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
value |
|---|---|---|---|---|---|---|
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/.mim/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/BEVerse/mmdet3d/ops/norm.py | import torch
from mmcv.cnn import NORM_LAYERS
from mmcv.runner import force_fp32
from torch import distributed as dist
from torch import nn as nn
from torch.autograd.function import Function
class AllReduce(Function):
@staticmethod
def forward(ctx, input):
input_list = [
torch.zeros_like(... | 5,015 | 36.432836 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/sparse_block.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.cnn import build_conv_layer, build_norm_layer
from torch import nn
from mmdet3d.ops import spconv
from mmdet.models.backbones.resnet import BasicBlock, Bottleneck
class SparseBottleneck(Bottleneck, spconv.SparseModule):
"""Sparse bottleneck block for Part... | 5,952 | 30.834225 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/pointnet_modules/point_sa_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.cnn import ConvModule
from torch import nn as nn
from torch.nn import functional as F
from mmdet3d.ops import (GroupAll, PAConv, Points_Sampler, QueryAndGroup,
gather_points)
from .builder import SA_MODULES
class BasePoin... | 13,315 | 37.822157 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/pointnet_modules/point_fp_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule, force_fp32
from torch import nn as nn
from typing import List
from mmdet3d.ops import three_interpolate, three_nn
class PointFPModule(BaseModule):
"""Point feature propagation module u... | 2,811 | 34.15 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/pointnet_modules/paconv_sa_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch import nn as nn
from mmdet3d.ops import PAConv, PAConvCUDA
from .builder import SA_MODULES
from .point_sa_module import BasePointSAModule
@SA_MODULES.register_module()
class PAConvSAModuleMSG(BasePointSAModule):
r"""Point set abstraction mod... | 13,102 | 37.312865 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/group_points/group_points.py | import torch
from torch import nn as nn
from torch.autograd import Function
from typing import Tuple
from ..ball_query import ball_query
from ..knn import knn
from . import group_points_ext
class QueryAndGroup(nn.Module):
"""Query and Group.
Groups with a ball query of radius
Args:
max_radius (... | 7,898 | 33.49345 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/gather_points/gather_points.py | import torch
from torch.autograd import Function
from . import gather_points_ext
class GatherPoints(Function):
"""Gather Points.
Gather points with given index.
"""
@staticmethod
def forward(ctx, features: torch.Tensor,
indices: torch.Tensor) -> torch.Tensor:
"""forward.... | 1,541 | 28.09434 | 74 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/bev_pool/bev_pool.py | import torch
from . import bev_pool_ext
__all__ = ["bev_pool"]
class QuickCumsum(torch.autograd.Function):
@staticmethod
def forward(ctx, x, geom_feats, ranks):
x = x.cumsum(0)
kept = torch.ones(x.shape[0], device=x.device, dtype=torch.bool)
kept[:-1] = ranks[1:] != ranks[:-1]
... | 2,638 | 25.928571 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/voxel/voxelize.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from .voxel_layer import dynamic_voxelize, hard_voxelize
class _Voxelization(Function):
@staticmethod
def forward(ctx,
... | 6,502 | 42.644295 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/voxel/scatter_points.py | import torch
from torch import nn
from torch.autograd import Function
from .voxel_layer import (dynamic_point_to_voxel_backward,
dynamic_point_to_voxel_forward)
class _dynamic_scatter(Function):
@staticmethod
def forward(ctx, feats, coors, reduce_type='max'):
"""convert kit... | 4,237 | 38.240741 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/knn/knn.py | import torch
from torch.autograd import Function
from . import knn_ext
class KNN(Function):
r"""KNN (CUDA) based on heap data structure.
Modified from `PAConv <https://github.com/CVMI-Lab/PAConv/tree/main/
scene_seg/lib/pointops/src/knnquery_heap>`_.
Find k-nearest points.
"""
@staticmethod... | 2,353 | 31.246575 | 75 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/furthest_point_sample/utils.py | import torch
def calc_square_dist(point_feat_a, point_feat_b, norm=True):
"""Calculating square distance between a and b.
Args:
point_feat_a (Tensor): (B, N, C) Feature vector of each point.
point_feat_b (Tensor): (B, M, C) Feature vector of each point.
norm (Bool): Whether to normali... | 1,051 | 31.875 | 70 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/furthest_point_sample/points_sampler.py | import torch
from mmcv.runner import force_fp32
from torch import nn as nn
from typing import List
from .furthest_point_sample import (furthest_point_sample,
furthest_point_sample_with_dist)
from .utils import calc_square_dist
def get_sampler_type(sampler_type):
"""Get the typ... | 5,371 | 32.786164 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/furthest_point_sample/furthest_point_sample.py | import torch
from torch.autograd import Function
from . import furthest_point_sample_ext
class FurthestPointSampling(Function):
"""Furthest Point Sampling.
Uses iterative furthest point sampling to select a set of features whose
corresponding points have the furthest distance.
"""
@staticmethod... | 2,381 | 29.151899 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/iou3d/iou3d_utils.py | import torch
from . import iou3d_cuda
def boxes_iou_bev(boxes_a, boxes_b):
"""Calculate boxes IoU in the bird view.
Args:
boxes_a (torch.Tensor): Input boxes a with shape (M, 5).
boxes_b (torch.Tensor): Input boxes b with shape (N, 5).
Returns:
ans_iou (torch.Tensor): IoU result... | 2,289 | 30.805556 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/interpolate/three_interpolate.py | import torch
from torch.autograd import Function
from typing import Tuple
from . import interpolate_ext
class ThreeInterpolate(Function):
@staticmethod
def forward(ctx, features: torch.Tensor, indices: torch.Tensor,
weight: torch.Tensor) -> torch.Tensor:
"""Performs weighted linear i... | 2,144 | 32.515625 | 74 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/interpolate/three_nn.py | import torch
from torch.autograd import Function
from typing import Tuple
from . import interpolate_ext
class ThreeNN(Function):
@staticmethod
def forward(ctx, target: torch.Tensor,
source: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]:
"""Find the top-3 nearest neighbors of the... | 1,296 | 27.195652 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/paconv/utils.py | import torch
def calc_euclidian_dist(xyz1, xyz2):
"""Calculate the Euclidian distance between two sets of points.
Args:
xyz1 (torch.Tensor): (N, 3), the first set of points.
xyz2 (torch.Tensor): (N, 3), the second set of points.
Returns:
torch.Tensor: (N, ), the Euclidian distanc... | 3,677 | 41.275862 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/paconv/assign_score.py | from torch.autograd import Function
from . import assign_score_withk_ext
class AssignScoreWithK(Function):
r"""Perform weighted sum to generate output features according to scores.
Modified from `PAConv <https://github.com/CVMI-Lab/PAConv/tree/main/
scene_seg/lib/paconv_lib/src/gpu>`_.
This is a mem... | 4,015 | 38.372549 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/paconv/paconv.py | import copy
import torch
from mmcv.cnn import (ConvModule, build_activation_layer, build_norm_layer,
constant_init)
from torch import nn as nn
from torch.nn import functional as F
from .assign_score import assign_score_withk as assign_score_cuda
from .utils import assign_kernel_withoutk, assign_s... | 15,868 | 39.585678 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/spconv/structure.py | import numpy as np
import torch
def scatter_nd(indices, updates, shape):
"""pytorch edition of tensorflow scatter_nd.
this function don't contain except handle code. so use this carefully when
indice repeats, don't support repeat add which is supported in tensorflow.
"""
ret = torch.zeros(*shape,... | 2,187 | 30.257143 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/spconv/modules.py | # Copyright 2019 Yan Yan
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... | 6,999 | 33.482759 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/spconv/functional.py | # Copyright 2019 Yan Yan
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... | 3,699 | 36.373737 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/spconv/ops.py | # Copyright 2019 Yan Yan
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... | 7,236 | 38.331522 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/spconv/conv.py | # Copyright 2019 Yan Yan
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... | 14,355 | 30.482456 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/roiaware_pool3d/roiaware_pool3d.py | import mmcv
import torch
from torch import nn as nn
from torch.autograd import Function
from . import roiaware_pool3d_ext
class RoIAwarePool3d(nn.Module):
def __init__(self, out_size, max_pts_per_voxel=128, mode='max'):
super().__init__()
"""RoIAwarePool3d module
Args:
out_s... | 3,668 | 32.054054 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/roiaware_pool3d/points_in_boxes.py | import torch
from . import roiaware_pool3d_ext
def points_in_boxes_gpu(points, boxes):
"""Find points that are in boxes (CUDA)
Args:
points (torch.Tensor): [B, M, 3], [x, y, z] in LiDAR coordinate
boxes (torch.Tensor): [B, T, 7],
num_valid_boxes <= T, [x, y, z, w, l, h, ry] in Li... | 4,690 | 36.830645 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/mmdet3d/ops/ball_query/ball_query.py | import torch
from torch.autograd import Function
from . import ball_query_ext
class BallQuery(Function):
"""Ball Query.
Find nearby points in spherical space.
"""
@staticmethod
def forward(ctx, min_radius: float, max_radius: float, sample_num: int,
xyz: torch.Tensor, center_xyz:... | 1,463 | 29.5 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/setup.py | from setuptools import find_packages, setup
import os
import shutil
import sys
import torch
import warnings
from os import path as osp
from torch.utils.cpp_extension import (BuildExtension, CppExtension,
CUDAExtension)
def readme():
with open('README.md', encoding='utf-8') ... | 11,944 | 36.211838 | 125 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/generate_dataset.py | import argparse
import os
import warnings
import time
import numpy as np
import torch
import mmcv
from mmdet3d.datasets import build_dataset, build_dataloader
from mmcv import Config, DictAction
from mmdet3d.datasets import build_dataset
from project.mmdet3d_plugin.corruptions import CORRUPTIONS
SEVERITY = {'1': '... | 5,606 | 35.174194 | 125 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/test.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import mmcv
import os
import torch
import warnings
from mmcv import Config, DictAction
from mmcv.cnn import fuse_conv_bn
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (get_dist_info, init_dist, load_checkpoint,... | 8,705 | 38.216216 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/robust_test.py | # Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Shaoyuan Xie
# ---------------------------------------------
import argparse
import mmcv
import os
import torch
import warnings
from mmcv import Config, DictAction
from mmcv.cnn import fuse_conv_bn
from mmcv.p... | 11,425 | 39.51773 | 94 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/train.py | # Copyright (c) OpenMMLab. All rights reserved.
from __future__ import division
import argparse
import copy
import mmcv
import os
import time
import torch
import warnings
from mmcv import Config, DictAction
from mmcv.runner import get_dist_info, init_dist
from os import path as osp
from mmdet import __version__ as mm... | 8,459 | 36.6 | 125 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/data_converter/create_gt_database.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pickle
from mmcv import track_iter_progress
from mmcv.ops import roi_align
from os import path as osp
from pycocotools import mask as maskUtils
from pycocotools.coco import COCO
from mmdet3d.core.bbox import box_np_ops as box_np_ops
... | 12,654 | 36.330383 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/misc/fuse_conv_bn.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import torch
from mmcv.runner import save_checkpoint
from torch import nn as nn
from mmdet3d.apis import init_model
def fuse_conv_bn(conv, bn):
"""During inference, the functionary of batch norm layers is turned off but
only the mean and var alo... | 2,242 | 31.985294 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/model_converters/publish_model.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import subprocess
import torch
def parse_args():
parser = argparse.ArgumentParser(
description='Process a checkpoint to be published')
parser.add_argument('in_file', help='input checkpoint filename')
parser.add_argument('out_file', he... | 1,075 | 28.888889 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/model_converters/regnet2mmdet.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import torch
from collections import OrderedDict
def convert_stem(model_key, model_weight, state_dict, converted_names):
new_key = model_key.replace('stem.conv', 'conv1')
new_key = new_key.replace('stem.bn', 'bn1')
state_dict[new_key] = model... | 3,062 | 33.033333 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/model_converters/convert_h3dnet_checkpoints.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import tempfile
import torch
from mmcv import Config
from mmcv.runner import load_state_dict
from mmdet3d.models import build_detector
def parse_args():
parser = argparse.ArgumentParser(
description='MMDet3D upgrade model version(before v0.6... | 6,152 | 33.762712 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/model_converters/convert_votenet_checkpoints.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import tempfile
import torch
from mmcv import Config
from mmcv.runner import load_state_dict
from mmdet3d.models import build_detector
def parse_args():
parser = argparse.ArgumentParser(
description='MMDet3D upgrade model version(before v0.6... | 5,090 | 32.27451 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/analysis_tools/benchmark.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import time
import torch
from mmcv import Config
from mmcv.parallel import MMDataParallel
from mmcv.runner import load_checkpoint, wrap_fp16_model
from mmdet3d.datasets import build_dataloader, build_dataset
from mmdet3d.models import build_detector
from ... | 2,987 | 30.125 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/analysis_tools/get_flops.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import torch
from mmcv import Config, DictAction
from mmdet3d.models import build_model
try:
from mmcv.cnn import get_model_complexity_info
except ImportError:
raise ImportError('Please upgrade mmcv to >0.6.2')
def parse_args():
parser = ar... | 3,578 | 31.834862 | 100 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/analysis_tools/mse_calculate.py | # ---------------------------------------------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------------------------------------------
# Modified by Shaoyuan Xie
# Used to calculate MSE of depth estimation between clean input and corrupt... | 7,571 | 35.057143 | 93 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tools/analysis_tools/depth_estimation.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Shaoyuan Xie
# Used to visualize depth estimation results
# ---------------------------------------------
import os
import time
import numpy as np
import os.pa... | 7,919 | 34.357143 | 88 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/docs_zh-CN/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... | 6,384 | 30.925 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/.dev_scripts/gather_models.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Script to gather benchmarked models and prepare them for upload.
Usage:
python gather_models.py ${root_path} ${out_dir}
"""
import argparse
import glob
import json
import mmcv
import shutil
import subprocess
import torch
from os import path as osp
# build schedule l... | 7,117 | 31.502283 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_runtime/test_config.py | # Copyright (c) OpenMMLab. All rights reserved.
from os.path import dirname, exists, join, relpath
def _get_config_directory():
"""Find the predefined detector config directory."""
try:
# Assume we are running in the source mmdetection3d repo
repo_dpath = dirname(dirname(dirname(__file__)))
... | 10,571 | 37.304348 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_runtime/test_apis.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import os
import pytest
import tempfile
import torch
from mmcv.parallel import MMDataParallel
from os.path import dirname, exists, join
from mmdet3d.apis import (convert_SyncBN, inference_detector,
inference_mono_3d_detector,
... | 15,732 | 42.461326 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_detectors.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import random
import torch
from os.path import dirname, exists, join
from mmdet3d.core.bbox import (CameraInstance3DBoxes, DepthInstance3DBoxes,
LiDARInstance3DBoxes)
from mmdet3d.models.builder ... | 17,930 | 36.989407 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_forward.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Test model forward process.
CommandLine:
pytest tests/test_models/test_forward.py
xdoctest tests/test_models/test_forward.py zero
"""
import copy
import numpy as np
import torch
from os.path import dirname, exists, join
def _get_config_directory():
"""Fi... | 6,212 | 28.727273 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_backbones.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.models import build_backbone
def test_pointnet2_sa_ssg():
if not torch.cuda.is_available():
pytest.skip()
cfg = dict(
type='PointNet2SASSG',
in_channels=6,
num_points=(3... | 12,167 | 39.56 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_segmentors.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import torch
from os.path import dirname, exists, join
from mmdet3d.models.builder import build_segmentor
from mmdet.apis import set_random_seed
def _get_config_directory():
"""Find the predefined detector config directo... | 12,345 | 39.214984 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_voxel_encoder/test_voxelize.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.voxel.voxel_generator import VoxelGenerator
from mmdet3d.datasets.pipelines import LoadPointsFromFile
from mmdet3d.ops.voxel.voxelize import Voxelization
def _get_voxel_points_indices(points, coors, voxel)... | 6,729 | 39.542169 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_voxel_encoder/test_dynamic_scatter.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from torch.autograd import gradcheck
from mmdet3d.ops import DynamicScatter
def test_dynamic_scatter():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
dsmean = DynamicScatter([0.32, 0.32, 6]... | 5,497 | 40.969466 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_voxel_encoder/test_voxel_encoders.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.models.builder import build_voxel_encoder
def test_pillar_feature_net():
pillar_feature_net_cfg = dict(
type='PillarFeatureNet',
in_channels=5,
feat_channels=[64],
with_distance=False,
voxel_size=(0.... | 1,146 | 31.771429 | 68 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_fusion/test_point_fusion.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Tests the core function of point fusion.
CommandLine:
pytest tests/test_models/test_fusion/test_point_fusion.py
"""
import torch
from mmdet3d.models.fusion_layers import PointFusion
def test_sample_single():
# this function makes sure the rewriting of 3d c... | 2,123 | 33.258065 | 75 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_fusion/test_vote_fusion.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Tests the core function of vote fusion.
CommandLine:
pytest tests/test_models/test_fusion/test_vote_fusion.py
"""
import torch
from mmdet3d.models.fusion_layers import VoteFusion
def test_vote_fusion():
img_meta = {
'ori_shape': (530, 730, 3),
... | 14,832 | 44.922601 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_fusion/test_fusion_coord_trans.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Tests coords transformation in fusion modules.
CommandLine:
pytest tests/test_models/test_fusion/test_fusion_coord_trans.py
"""
import torch
from mmdet3d.models.fusion_layers import apply_3d_transformation
def test_coords_transformation():
"""Test the tran... | 4,958 | 34.934783 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_common_modules/test_roiaware_pool3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.ops.roiaware_pool3d import (RoIAwarePool3d, points_in_boxes_batch,
points_in_boxes_cpu,
points_in_boxes_gpu)
def test_RoIAwarePool3d():
# RoIAw... | 5,798 | 43.607692 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_common_modules/test_vote_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
def test_vote_module():
from mmdet3d.models.model_utils import VoteModule
vote_loss = dict(
type='ChamferDistance',
mode='l1',
reduction='none',
loss_dst_weight=10.0)
self = VoteModule(vote_per_seed=3, in_channel... | 1,380 | 33.525 | 77 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_common_modules/test_paconv_modules.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
def test_paconv_sa_module_msg():
if not torch.cuda.is_available():
pytest.skip()
from mmdet3d.ops import PAConvSAModuleMSG
# paconv_num_kernels should have same length as mlp_channels
with pytest.rai... | 10,480 | 33.820598 | 74 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_common_modules/test_pointnet_ops.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.ops import (ball_query, furthest_point_sample,
furthest_point_sample_with_dist, gather_points,
grouping_operation, knn, three_interpolate, three_nn)
def test_fps():
if not tor... | 20,649 | 49.862069 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_common_modules/test_middle_encoders.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.models.builder import build_middle_encoder
def test_sparse_encoder():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
sparse_encoder_cfg = dict(
type='SparseEncoder',
... | 1,036 | 36.035714 | 76 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_common_modules/test_paconv_ops.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.ops import PAConv, PAConvCUDA, assign_score_withk
def test_paconv_assign_scores():
if not torch.cuda.is_available():
pytest.skip()
scores = torch.tensor([[[[0.06947571, 0.6065746], [0.28462553, 0.8378516],
... | 12,945 | 54.562232 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_common_modules/test_pointnet_modules.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
def test_pointnet_sa_module_msg():
if not torch.cuda.is_available():
pytest.skip()
from mmdet3d.ops import PointSAModuleMSG
self = PointSAModuleMSG(
num_point=16,
radii=[0.2, 0.4],
... | 7,125 | 31.244344 | 74 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_common_modules/test_sparse_unet.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.ops import SparseBasicBlock
from mmdet3d.ops import spconv as spconv
def test_SparseUNet():
from mmdet3d.models.middle_encoders.sparse_unet import SparseUNet
self = SparseUNet(in_channels=4, sparse_shape=[41, 1600, 1408])
# test e... | 5,844 | 41.355072 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_heads/test_roi_extractors.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.models.roi_heads.roi_extractors import Single3DRoIAwareExtractor
def test_single_roiaware_extractor():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
roi_layer_cfg = dict(
... | 1,313 | 40.0625 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_heads/test_semantic_heads.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.core.bbox import LiDARInstance3DBoxes
def test_PointwiseSemanticHead():
# PointwiseSemanticHead only support gpu version currently.
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')... | 3,037 | 35.60241 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_heads/test_paconv_decode_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmcv.cnn.bricks import ConvModule
from mmdet3d.models.builder import build_head
def test_paconv_decode_head_loss():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
paco... | 3,018 | 34.940476 | 71 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_heads/test_heads.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import random
import torch
from os.path import dirname, exists, join
from mmdet3d.core.bbox import (Box3DMode, CameraInstance3DBoxes,
DepthInstance3DBoxes, LiDARInstance3DBoxes)
from mmdet3d.mode... | 47,258 | 37.578776 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_heads/test_pointnet2_decode_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmcv.cnn.bricks import ConvModule
from mmdet3d.models.builder import build_head
def test_pn2_decode_head_loss():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
pn2_dec... | 3,002 | 34.75 | 71 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_heads/test_parta2_bbox_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmcv import Config
from torch.nn import BatchNorm1d, ReLU
from mmdet3d.core.bbox import Box3DMode, LiDARInstance3DBoxes
from mmdet3d.core.bbox.samplers import IoUNegPiecewiseSampler
from mmdet3d.models import PartA2BboxHead
from mmdet3d.op... | 20,614 | 40.646465 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_models/test_necks/test_necks.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.models.builder import build_backbone, build_neck
def test_centerpoint_fpn():
second_cfg = dict(
type='SECOND',
in_channels=64,
out_channels=[64, 128, 256],
layer_nums=[3, 5, 5],
layer_... | 1,834 | 29.583333 | 72 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_dataset_wrappers.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.datasets.builder import build_dataset
def test_getitem():
np.random.seed(1)
torch.manual_seed(1)
point_cloud_range = [-50, -50, -5, 50, 50, 3]
file_client_args = dict(backend='disk')
class_names = [
... | 2,891 | 35.15 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_kitti_mono_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pytest
import torch
from mmdet3d.datasets import KittiMonoDataset
def test_getitem():
np.random.seed(0)
class_names = ['Pedestrian', 'Cyclist', 'Car']
img_norm_cfg = dict(
mean=[103.530, 116.280, 123.675], std=[... | 8,734 | 39.439815 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_kitti_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import os
import pytest
import tempfile
import torch
from mmdet3d.core.bbox import LiDARInstance3DBoxes
from mmdet3d.datasets import KittiDataset
def _generate_kitti_dataset_config():
data_root = 'tests/data/kitti'
ann_file = 'tests/data/kitt... | 18,679 | 40.789709 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_scannet_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import torch
from mmdet3d.datasets import ScanNetDataset, ScanNetSegDataset
def test_getitem():
np.random.seed(0)
root_path = './tests/data/scannet/'
ann_file = './tests/data/scannet/scannet_infos.pkl'
class_... | 27,055 | 38.555556 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_nuscenes_mono_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pytest
import tempfile
import torch
from os import path as osp
from mmdet3d.datasets import NuScenesMonoDataset
def test_getitem():
np.random.seed(0)
class_names = [
'car', 'truck', 'trailer', 'bus', 'construction_v... | 7,531 | 38.434555 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVDet/tests/test_data/test_datasets/test_waymo_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import tempfile
import torch
from mmdet3d.datasets import WaymoDataset
def _generate_waymo_train_dataset_config():
data_root = 'tests/data/waymo/kitti_format/'
ann_file = 'tests/data/waymo/kitti_format/waymo_infos_train.pkl'
... | 10,825 | 40.163498 | 79 | py |
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