core.bbox import (BaseInstance3DBoxes, Box3DMode,
CameraInstance3DBoxes, DepthInstance3DBoxes,
LiDARInstance3DBoxes, bbox3d2roi,
... | 64,168 | 47.356443 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_merge_augs.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import pytest
import torch
from mmdet3d.core import merge_aug_bboxes_3d
from mmdet3d.core.bbox import DepthInstance3DBoxes
def test_merge_aug_bboxes_3d():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
img_... | 2,603 | 40.333333 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_anchors.py | # Copyright (c) OpenMMLab. All rights reserved.
"""
CommandLine:
pytest tests/test_utils/test_anchor.py
xdoctest tests/test_utils/test_anchor.py zero
"""
import torch
from mmdet3d.core.anchor import build_prior_generator
def test_anchor_3d_range_generator():
if torch.cuda.is_available():
device ... | 9,343 | 37.933333 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_utils/test_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.core import draw_heatmap_gaussian
def test_gaussian():
heatmap = torch.zeros((128, 128))
ct_int = torch.tensor([64, 64], dtype=torch.int32)
radius = 2
draw_heatmap_gaussian(heatmap, ct_int, radius)
assert torch.isclose(torc... | 369 | 27.461538 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_metrics/test_kitti_eval.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.evaluation.kitti_utils.eval import (do_eval, eval_class,
kitti_eval)
def test_do_eval():
if not torch.cuda.is_available():
pytest.skip('tes... | 12,056 | 48.413934 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_metrics/test_losses.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from torch import nn as nn
def test_chamfer_disrance():
from mmdet3d.models.losses import ChamferDistance, chamfer_distance
with pytest.raises(AssertionError):
# test invalid mode
ChamferDistance(mode='smoothl1')
... | 4,738 | 41.3125 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_metrics/test_seg_eval.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.evaluation.seg_eval import seg_eval
def test_indoor_eval():
if not torch.cuda.is_available():
pytest.skip()
seg_preds = [
torch.Tensor([
0, 0, 1, 0, 0, 2, 1, 3, 1, 2, 1,... | 1,086 | 26.175 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_metrics/test_indoor_eval.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.evaluation.indoor_eval import average_precision, indoor_eval
def test_indoor_eval():
if not torch.cuda.is_available():
pytest.skip()
from mmdet3d.core.bbox.structures import Box3DMode, Dept... | 6,630 | 34.084656 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdet4d/bevdet4d-r50.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,966 | 35.509158 | 91 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/fcos3d/fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d_finetune.py | _base_ = './fcos3d_r101_caffe_fpn_gn-head_dcn_2x8_1x_nus-mono3d.py'
# model settings
model = dict(
train_cfg=dict(
code_weight=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.05, 0.05]))
# optimizer
optimizer = dict(lr=0.001)
load_from = 'work_dirs/fcos3d_nus/latest.pth'
| 274 | 29.555556 | 69 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py | _base_ = [
'../_base_/datasets/sunrgbd-3d-10class.py',
'../_base_/schedules/schedule_3x.py', '../_base_/default_runtime.py',
'../_base_/models/imvotenet_image.py'
]
class_names = ('bed', 'table', 'sofa', 'chair', 'toilet', 'desk', 'dresser',
'night_stand', 'bookshelf', 'bathtub')
# use caff... | 9,238 | 34.398467 | 225 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py | _base_ = [
'../_base_/datasets/sunrgbd-3d-10class.py', '../_base_/default_runtime.py',
'../_base_/models/imvotenet_image.py'
]
# use caffe img_norm
img_norm_cfg = dict(
mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type... | 1,986 | 32.677966 | 227 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/mask_rcnn_r50_caffe_fpn_1x_nuim.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/nuim_instance.py',
'../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(norm_cfg=dict(requires_grad=False), style='caffe'),... | 1,636 | 33.829787 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/nuim_instance.py',
'../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(norm_cfg=dict(requires_grad=False), style='caffe'),... | 1,945 | 35.716981 | 227 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py | _base_ = [
'../_base_/models/mask_rcnn_r50_fpn.py',
'../_base_/datasets/nuim_instance.py',
'../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
pretrained='open-mmlab://detectron2/resnet50_caffe',
backbone=dict(norm_cfg=dict(requires_grad=False), style='caffe'),... | 1,866 | 37.102041 | 228 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/htc_without_semantic_r50_fpn_1x_nuim.py | _base_ = [
'../_base_/datasets/nuim_instance.py',
'../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='HybridTaskCascade',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
... | 7,693 | 33.657658 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/mask_rcnn_x101_32x4d_fpn_1x_nuim.py | _base_ = './mask_rcnn_r50_fpn_1x_nuim.py'
model = dict(
pretrained='open-mmlab://resnext101_32x4d',
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN',... | 368 | 25.357143 | 53 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/mask_rcnn_r101_fpn_1x_nuim.py | _base_ = './mask_rcnn_r50_fpn_1x_nuim.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 119 | 39 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/cascade_mask_rcnn_r101_fpn_1x_nuim.py | _base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py'
model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))
| 127 | 41.666667 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim.py | _base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py'
model = dict(
pretrained='open-mmlab://resnext101_32x4d',
backbone=dict(
type='ResNeXt',
depth=101,
groups=32,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(ty... | 376 | 25.928571 | 53 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/nuimages/htc_x101_64x4d_fpn_dconv_c3-c5_coco-20e_16x1_20e_nuim.py | _base_ = './htc_r50_fpn_1x_nuim.py'
model = dict(
pretrained='open-mmlab://resnext101_64x4d',
backbone=dict(
type='ResNeXt',
depth=101,
groups=64,
base_width=4,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requi... | 859 | 34.833333 | 218 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py | _base_ = [
'../_base_/models/hv_pointpillars_fpn_nus.py',
'../_base_/datasets/nus-3d.py',
'../_base_/schedules/schedule_2x.py',
'../_base_/default_runtime.py',
]
# model settings
model = dict(
type='MVXFasterRCNN',
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
ar... | 793 | 30.76 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d.py | _base_ = [
'../_base_/models/hv_pointpillars_fpn_lyft.py',
'../_base_/datasets/lyft-3d.py',
'../_base_/schedules/schedule_2x.py',
'../_base_/default_runtime.py',
]
# model settings
model = dict(
type='MVXFasterRCNN',
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
... | 795 | 30.84 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_range100_2x8_2x_lyft-3d.py | _base_ = [
'../_base_/models/hv_pointpillars_fpn_range100_lyft.py',
'../_base_/datasets/range100_lyft-3d.py',
'../_base_/schedules/schedule_2x.py',
'../_base_/default_runtime.py',
]
# model settings
model = dict(
type='MVXFasterRCNN',
pts_backbone=dict(
_delete_=True,
type='NoSte... | 813 | 31.56 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py | _base_ = [
'../_base_/models/hv_pointpillars_fpn_nus.py',
'../_base_/datasets/nus-3d.py',
'../_base_/schedules/schedule_2x.py',
'../_base_/default_runtime.py',
]
# model settings
model = dict(
type='MVXFasterRCNN',
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
ar... | 744 | 28.8 | 72 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py | _base_ = ['../_base_/schedules/cosine.py', '../_base_/default_runtime.py']
# model settings
voxel_size = [0.05, 0.05, 0.1]
point_cloud_range = [0, -40, -3, 70.4, 40, 1]
model = dict(
type='DynamicMVXFasterRCNN',
img_backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indi... | 8,599 | 33.126984 | 193 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/robust_test/bevdet-r101-fcos-pretrain.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,501 | 33.552727 | 117 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/robust_test/bevdet-r50.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,346 | 34.139098 | 190 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/robust_test/bevdet-r101.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,042 | 34.18677 | 117 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/robust_test/bevdepth-r50.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 10,130 | 35.053381 | 190 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/robust_test/bevdet-r101-fcos-pretrain-coslr.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 10,337 | 33.691275 | 117 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdepth/bevdepth-r50.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,892 | 34.458781 | 190 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdepth/bevdepth-r101-fcos-pretrain.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,442 | 35.041985 | 92 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdepth/bevdepth4d-r50.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 10,596 | 36.182456 | 103 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdepth/bevdepth-r101.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,241 | 34.683398 | 92 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/_base_/models/cascade_mask_rcnn_r50_fpn.py | # model settings
model = dict(
type='CascadeRCNN',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | 6,976 | 33.711443 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/_base_/models/mask_rcnn_r50_fpn.py | # model settings
model = dict(
type='MaskRCNN',
pretrained='torchvision://resnet50',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=True,
... | 4,080 | 31.648 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/_base_/models/fcos3d.py | model = dict(
type='FCOSMono3D',
pretrained='open-mmlab://detectron2/resnet101_caffe',
backbone=dict(
type='ResNet',
depth=101,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
... | 2,279 | 29.4 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/_base_/models/imvotenet_image.py | model = dict(
type='ImVoteNet',
img_backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
style='caffe'),
img_neck=dict(
type='FPN... | 3,563 | 31.697248 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/_base_/schedules/cyclic_40e.py | # The schedule is usually used by models trained on KITTI dataset
# The learning rate set in the cyclic schedule is the initial learning rate
# rather than the max learning rate. Since the target_ratio is (10, 1e-4),
# the learning rate will change from 0.0018 to 0.018, than go to 0.0018*1e-4
lr = 0.0018
# The optimiz... | 1,572 | 48.15625 | 150 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/imvoxelnet/imvoxelnet_4x8_kitti-3d-car.py | model = dict(
type='ImVoxelNet',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=1,
norm_cfg=dict(type='BN', requires_grad=False),
norm_eval=True,
init_cfg=dict(type='Pretrained', checkpoint='torchvisio... | 5,125 | 30.838509 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py | _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
model = dict(
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
arch='regnetx_1.6gf',
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://regnetx_1.6gf'),
out_indices=(1, 2, 3),
... | 2,504 | 34.28169 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/free_anchor/hv_pointpillars_regnet-400mf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py | _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
model = dict(
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
arch='regnetx_400mf',
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://regnetx_400mf'),
out_indices=(1, 2, 3),
... | 593 | 30.263158 | 72 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py | _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
model = dict(
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
arch='regnetx_3.2gf',
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://regnetx_3.2gf'),
out_indices=(1, 2, 3),
... | 2,503 | 34.267606 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py | _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
model = dict(
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
arch='regnetx_1.6gf',
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://regnetx_1.6gf'),
out_indices=(1, 2, 3),
... | 594 | 30.315789 | 72 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py | _base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'
model = dict(
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
arch='regnetx_3.2gf',
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://regnetx_3.2gf'),
out_indices=(1, 2, 3),
... | 595 | 30.368421 | 72 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdet/bevdet-r101-fcos-pretrain-cbgs-coslr.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,288 | 33.025641 | 92 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdet/bevdet-r101-fcos-pretrain.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,158 | 33.562264 | 92 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdet/bevdet-r50.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,133 | 33.598485 | 190 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdet/bevdet-r101-dcn-wo-pretrain.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,295 | 33.051282 | 92 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/bevdet/bevdet-r101.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 8,836 | 33.654902 | 92 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d.py | _base_ = './hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d.py'
# model settings
model = dict(
type='MVXFasterRCNN',
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
arch=dict(w0=24, wa=24.48, wm=2.54, group_w=16, depth=22, bot_mul=1.0),
init_cfg=dict(
type='Pretrained', c... | 668 | 32.45 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_1x16_2x_lyft-3d.py | _base_ = './hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py'
# model settings
model = dict(
type='MVXFasterRCNN',
pts_backbone=dict(
_delete_=True,
type='NoStemRegNet',
arch=dict(w0=24, wa=24.48, wm=2.54, group_w=16, depth=22, bot_mul=1.0),
init_cfg=dict(
type='Pretrained', ... | 738 | 32.590909 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/docs/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 6,403 | 31.02 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/apis/inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import re
import torch
from copy import deepcopy
from mmcv.parallel import collate, scatter
from mmcv.runner import load_checkpoint
from os import path as osp
from mmdet3d.core import (Box3DMode, CameraInstance3DBoxes,
... | 16,723 | 33.0611 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/apis/test.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch
from mmcv.image import tensor2imgs
from os import path as osp
from mmdet3d.models import (Base3DDetector, Base3DSegmentor,
SingleStageMono3DDetector)
def single_gpu_test(model,
data_loader,
... | 3,108 | 35.576471 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/evaluation/seg_eval.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
from mmcv.utils import print_log
from terminaltables import AsciiTable
def fast_hist(preds, labels, num_classes):
"""Compute the confusion matrix for every batch.
Args:
preds (np.ndarray): Prediction labels of points with shape of
... | 3,743 | 27.363636 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/evaluation/indoor_eval.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmcv.utils import print_log
from terminaltables import AsciiTable
def average_precision(recalls, precisions, mode='area'):
"""Calculate average precision (for single or multiple scales).
Args:
recalls (np.ndarray): R... | 11,085 | 34.646302 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/evaluation/kitti_utils/rotate_iou.py | # Copyright (c) OpenMMLab. All rights reserved.
#####################
# Based on https://github.com/hongzhenwang/RRPN-revise
# Licensed under The MIT License
# Author: yanyan, scrin@foxmail.com
#####################
import math
import numba
import numpy as np
from numba import cuda
@numba.jit(nopython=True)
def div_u... | 13,315 | 34.042105 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/post_processing/merge_augs.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.ops.iou3d.iou3d_utils import nms_gpu, nms_normal_gpu
from ..bbox import bbox3d2result, bbox3d_mapping_back, xywhr2xyxyr
def merge_aug_bboxes_3d(aug_results, img_metas, test_cfg):
"""Merge augmented detection 3D bboxes and scores.
Args... | 3,495 | 36.591398 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/post_processing/box3d_nms.py | # Copyright (c) OpenMMLab. All rights reserved.
import numba
import numpy as np
import torch
from mmdet3d.ops.iou3d.iou3d_utils import nms_gpu, nms_normal_gpu
def box3d_multiclass_nms(mlvl_bboxes,
mlvl_bboxes_for_nms,
mlvl_scores,
score_thr,
... | 8,007 | 35.235294 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/box_np_ops.py | # Copyright (c) OpenMMLab. All rights reserved.
# TODO: clean the functions in this file and move the APIs into box structures
# in the future
import numba
import numpy as np
def camera_to_lidar(points, r_rect, velo2cam):
"""Convert points in camera coordinate to lidar coordinate.
Args:
points (np.n... | 33,537 | 36.389075 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/transforms.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
def bbox3d_mapping_back(bboxes, scale_factor, flip_horizontal, flip_vertical):
"""Map bboxes from testing scale to original image scale.
Args:
bboxes (:obj:`BaseInstance3DBoxes`): Boxes to be mapped back.
scale_factor (float): Scale... | 2,414 | 30.363636 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/iou_calculators/iou3d_calculator.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet.core.bbox import bbox_overlaps
from mmdet.core.bbox.iou_calculators.builder import IOU_CALCULATORS
from ..structures import get_box_type
@IOU_CALCULATORS.register_module()
class BboxOverlapsNearest3D(object):
"""Nearest 3D IoU Calculator.
... | 12,522 | 37.891304 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/samplers/iou_neg_piecewise_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet.core.bbox.builder import BBOX_SAMPLERS
from . import RandomSampler, SamplingResult
@BBOX_SAMPLERS.register_module()
class IoUNegPiecewiseSampler(RandomSampler):
"""IoU Piece-wise Sampling.
Sampling negtive proposals according to a list ... | 6,861 | 42.157233 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/coders/anchor_free_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet.core.bbox.builder import BBOX_CODERS
from .partial_bin_based_bbox_coder import PartialBinBasedBBoxCoder
@BBOX_CODERS.register_module()
class AnchorFreeBBoxCoder(PartialBinBasedBBoxCoder):
"""Anchor free bbox coder for 3D b... | 4,367 | 32.343511 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/coders/groupfree3d_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet.core.bbox.builder import BBOX_CODERS
from .partial_bin_based_bbox_coder import PartialBinBasedBBoxCoder
@BBOX_CODERS.register_module()
class GroupFree3DBBoxCoder(PartialBinBasedBBoxCoder):
"""Modified partial bin based bbo... | 7,202 | 36.712042 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/coders/delta_xyzwhlr_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet.core.bbox import BaseBBoxCoder
from mmdet.core.bbox.builder import BBOX_CODERS
@BBOX_CODERS.register_module()
class DeltaXYZWLHRBBoxCoder(BaseBBoxCoder):
"""Bbox Coder for 3D boxes.
Args:
code_size (int): The dimension of boxes ... | 3,122 | 32.945652 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/coders/centerpoint_bbox_coders.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet.core.bbox import BaseBBoxCoder
from mmdet.core.bbox.builder import BBOX_CODERS
@BBOX_CODERS.register_module()
class CenterPointBBoxCoder(BaseBBoxCoder):
"""Bbox coder for CenterPoint.
Args:
pc_range (list[float]): Range of point... | 8,591 | 36.519651 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/coders/partial_bin_based_bbox_coder.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet.core.bbox import BaseBBoxCoder
from mmdet.core.bbox.builder import BBOX_CODERS
@BBOX_CODERS.register_module()
class PartialBinBasedBBoxCoder(BaseBBoxCoder):
"""Partial bin based bbox coder.
Args:
num_dir_bins ... | 9,146 | 36.797521 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/structures/depth_box3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.points import BasePoints
from mmdet3d.ops import points_in_boxes_batch
from .base_box3d import BaseInstance3DBoxes
from .utils import limit_period, rotation_3d_in_axis
class DepthInstance3DBoxes(BaseInstance3DBoxes):
... | 13,666 | 38.729651 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/structures/cam_box3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.points import BasePoints
from .base_box3d import BaseInstance3DBoxes
from .utils import limit_period, rotation_3d_in_axis
class CameraInstance3DBoxes(BaseInstance3DBoxes):
"""3D boxes of instances in CAM coordinates... | 12,716 | 38.129231 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/structures/base_box3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from abc import abstractmethod
from mmdet3d.ops.iou3d import iou3d_cuda
from .utils import limit_period, xywhr2xyxyr
class BaseInstance3DBoxes(object):
"""Base class for 3D Boxes.
Note:
The box is bottom centered, i.e. t... | 16,502 | 34.720779 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/structures/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from logging import warning
def limit_period(val, offset=0.5, period=np.pi):
"""Limit the value into a period for periodic function.
Args:
val (torch.Tensor): The value to be converted.
offset (float, optional): O... | 7,682 | 34.734884 | 131 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/structures/box_3d_mode.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from enum import IntEnum, unique
from .base_box3d import BaseInstance3DBoxes
from .cam_box3d import CameraInstance3DBoxes
from .depth_box3d import DepthInstance3DBoxes
from .lidar_box3d import LiDARInstance3DBoxes
@unique
class Box3DMode... | 6,034 | 35.137725 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/structures/lidar_box3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.points import BasePoints
from mmdet3d.ops.roiaware_pool3d import points_in_boxes_gpu
from .base_box3d import BaseInstance3DBoxes
from .utils import limit_period, rotation_3d_in_axis
class LiDARInstance3DBoxes(BaseInstan... | 10,528 | 37.852399 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/bbox/structures/coord_3d_mode.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from enum import IntEnum, unique
from mmdet3d.core.points import (BasePoints, CameraPoints, DepthPoints,
LiDARPoints)
from .base_box3d import BaseInstance3DBoxes
from .cam_box3d import CameraInstance3DBoxes... | 10,929 | 37.758865 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/points/cam_points.py | # Copyright (c) OpenMMLab. All rights reserved.
from .base_points import BasePoints
class CameraPoints(BasePoints):
"""Points of instances in CAM coordinates.
Args:
tensor (torch.Tensor | np.ndarray | list): a N x points_dim matrix.
points_dim (int): Number of the dimension of a point.
... | 2,866 | 39.380282 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/points/base_points.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
import warnings
from abc import abstractmethod
class BasePoints(object):
"""Base class for Points.
Args:
tensor (torch.Tensor | np.ndarray | list): a N x points_dim matrix.
points_dim (int): Number of the dimensio... | 16,655 | 37.114416 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/points/lidar_points.py | # Copyright (c) OpenMMLab. All rights reserved.
from .base_points import BasePoints
class LiDARPoints(BasePoints):
"""Points of instances in LIDAR coordinates.
Args:
tensor (torch.Tensor | np.ndarray | list): a N x points_dim matrix.
points_dim (int): Number of the dimension of a point.
... | 2,868 | 39.408451 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/points/depth_points.py | # Copyright (c) OpenMMLab. All rights reserved.
from .base_points import BasePoints
class DepthPoints(BasePoints):
"""Points of instances in DEPTH coordinates.
Args:
tensor (torch.Tensor | np.ndarray | list): a N x points_dim matrix.
points_dim (int): Number of the dimension of a point.
... | 2,868 | 39.408451 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/utils/gaussian.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
def gaussian_2d(shape, sigma=1):
"""Generate gaussian map.
Args:
shape (list[int]): Shape of the map.
sigma (float): Sigma to generate gaussian map.
Defaults to 1.
Returns:
np.ndarray: Gen... | 2,538 | 28.183908 | 74 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/visualizer/open3d_vis.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import torch
try:
import open3d as o3d
from open3d import geometry
except ImportError:
raise ImportError(
'Please run "pip install open3d" to install open3d first.')
def _draw_points(points,
vis,
... | 17,728 | 38.93018 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/visualizer/image_vis.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import cv2
import numpy as np
import torch
from matplotlib import pyplot as plt
def project_pts_on_img(points,
raw_img,
lidar2img_rt,
max_distance=70,
thickness=-1):
... | 7,761 | 38.005025 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/mmdet3d/core/anchor/anchor_3d_generator.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch
from mmdet.core.anchor import ANCHOR_GENERATORS
@ANCHOR_GENERATORS.register_module()
class Anchor3DRangeGenerator(object):
"""3D Anchor Generator by range.
This anchor generator generates anchors by the given range in different
fea... | 17,177 | 41.414815 | 79 | py |
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