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/BEVerse/tools/test.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
from black import out
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_... | 10,764 | 37.584229 | 128 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/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... | 11,626 | 39.653846 | 94 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/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... | 9,633 | 36.780392 | 125 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/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/BEVerse/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 mmdet.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 alone... | 2,240 | 31.955882 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/tools/analysis_tools/get_flops.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import torch
import os
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')
import pdb
def parse_a... | 4,138 | 32.92623 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/tools/multi_gpu_test.py | import os.path as osp
import pickle
import shutil
import tempfile
import time
import mmcv
import torch
import torch.distributed as dist
from mmcv.runner import get_dist_info
from ..metrics import IntersectionOverUnion, PanopticMetric
from ..visualize import Visualizer
import pdb
def multi_gpu_test(model, data_load... | 10,540 | 37.330909 | 108 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/tools/single_gpu_test.py | # Copyright (c) OpenMMLab. All rights reserved.
from collections import defaultdict
import mmcv
import torch
from mmcv.image import tensor2imgs
from os import path as osp
import pdb
import time
import numpy as np
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import cv2
# define semantic metrics
f... | 10,219 | 37.421053 | 112 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/tools/__pycache__/debug_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
from __future__ import division
import argparse
import copy
from black import out
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 im... | 8,190 | 34.306034 | 102 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/basic_modules.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import OrderedDict
from functools import partial
from ..datasets.utils.geometry import warp_features
class ConvBlock(nn.Module):
"""2D convolution followed by
- an optional normalisation (batch norm or instance norm)
... | 19,425 | 36.647287 | 119 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/motion_modules.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .basic_modules import Bottleneck, SpatialGRU, ConvBlock, GRUCell
import pdb
import copy
class DistributionModule(nn.Module):
"""
A convolutional net that parametrises a diagonal Gaussian distribution.
"""
def __init__(
... | 15,447 | 33.328889 | 97 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/detectors/beverse.py | import torch
from mmdet3d.core import bbox3d2result, merge_aug_bboxes_3d
from mmdet.models import DETECTORS
from mmdet3d.models.detectors.mvx_two_stage import MVXTwoStageDetector
from mmdet3d.models import builder
from ...datasets.utils.geometry import cumulative_warp_features
import pdb
import time
from mmcv.runner... | 19,235 | 38.418033 | 110 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/necks/TransformerLSS.py | # Copyright (c) Junjie.huang. All rights reserved.
import torch
import torch.nn as nn
from mmcv.runner import BaseModule
from mmdet3d.models.builder import NECKS
from mmdet3d.models import builder
from mmdet.models.backbones.resnet import Bottleneck, BasicBlock
from mmcv.cnn import build_norm_layer
from mmdet3d.models... | 7,960 | 34.86036 | 96 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/necks/temporal.py | import torch
import torch.nn as nn
from mmcv.runner import BaseModule
from mmdet3d.models.builder import NECKS
from ...datasets.utils.geometry import cumulative_warp_features
from ...datasets.utils import FeatureWarper
from ..basic_modules import Bottleneck3D, TemporalBlock
import pdb
@NECKS.register_module()
class ... | 5,481 | 32.631902 | 92 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/dense_heads/mtl_head.py | import torch
import torch.nn as nn
from mmcv.runner import BaseModule
from mmdet3d.models import builder
from mmcv.cnn import build_norm_layer
from mmdet3d.models.builder import HEADS, build_loss
from .bev_encoder import BevEncode
from .map_head import BevFeatureSlicer
from mmcv.runner import auto_fp16, force_fp32
im... | 8,891 | 36.205021 | 107 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/dense_heads/motion_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet3d.models.builder import HEADS
from .base_taskhead import BaseTaskHead
from .loss_utils import MotionSegmentationLoss, SpatialRegressionLoss, ProbabilisticLoss, GaussianFocalLoss
from ...datasets.utils.geometry import cumulative_warp_features_... | 15,111 | 36.31358 | 114 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/dense_heads/loss_utils.py | from matplotlib.pyplot import autoscale
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet3d.models.builder import build_loss
from mmdet3d.models.utils import clip_sigmoid
import pdb
from mmcv.runner import auto_fp16, force_fp32
class BinarySegmentationLoss(torch.nn.Module):
def __init... | 10,549 | 32.492063 | 105 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/dense_heads/det_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import torch
from mmcv.cnn import ConvModule, build_conv_layer
from mmcv.runner import BaseModule, force_fp32
from torch import nn
from mmdet3d.core import (circle_nms, draw_heatmap_gaussian, gaussian_radius,
xywhr2xyxyr)
from mmdet3... | 26,257 | 40.812102 | 101 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/dense_heads/map_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet3d.models.builder import HEADS
from .base_taskhead import BaseTaskHead
import pdb
from .loss_utils import SegmentationLoss, BinarySegmentationLoss
from mmcv.runner import auto_fp16, force_fp32
from mmdet3d.models.utils import clip_sigmoid
d... | 5,670 | 37.060403 | 112 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/dense_heads/base_taskhead.py | import torch
import torch.nn as nn
from mmcv.runner import BaseModule
from mmcv.cnn import build_norm_layer
from mmdet3d.models.builder import HEADS
from mmcv.runner import auto_fp16, force_fp32
import pdb
@HEADS.register_module()
class BaseTaskHead(BaseModule):
def __init__(self, task_dict, in_channels, inter_... | 1,299 | 31.5 | 90 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/dense_heads/bev_encoder.py | import torch
import torch.nn as nn
from mmcv.runner import BaseModule
from mmdet.models.backbones.resnet import Bottleneck, BasicBlock
from mmcv.cnn import build_norm_layer
from mmdet3d.models import builder
import pdb
class Up(nn.Module):
def __init__(self, in_channels, out_channels, scale_factor=2, norm_cfg=di... | 7,656 | 40.389189 | 99 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/motion_heads/_base_motion_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from mmdet3d.models.builder import HEADS
from ..dense_heads.base_taskhead import BaseTaskHead
from ..dense_heads.loss_utils import MotionSegmentationLoss, SpatialRegressionLoss, ProbabilisticLoss, GaussianFocalLoss, SpatialProbabilis... | 17,244 | 37.068433 | 146 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/motion_heads/iterative_flow.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet3d.models.builder import HEADS
from ..dense_heads.base_taskhead import BaseTaskHead
from ..dense_heads.loss_utils import MotionSegmentationLoss, SpatialRegressionLoss, ProbabilisticLoss, GaussianFocalLoss, SpatialProbabilisticLoss
from ...data... | 3,357 | 35.5 | 146 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/models/motion_heads/fierymotion.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmdet3d.models.builder import HEADS
from ..motion_modules import FuturePrediction
from ._base_motion_head import BaseMotionHead
import pdb
@HEADS.register_module()
class FieryMotionHead(BaseMotionHead):
def __init__(
self,
d... | 2,604 | 31.974684 | 90 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/visualize/motion_visualisation.py | import numpy as np
import torch
import matplotlib.pylab
import matplotlib.pyplot as plt
import pdb
import cv2
from ..datasets.utils.instance import predict_instance_segmentation_and_trajectories
DEFAULT_COLORMAP = matplotlib.pylab.cm.jet
INSTANCE_COLOURS = np.asarray([
[0, 0, 0],
[255, 179, 0],
[128, 62, ... | 13,694 | 31.375887 | 137 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/visualize/visualizer.py | import PIL
import numpy as np
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import torch
import imageio
import cv2
import mmcv
from PIL import Image
from .motion_visualisation import plot_instance_map, visualise_output, make_contour, generate_instance_colours, plot_motion_prediction
from mmdet3d.c... | 19,808 | 37.094231 | 134 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/metrics/metrics.py | import torch
import mmcv
import tempfile
import torch.distributed as dist
import os.path as osp
import shutil
from typing import Optional
from torchmetrics.metric import Metric
from torchmetrics.functional.classification import stat_scores
from mmcv.runner import get_dist_info
import pdb
class IntersectionOverUnion(... | 11,836 | 40.533333 | 115 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/mtl_nuscenes_dataset_ego.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import torch
import pyquaternion
import tempfile
from nuscenes.utils.data_classes import Box as NuScenesBox
from os import path as osp
from mmdet.datasets import DATASETS
from mmdet3d.core import show_result
from mmdet3d.core.bbox import Bo... | 22,637 | 37.697436 | 316 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/utils/warper.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from pyquaternion import Quaternion
from .geometry import pose_vec2mat, mat2pose_vec, invert_pose_matrix
def gen_dx_bx(xbound, ybound, zbound):
dx = torch.Tensor([row[2] for row in [xbound, ybound, zbound]])
bx = torch.Tenso... | 4,904 | 35.879699 | 97 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/utils/geometry.py | import PIL
import numpy as np
import torch
from pyquaternion import Quaternion
import pdb
def invert_matrix_egopose_numpy(egopose):
""" Compute the inverse transformation of a 4x4 egopose numpy matrix."""
inverse_matrix = np.zeros((4, 4), dtype=np.float32)
rotation = egopose[:3, :3]
translation = ego... | 8,556 | 33.091633 | 109 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/utils/instance.py | from typing import Tuple
import torch
import torch.nn.functional as F
import numpy as np
from scipy.optimize import linear_sum_assignment
from .geometry import mat2pose_vec, pose_vec2mat, warp_features
import pdb
def convert_instance_mask_to_center_and_offset_label(instance_img, future_egomotion, num_instances, ign... | 17,542 | 38.961276 | 173 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/pipelines/loading.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch
import torchvision
from PIL import Image
import numpy as np
import os
import pyquaternion
import imageio
from mmdet.datasets.builder import PIPELINES
from mmdet.datasets.pipelines import LoadAnnotations
import pdb
def get_rot(h):
return to... | 16,752 | 36.064159 | 92 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/pipelines/transform_3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import numpy as np
import warnings
from mmcv import is_tuple_of
from mmcv.utils import build_from_cfg
from mmdet3d.core import VoxelGenerator
from mmdet3d.core.bbox import (CameraInstance3DBoxes, DepthInstance3DBoxes,
LiDARInst... | 21,970 | 37.478109 | 143 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/pipelines/motion_labels.py | from enum import unique
from unittest import result
import torch
import numpy as np
import cv2
import pdb
from ...models.dense_heads.map_head import calculate_birds_eye_view_parameters
from mmdet.datasets.builder import PIPELINES
from ..utils.instance import convert_instance_mask_to_center_and_offset_label, convert_in... | 6,493 | 42.583893 | 144 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/pipelines/rasterize.py | import torch
import numpy as np
from mmdet.datasets.builder import PIPELINES
from ..utils import preprocess_map
import pdb
import warnings
warnings.filterwarnings('ignore')
@PIPELINES.register_module()
class RasterizeMapVectors(object):
"""Load multi channel images from a list of separate channel files.
Ex... | 2,291 | 32.217391 | 127 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/projects/mmdet3d_plugin/datasets/pipelines/custom_loading.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch
import torchvision
from PIL import Image
import numpy as np
import os
import pyquaternion
import imageio
from mmdet.datasets.builder import PIPELINES
from mmdet.datasets.pipelines import LoadAnnotations
import pdb
def get_rot(h):
return tor... | 10,784 | 39.092937 | 117 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/BEVerse/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)
import pdb
def single_gpu_test(model,
data_lo... | 3,121 | 34.477273 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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/BEVerse/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 |
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