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/Sparse4D/projects/mmdet3d_plugin/models/target.py | import torch
import numpy as np
from scipy.optimize import linear_sum_assignment
from mmdet3d.core.bbox import BaseInstance3DBoxes
from mmdet.core.bbox.builder import BBOX_SAMPLERS
__all__ = ["SparseBox3DTarget"]
X, Y, Z, W, L, H, SIN_YAW, COS_YAW, VX, VY, VZ = list(range(11))
YAW = 6
@BBOX_SAMPLERS.register_modul... | 4,883 | 32.22449 | 81 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/models/sparse4d_head.py | # Copyright (c) Horizon Robotics. All rights reserved.
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn.bricks.registry import (
ATTENTION,
PLUGIN_LAYERS,
POSITIONAL_ENCODING,
FEEDFORWARD_NETWORK,
NORM_LAYERS,
)
from mmcv.runner im... | 11,567 | 35.263323 | 78 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/models/sparse4d.py | # Copyright (c) Horizon Robotics. All rights reserved.
import torch
from mmcv.runner import force_fp32, auto_fp16
from mmdet.models import (
DETECTORS,
BaseDetector,
build_backbone,
build_head,
build_neck,
)
from .grid_mask import GridMask
__all__ = ["Sparse4D"]
@DETECTORS.register_module()
clas... | 3,491 | 28.846154 | 74 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/models/grid_mask.py | import torch
import torch.nn as nn
import numpy as np
from PIL import Image
class Grid(object):
def __init__(
self, use_h, use_w, rotate=1, offset=False, ratio=0.5, mode=0, prob=1.0
):
self.use_h = use_h
self.use_w = use_w
self.rotate = rotate
self.offset = offset
... | 4,083 | 28.381295 | 79 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/models/decoder.py | # Copyright (c) Horizon Robotics. All rights reserved.
from typing import Optional
import torch
from mmdet.core.bbox.builder import BBOX_CODERS
X, Y, Z, W, L, H, SIN_Y, COS_Y, VX, VY, VZ = list(range(11))
@BBOX_CODERS.register_module()
class SparseBox3DDecoder(object):
def __init__(
self,
num_o... | 1,892 | 30.032787 | 72 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/models/blocks.py | # Copyright (c) Horizon Robotics. All rights reserved.
from typing import List, Optional, Tuple
import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import Linear, Scale, bias_init_with_prob
from mmcv.runner.base_module import Sequential, BaseModule
from mmcv.cnn.bricks.transformer import FFN
from mmcv... | 21,197 | 34.567114 | 80 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/datasets/nuscenes_3d_det_track_dataset.py | import torch
import random
import os
from os import path as osp
import cv2
import tempfile
import copy
import numpy as np
import pyquaternion
from nuscenes.utils.data_classes import Box as NuScenesBox
from nuscenes.eval.detection.config import config_factory as det_configs
from nuscenes.eval.common.config import confi... | 40,448 | 34.890861 | 79 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/datasets/builder.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import platform
import random
from functools import partial
import numpy as np
from mmcv.parallel import collate
from mmcv.runner import get_dist_info
from mmcv.utils import Registry, build_from_cfg
from torch.utils.data import DataLoader
from mmdet.datasets... | 5,755 | 31.519774 | 78 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/datasets/samplers/group_sampler.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import numpy as np
import torch
from mmcv.runner import get_dist_info
from torch.utils.data import Sampler
from .sampler import SAMPLER
import random
from IPython import embed
@SAMPLER.register_module()
class DistributedGroupSampler(Sampler):
"""Sampler... | 4,133 | 33.45 | 78 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/datasets/samplers/distributed_sampler.py | import math
import torch
from torch.utils.data import DistributedSampler as _DistributedSampler
from .sampler import SAMPLER
import pdb
import sys
class ForkedPdb(pdb.Pdb):
def interaction(self, *args, **kwargs):
_stdin = sys.stdin
try:
sys.stdin = open("/dev/stdin")
pdb.... | 2,567 | 29.939759 | 78 | py |
RoboBEV | RoboBEV-master/zoo/Sparse4D/projects/mmdet3d_plugin/datasets/pipelines/transform_3d.py | import time
import torch
import numpy as np
from numpy import random
import mmcv
from mmdet.datasets.builder import PIPELINES
from PIL import Image
@PIPELINES.register_module()
class NuScenesSparse4DAdaptor(object):
def __init(self):
pass
def __call__(self, input_dict):
input_dict["projectio... | 20,356 | 32.263072 | 82 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/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 = {'2': '... | 5,629 | 35.322581 | 125 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/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/ora3d/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... | 9,490 | 37.116466 | 125 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/tools/corruption_test.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from copy import deepcopy
import os.path as osp
import pickle
import shutil
import tempfile
import time
... | 6,699 | 35.813187 | 118 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/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/ora3d/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/ora3d/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/ora3d/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/ora3d/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/ora3d/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/ora3d/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... | 3,147 | 31.791667 | 79 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/core/bbox/util.py | import torch
def normalize_bbox(bboxes, pc_range):
cx = bboxes[..., 0:1]
cy = bboxes[..., 1:2]
cz = bboxes[..., 2:3]
w = bboxes[..., 3:4].log()
l = bboxes[..., 4:5].log()
h = bboxes[..., 5:6].log()
rot = bboxes[..., 6:7]
if bboxes.size(-1) > 7:
vx = bboxes[..., 7:8]
... | 1,464 | 26.641509 | 83 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/core/bbox/assigners/hungarian_assigner_3d.py | import torch
from mmdet.core.bbox.builder import BBOX_ASSIGNERS
from mmdet.core.bbox.assigners import AssignResult
from mmdet.core.bbox.assigners import BaseAssigner
from mmdet.core.bbox.match_costs import build_match_cost
from mmdet.models.utils.transformer import inverse_sigmoid
from projects.ora3d.core.bbox.util im... | 6,382 | 46.634328 | 79 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/core/bbox/match_costs/match_cost.py | import torch
from mmdet.core.bbox.match_costs.builder import MATCH_COST
@MATCH_COST.register_module()
class BBox3DL1Cost(object):
"""BBox3DL1Cost.
Args:
weight (int | float, optional): loss_weight
"""
def __init__(self, weight=1.):
self.weight = weight
def __call__(self, bbox_p... | 852 | 30.592593 | 75 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/core/bbox/coders/nms_free_coder.py | import torch
from mmdet.core.bbox import BaseBBoxCoder
from mmdet.core.bbox.builder import BBOX_CODERS
from projects.ora3d.core.bbox.util import denormalize_bbox
@BBOX_CODERS.register_module()
class NMSFreeCoder(BaseBBoxCoder):
"""Bbox coder for NMS-free detector.
Args:
pc_range (list[float]): Range ... | 4,133 | 36.243243 | 109 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/detectors/detr3d.py | import torch
import torchvision
from mmcv.runner import force_fp32, auto_fp16
from mmdet.models import DETECTORS
from mmdet3d.core import bbox3d2result
from mmdet3d.models.detectors.mvx_two_stage import MVXTwoStageDetector
from projects.ora3d.models.transformer.utils.grid_mask import GridMask
from projects.ora3d.models... | 13,367 | 42.122581 | 145 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/detectors/utils/overlap_stereo.py | import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
from functools import wraps
from time import time
import math
import torchvision
from projects.ora3d.models.detectors.utils.overlap_depth_loss import DisparityLoss
def conv3x3(in_planes, out_planes, stride=1, dilation=1):
""... | 12,405 | 39.67541 | 130 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/detectors/utils/overlap_depth_loss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import torchvision.transforms.functional as TVF
def isNaN(x):
return x != x
class Disp2Prob(object):
"""
Convert disparity map to matching probability volume
Args:
maxDisp, (int): the maximum of dis... | 10,508 | 39.419231 | 151 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/detectors/utils/find_overlap_region.py | import torch
import numpy as np
def find_overlap_left(cam2lidar_1, lidar2cam_2):
infinity = 10000
# Camera coordinate system representation of the top left and bottom left points of the image
cam_left_top_1 = torch.FloatTensor([0.001 * infinity, 0.001 * infinity, infinity, 1])
cam_left_bottom_1 = tor... | 4,177 | 40.78 | 125 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/dense_heads/detr3d_head.py | import copy
import torch
import torch.nn as nn
from mmcv.cnn import Linear, bias_init_with_prob
from mmcv.runner import force_fp32
from mmdet.core import (multi_apply, multi_apply, reduce_mean)
from mmdet.models.utils.transformer import inverse_sigmoid
from mmdet.models import HEADS
from mmdet.models.dense_heads impor... | 22,213 | 44.991718 | 135 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/dense_heads/utils/discriminator.py | import torch
import torch.nn as nn
import torch.nn.functional as F
class Discriminator(nn.Module):
def __init__(self):
super(Discriminator, self).__init__()
self.discriminator = nn.Sequential(
nn.Linear(in_features=256, out_features=100),
nn.BatchNorm1d(900),
nn... | 1,293 | 32.179487 | 57 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/transformer/detr3d_transformer.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import xavier_init, constant_init
from mmcv.cnn.bricks.registry import (ATTENTION,
TRANSFORMER_LAYER_SEQUENCE)
from mmcv.cnn.bricks.transformer import (MultiScaleDeformableAttention,... | 18,673 | 39.684096 | 104 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/transformer/utils/grid_mask.py | import torch
import torch.nn as nn
import numpy as np
from PIL import Image
class Grid(object):
def __init__(self, use_h, use_w, rotate = 1, offset=False, ratio = 0.5, mode=0, prob = 1.):
self.use_h = use_h
self.use_w = use_w
self.rotate = rotate
self.offset = offset
self.ra... | 3,825 | 30.105691 | 95 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/models/backbones/vovnet.py |
from collections import OrderedDict
from mmcv.runner import BaseModule
from mmdet.models.builder import BACKBONES
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.batchnorm import _BatchNorm
VoVNet19_slim_dw_eSE = {
'stem': [64, 64, 64],
'stage_conv_ch': [64, 80, 96, 1... | 11,700 | 30.202667 | 119 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/ora3d/datasets/nuscenes_dataset.py | import numpy as np
from mmdet.datasets import DATASETS
from mmdet3d.datasets import NuScenesDataset
@DATASETS.register_module()
class CustomNuScenesDataset(NuScenesDataset):
r"""NuScenes Dataset.
This datset only add camera intrinsics and extrinsics to the results.
"""
def get_data_info(self, index)... | 2,846 | 35.974026 | 78 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/configs/ora3d_res101.py | _base_ = [
'../../../mmdetection3d/configs/_base_/datasets/nus-3d.py',
'../../../mmdetection3d/configs/_base_/default_runtime.py'
]
plugin=True
plugin_dir='projects/ora3d/'
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
voxel_size = [0.2, 0.2, 8]
img_norm_cfg = dict(
mean=[103.530, 116.280, 12... | 7,329 | 29.164609 | 97 | py |
RoboBEV | RoboBEV-master/zoo/ora3d/projects/configs/robust_test/ora3d_res101.py | _base_ = [
'/nvme/konglingdong/models/mmdetection3d/configs/_base_/datasets/nus-3d.py',
'/nvme/konglingdong/models/mmdetection3d/configs/_base_/default_runtime.py'
]
plugin=True
plugin_dir='projects/ora3d/'
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
voxel_size = [0.2, 0.2, 8]
img_norm_cfg = di... | 8,473 | 30.501859 | 130 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/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 = {'2': '... | 5,629 | 35.322581 | 125 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/tools/test.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
import argparse
from genericpath import isdir
import mmcv
import os
import torch
import warnings
from mm... | 13,735 | 39.046647 | 116 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/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/BEVFormer/tools/train.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from __future__ import division
import argparse
import copy
import mmcv
import os
import time
import ... | 10,041 | 37.623077 | 125 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/tools/corruption_test.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from copy import deepcopy
import os.path as osp
import pickle
import shutil
import tempfile
import time
... | 6,699 | 35.813187 | 118 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/tools/corruptions.py | from copy import deepcopy
import functools
import PIL
from PIL import Image
import torch
import numpy as np
from mmcv.utils import Registry
from imagecorruptions import corrupt
CORRUPTIONS= Registry('corruptions')
@CORRUPTIONS.register_module()
class Clean:
def __init__(self, severity, norm_config):
"... | 11,150 | 30.589235 | 108 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/tools/fp16/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, wrap_fp16_model
from os import path as osp
from mmdet import ... | 10,371 | 37.132353 | 125 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/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/BEVFormer/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/BEVFormer/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/BEVFormer/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/BEVFormer/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/BEVFormer/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
import sys
sys.path.append('.')
from projects.mmdet3d_plugin.datasets.builder import build_dataloader
from pr... | 3,245 | 31.787879 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/tools/analysis_tools/get_params.py | import torch
file_path = './ckpts/bevformer_v4.pth'
model = torch.load(file_path, map_location='cpu')
all = 0
for key in list(model['state_dict'].keys()):
all += model['state_dict'][key].nelement()
print(all)
# smaller 63374123
# v4 69140395
| 247 | 21.545455 | 49 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/tools/analysis_tools/visual.py | # Based on https://github.com/nutonomy/nuscenes-devkit
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
import mmcv
import os
from nuscenes.nuscenes import NuScenes
from PIL import Image
from nuscenes.utils.geometry_utils import view_points, box_in... | 22,696 | 43.944554 | 143 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/bevformer_fp16/bevformer_tiny_fp16.py | # BEvFormer-tiny consumes at lease 6700M GPU memory
# compared to bevformer_base, bevformer_tiny has
# smaller backbone: R101-DCN -> R50
# smaller BEV: 200*200 -> 50*50
# less encoder layers: 6 -> 3
# smaller input size: 1600*900 -> 800*450
# multi-scale feautres -> single scale features (C5)
_base_ = [
'../datas... | 9,215 | 32.882353 | 118 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/robust_test/bevformer_small_no_temp.py | # BEvFormer-small consumes at lease 10500M GPU memory
# compared to bevformer_base, bevformer_small has
# smaller BEV: 200*200 -> 150*150
# less encoder layers: 6 -> 3
# smaller input size: 1600*900 -> (1600*900)*0.8
# multi-scale feautres -> single scale features (C5)
# with_cp of backbone = True
_base_ = [
'../d... | 9,754 | 34.732601 | 135 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/robust_test/bevformer_base_no_temp.py | _base_ = [
'../datasets/custom_nus-3d.py',
'../_base_/default_runtime.py'
]
#
plugin = True
plugin_dir = 'projects/mmdet3d_plugin/'
# 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]
voxel_size = [0.2,... | 9,258 | 34.205323 | 135 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/robust_test/bevformer_base.py | _base_ = [
'../datasets/custom_nus-3d.py',
'../_base_/default_runtime.py'
]
#
plugin = True
plugin_dir = 'projects/mmdet3d_plugin/'
# 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]
voxel_size = [0.2,... | 9,291 | 34.330798 | 135 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/robust_test/bevformer_small.py | # BEvFormer-small consumes at lease 10500M GPU memory
# compared to bevformer_base, bevformer_small has
# smaller BEV: 200*200 -> 150*150
# less encoder layers: 6 -> 3
# smaller input size: 1600*900 -> (1600*900)*0.8
# multi-scale feautres -> single scale features (C5)
# with_cp of backbone = True
_base_ = [
'../d... | 9,753 | 34.728938 | 135 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/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/BEVFormer/projects/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/BEVFormer/projects/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/BEVFormer/projects/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/BEVFormer/projects/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/BEVFormer/projects/configs/bevformer/bevformer_small_no_temp.py | # BEvFormer-small consumes at lease 10500M GPU memory
# compared to bevformer_base, bevformer_small has
# smaller BEV: 200*200 -> 150*150
# less encoder layers: 6 -> 3
# smaller input size: 1600*900 -> (1600*900)*0.8
# multi-scale feautres -> single scale features (C5)
# with_cp of backbone = True
_base_ = [
'../d... | 9,477 | 34.103704 | 135 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/bevformer/bevformer_base_no_temp.py | _base_ = [
'../datasets/custom_nus-3d.py',
'../_base_/default_runtime.py'
]
#
plugin = True
plugin_dir = 'projects/mmdet3d_plugin/'
# 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]
voxel_size = [0.2,... | 8,924 | 33.593023 | 135 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/bevformer/bevformer_tiny.py | # BEvFormer-tiny consumes at lease 6700M GPU memory
# compared to bevformer_base, bevformer_tiny has
# smaller backbone: R101-DCN -> R50
# smaller BEV: 200*200 -> 50*50
# less encoder layers: 6 -> 3
# smaller input size: 1600*900 -> 800*450
# multi-scale feautres -> single scale features (C5)
_base_ = [
'../datas... | 9,111 | 32.623616 | 118 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/bevformer/bevformer_base.py | _base_ = [
'../datasets/custom_nus-3d.py',
'../_base_/default_runtime.py'
]
#
plugin = True
plugin_dir = 'projects/mmdet3d_plugin/'
# 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]
voxel_size = [0.2,... | 8,924 | 33.593023 | 135 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/configs/bevformer/bevformer_small.py | # BEvFormer-small consumes at lease 10500M GPU memory
# compared to bevformer_base, bevformer_small has
# smaller BEV: 200*200 -> 150*150
# less encoder layers: 6 -> 3
# smaller input size: 1600*900 -> (1600*900)*0.8
# multi-scale feautres -> single scale features (C5)
# with_cp of backbone = True
_base_ = [
'../d... | 9,476 | 34.1 | 135 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/core/evaluation/eval_hooks.py |
# Note: Considering that MMCV's EvalHook updated its interface in V1.3.16,
# in order to avoid strong version dependency, we did not directly
# inherit EvalHook but BaseDistEvalHook.
import bisect
import os.path as osp
import mmcv
import torch.distributed as dist
from mmcv.runner import DistEvalHook as BaseDistEvalH... | 3,512 | 37.184783 | 112 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/core/bbox/util.py | import torch
def normalize_bbox(bboxes, pc_range):
cx = bboxes[..., 0:1]
cy = bboxes[..., 1:2]
cz = bboxes[..., 2:3]
w = bboxes[..., 3:4].log()
l = bboxes[..., 4:5].log()
h = bboxes[..., 5:6].log()
rot = bboxes[..., 6:7]
if bboxes.size(-1) > 7:
vx = bboxes[..., 7:8]
... | 1,467 | 26.698113 | 83 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/core/bbox/assigners/hungarian_assigner_3d.py | import torch
from mmdet.core.bbox.builder import BBOX_ASSIGNERS
from mmdet.core.bbox.assigners import AssignResult
from mmdet.core.bbox.assigners import BaseAssigner
from mmdet.core.bbox.match_costs import build_match_cost
from mmdet.models.utils.transformer import inverse_sigmoid
from projects.mmdet3d_plugin.core.bbo... | 6,404 | 46.095588 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/core/bbox/match_costs/match_cost.py | import torch
from mmdet.core.bbox.match_costs.builder import MATCH_COST
@MATCH_COST.register_module()
class BBox3DL1Cost(object):
"""BBox3DL1Cost.
Args:
weight (int | float, optional): loss_weight
"""
def __init__(self, weight=1.):
self.weight = weight
def __call__(self, bbox_p... | 852 | 30.592593 | 75 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/core/bbox/coders/nms_free_coder.py | import torch
from mmdet.core.bbox import BaseBBoxCoder
from mmdet.core.bbox.builder import BBOX_CODERS
from projects.mmdet3d_plugin.core.bbox.util import denormalize_bbox
import numpy as np
@BBOX_CODERS.register_module()
class NMSFreeCoder(BaseBBoxCoder):
"""Bbox coder for NMS-free detector.
Args:
pc... | 4,476 | 35.398374 | 109 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/models/opt/adamw.py | try:
from torch.optim import _functional as F
except:
print('WARNING!!!, I recommend using torch>=1.8')
import torch
from torch.optim.optimizer import Optimizer
from mmcv.runner.optimizer.builder import OPTIMIZERS
@OPTIMIZERS.register_module()
class AdamW2(Optimizer):
r"""Implements AdamW algorithm. Solve... | 5,144 | 38.274809 | 106 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/models/utils/position_embedding.py | import torch
import torch.nn as nn
import math
class RelPositionEmbedding(nn.Module):
def __init__(self, num_pos_feats=64, pos_norm=True):
super().__init__()
self.num_pos_feats = num_pos_feats
self.fc = nn.Linear(4, self.num_pos_feats,bias=False)
#nn.init.orthogonal_(self.fc.weight)... | 1,437 | 41.294118 | 97 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/models/utils/grid_mask.py | import torch
import torch.nn as nn
import numpy as np
from PIL import Image
from mmcv.runner import force_fp32, auto_fp16
class Grid(object):
def __init__(self, use_h, use_w, rotate = 1, offset=False, ratio = 0.5, mode=0, prob = 1.):
self.use_h = use_h
self.use_w = use_w
self.rotate = rotat... | 3,935 | 30.741935 | 95 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/models/utils/bricks.py | import functools
import time
from collections import defaultdict
import torch
time_maps = defaultdict(lambda :0.)
count_maps = defaultdict(lambda :0.)
def run_time(name):
def middle(fn):
def wrapper(*args, **kwargs):
torch.cuda.synchronize()
start = time.time()
res = fn(*... | 725 | 35.3 | 149 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/models/utils/visual.py | import torch
from torchvision.utils import make_grid
import torchvision
import matplotlib.pyplot as plt
import cv2
def convert_color(img_path):
plt.figure()
img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)
plt.imsave(img_path, img, cmap=plt.get_cmap('viridis'))
plt.close()
def save_tensor(tensor, pa... | 768 | 29.76 | 100 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/models/backbones/vovnet.py |
from collections import OrderedDict
from mmcv.runner import BaseModule
from mmdet.models.builder import BACKBONES
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.batchnorm import _BatchNorm
VoVNet19_slim_dw_eSE = {
'stem': [64, 64, 64],
'stage_conv_ch': [64, 80, 96, 1... | 11,701 | 30.205333 | 119 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/datasets/nuscenes_dataset.py | import copy
import numpy as np
from mmdet.datasets import DATASETS
from mmdet3d.datasets import NuScenesDataset
import mmcv
from os import path as osp
from mmdet.datasets import DATASETS
import torch
import numpy as np
from nuscenes.eval.common.utils import quaternion_yaw, Quaternion
from .nuscnes_eval import NuScenes... | 9,395 | 37.987552 | 97 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/datasets/nuscenes_mono_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import mmcv
import numpy as np
import pyquaternion
import tempfile
import torch
import warnings
from nuscenes.utils.data_classes import Box as NuScenesBox
from os import path as osp
from mmdet3d.core import bbox3d2result, box3d_multiclass_nms, xywhr2xyxyr
fro... | 33,027 | 41.507079 | 154 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/datasets/nuscnes_eval.py | import argparse
import copy
import json
import os
import time
from typing import Tuple, Dict, Any
import torch
import numpy as np
from nuscenes import NuScenes
from nuscenes.eval.common.config import config_factory
from nuscenes.eval.common.data_classes import EvalBoxes
from nuscenes.eval.detection.data_classes import... | 31,695 | 41.148936 | 118 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/datasets/builder.py |
# Copyright (c) OpenMMLab. All rights reserved.
import copy
import platform
import random
from functools import partial
import numpy as np
from mmcv.parallel import collate
from mmcv.runner import get_dist_info
from mmcv.utils import Registry, build_from_cfg
from torch.utils.data import DataLoader
from mmdet.dataset... | 5,961 | 39.557823 | 128 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/datasets/samplers/group_sampler.py |
# Copyright (c) OpenMMLab. All rights reserved.
import math
import numpy as np
import torch
from mmcv.runner import get_dist_info
from torch.utils.data import Sampler
from .sampler import SAMPLER
import random
from IPython import embed
@SAMPLER.register_module()
class DistributedGroupSampler(Sampler):
"""Sample... | 3,959 | 34.675676 | 78 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/datasets/samplers/distributed_sampler.py | import math
import torch
from torch.utils.data import DistributedSampler as _DistributedSampler
from .sampler import SAMPLER
@SAMPLER.register_module()
class DistributedSampler(_DistributedSampler):
def __init__(self,
dataset=None,
num_replicas=None,
rank=None,... | 1,371 | 31.666667 | 79 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/apis/test.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from copy import deepcopy
import os.path as osp
import pickle
import shutil
import tempfile
import time
... | 8,500 | 34.569038 | 127 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/apis/mmdet_train.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
import random
import warnings
import numpy as np
import torch
import torch.distributed as dist
from mmc... | 7,863 | 38.124378 | 115 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/modules/custom_base_transformer_layer.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
import copy
import warnings
import torch
import torch.nn as nn
from mmcv import ConfigDict, deprecate... | 11,348 | 42.482759 | 109 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/modules/multi_scale_deformable_attn_function.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
import torch
from torch.cuda.amp import custom_bwd, custom_fwd
from torch.autograd.function import Func... | 6,120 | 36.323171 | 74 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/modules/encoder.py |
# ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from projects.mmdet3d_plugin.models.utils.bricks import run_time
from projects.mmdet3d_plugin.models.u... | 16,550 | 39.967822 | 168 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/modules/transformer.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import xavier_init
from mmcv.cnn.br... | 11,918 | 40.1 | 99 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/modules/decoder.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from mmcv.ops.multi_scale_deform_attn import multi_scale_deformable_attn_pytorch
import mmcv
import cv2... | 14,189 | 40.011561 | 97 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/modules/temporal_self_attention.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from projects.mmdet3d_plugin.models.utils.bricks import run_time
from .multi_scale_deformable_attn_func... | 11,898 | 42.586081 | 117 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/modules/spatial_cross_attention.py |
# ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from mmcv.ops.multi_scale_deform_attn import multi_scale_deformable_attn_pytorch
import warnings
impor... | 17,548 | 42.8725 | 155 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/detectors/bevformer_fp16.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from tkinter.messagebox import NO
import torch
from mmcv.runner import force_fp32, auto_fp16
from mmdet... | 3,633 | 39.831461 | 93 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/detectors/bevformer.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
from tkinter.messagebox import NO
import torch
from mmcv.runner import force_fp32, auto_fp16
from mmdet... | 12,021 | 39.891156 | 107 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/dense_heads/bevformer_head.py | # ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import Lin... | 23,021 | 42.935115 | 97 | py |
RoboBEV | RoboBEV-master/zoo/BEVFormer/projects/mmdet3d_plugin/bevformer/runner/epoch_based_runner.py | # Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
import os.path as osp
import torch
import mmcv
from mmcv.runner.base_runner import BaseRunner
from mmcv.runner.epoch_based_runner import EpochBasedRunn... | 3,864 | 38.845361 | 166 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/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') ... | 11,930 | 36.284375 | 125 | py |
RoboBEV | RoboBEV-master/zoo/BEVerse/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 = {'2': '... | 5,629 | 35.322581 | 125 | py |
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