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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3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/vfe_template.py | import torch.nn as nn
class VFETemplate(nn.Module):
def __init__(self, model_cfg, **kwargs):
super().__init__()
self.model_cfg = model_cfg
def get_output_feature_dim(self):
raise NotImplementedError
def forward(self, **kwargs):
"""
Args:
**kwargs:
... | 470 | 19.478261 | 45 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/dynamic_mean_vfe.py | import torch
from .vfe_template import VFETemplate
try:
import torch_scatter
except Exception as e:
# Incase someone doesn't want to use dynamic pillar vfe and hasn't installed torch_scatter
pass
from .vfe_template import VFETemplate
class DynamicMeanVFE(VFETemplate):
def __init__(self, model_cfg, ... | 2,980 | 37.714286 | 106 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/mean_vfe.py | import torch
from .vfe_template import VFETemplate
class MeanVFE(VFETemplate):
def __init__(self, model_cfg, num_point_features, **kwargs):
super().__init__(model_cfg=model_cfg)
self.num_point_features = num_point_features
def get_output_feature_dim(self):
return self.num_point_featu... | 1,038 | 31.46875 | 99 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/dynamic_pillar_vfe.py | import torch
import torch.nn as nn
import torch.nn.functional as F
try:
import torch_scatter
except Exception as e:
# Incase someone doesn't want to use dynamic pillar vfe and hasn't installed torch_scatter
pass
from .vfe_template import VFETemplate
class PFNLayerV2(nn.Module):
def __init__(self,
... | 5,614 | 38.265734 | 118 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/pillar_vfe.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .vfe_template import VFETemplate
class PFNLayer(nn.Module):
def __init__(self,
in_channels,
out_channels,
use_norm=True,
last_layer=False):
super().__init__()
... | 5,099 | 40.129032 | 137 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe.py | import torch
from .vfe_template import VFETemplate
from .image_vfe_modules import ffn, f2v
class ImageVFE(VFETemplate):
def __init__(self, model_cfg, grid_size, point_cloud_range, depth_downsample_factor, **kwargs):
super().__init__(model_cfg=model_cfg)
self.grid_size = grid_size
self.pc_... | 2,526 | 28.383721 | 99 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/depth_ffn.py | import torch.nn as nn
import torch.nn.functional as F
from . import ddn, ddn_loss
from pcdet.models.model_utils.basic_block_2d import BasicBlock2D
class DepthFFN(nn.Module):
def __init__(self, model_cfg, downsample_factor):
"""
Initialize frustum feature network via depth distribution estimation... | 3,778 | 35.336538 | 96 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn/ddn_deeplabv3.py | from .ddn_template import DDNTemplate
try:
import torchvision
except:
pass
class DDNDeepLabV3(DDNTemplate):
def __init__(self, backbone_name, **kwargs):
"""
Initializes DDNDeepLabV3 model
Args:
backbone_name: string, ResNet Backbone Name [ResNet50/ResNet101]
"... | 674 | 26 | 77 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn/ddn_template.py | from collections import OrderedDict
from pathlib import Path
from torch import hub
import torch
import torch.nn as nn
import torch.nn.functional as F
try:
from kornia.enhance.normalize import normalize
except:
pass
# print('Warning: kornia is not installed. This package is only required by CaDDN')
c... | 5,941 | 35.453988 | 106 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn_loss/balancer.py | import torch
import torch.nn as nn
from pcdet.utils import loss_utils
class Balancer(nn.Module):
def __init__(self, fg_weight, bg_weight, downsample_factor=1):
"""
Initialize fixed foreground/background loss balancer
Args:
fg_weight: float, Foreground loss weight
b... | 1,806 | 34.431373 | 102 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn_loss/ddn_loss.py | import torch
import torch.nn as nn
from .balancer import Balancer
from pcdet.utils import transform_utils
try:
from kornia.losses.focal import FocalLoss
except:
pass
# print('Warning: kornia is not installed. This package is only required by CaDDN')
class DDNLoss(nn.Module):
def __init__(self... | 2,428 | 30.960526 | 97 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/frustum_to_voxel.py | import torch
import torch.nn as nn
from .frustum_grid_generator import FrustumGridGenerator
from .sampler import Sampler
class FrustumToVoxel(nn.Module):
def __init__(self, model_cfg, grid_size, pc_range, disc_cfg):
"""
Initializes module to transform frustum features to voxel features via 3D tr... | 2,338 | 41.527273 | 109 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/frustum_grid_generator.py | import torch
import torch.nn as nn
try:
from kornia.utils.grid import create_meshgrid3d
from kornia.geometry.linalg import transform_points
except Exception as e:
# Note: Kornia team will fix this import issue to try to allow the usage of lower torch versions.
# print('Warning: kornia is not installed ... | 6,249 | 41.808219 | 201 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/sampler.py | import torch
import torch.nn as nn
import torch.nn.functional as F
class Sampler(nn.Module):
def __init__(self, mode="bilinear", padding_mode="zeros"):
"""
Initializes module
Args:
mode: string, Sampling mode [bilinear/nearest]
padding_mode: string, Padding mode fo... | 980 | 30.645161 | 111 | py |
3DTrans | 3DTrans-master/pcdet/models/active_models/discriminator.py | from xml.dom.minidom import DOMImplementation
import torch
import torch.nn as nn
import torch.nn.functional as F
import math
class ActiveDiscriminator(nn.Module):
def __init__(self, model_cfg):
super().__init__()
self.model_cfg = model_cfg
self.fc = nn.Linear(model_cfg['FEATURE_DIM'], 1)
... | 2,477 | 41.724138 | 163 | py |
3DTrans | 3DTrans-master/pcdet/models/active_models/discriminator_from_bev.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class BEVDiscriminator_Conv(nn.Module):
def __init__(self, model_cfg):
super().__init__()
c_in = model_cfg['FEATURE_DIM']
c_out = model_cfg['FEATURE_DIM'] // 4
self.c_out = c_out
self.block = nn.... | 13,106 | 42.115132 | 163 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/anchor_head_single.py | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from .anchor_head_template import AnchorHeadTemplate
class AnchorHeadSingle(AnchorHeadTemplate):
def __init__(self, model_cfg, input_channels, num_class, class_names, grid_size, point_cloud_range,
predict_boxes_... | 14,330 | 41.907186 | 178 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_head_template.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import common_utils, loss_utils
class PointHeadTemplate(nn.Module):
def __init__(self, model_cfg, num_class):
super().__init__()
self.model_cfg = model_cfg
... | 9,776 | 45.336493 | 119 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/anchor_head_template.py | import numpy as np
import torch
import torch.nn as nn
from ...utils import box_coder_utils, common_utils, loss_utils
from .target_assigner.anchor_generator import AnchorGenerator
from .target_assigner.atss_target_assigner import ATSSTargetAssigner
from .target_assigner.axis_aligned_target_assigner import AxisAlignedTa... | 12,364 | 43.800725 | 118 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/center_head_semi.py | import copy
import numpy as np
import torch
import torch.nn as nn
from torch.nn.init import kaiming_normal_
from ..model_utils import model_nms_utils
from ..model_utils import centernet_utils
from ...utils import loss_utils
class SeparateHead(nn.Module):
def __init__(self, input_channels, sep_head_dict, init_bias... | 18,189 | 44.588972 | 125 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/anchor_head_multi.py | import numpy as np
import torch
import torch.nn as nn
from ..backbones_2d import BaseBEVBackbone
from .anchor_head_template import AnchorHeadTemplate
class SingleHead(BaseBEVBackbone):
def __init__(self, model_cfg, input_channels, num_class, num_anchors_per_location, code_size, rpn_head_cfg=None,
... | 17,041 | 44.566845 | 117 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/center_head.py | import copy
import numpy as np
import torch
import torch.nn as nn
from torch.nn.init import kaiming_normal_
from ..model_utils import model_nms_utils
from ..model_utils import centernet_utils
from ...utils import loss_utils
class SeparateHead(nn.Module):
def __init__(self, input_channels, sep_head_dict, init_bias... | 30,472 | 45.101362 | 125 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/anchor_head_semi.py | import numpy as np
import torch.nn as nn
from .anchor_head_template import AnchorHeadTemplate
class AnchorHeadSemi(AnchorHeadTemplate):
def __init__(self, model_cfg, input_channels, num_class, class_names, grid_size, voxel_size, point_cloud_range,
predict_boxes_when_training=True):
super(... | 4,321 | 39.018519 | 136 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_head_box.py | import torch
from ...utils import box_coder_utils, box_utils
from .point_head_template import PointHeadTemplate
class PointHeadBox(PointHeadTemplate):
"""
A simple point-based segmentation head, which are used for PointRCNN.
Reference Paper: https://arxiv.org/abs/1812.04244
PointRCNN: 3D Object Propo... | 4,930 | 41.508621 | 106 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_head_simple.py | import torch
from ...utils import box_utils
from .point_head_template import PointHeadTemplate
class PointHeadSimple(PointHeadTemplate):
"""
A simple point-based segmentation head, which are used for PV-RCNN keypoint segmentaion.
Reference Paper: https://arxiv.org/abs/1912.13192
PV-RCNN: Point-Voxel ... | 4,255 | 39.150943 | 128 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_head_semi.py | import torch
from ...utils import box_utils
from .point_head_template import PointHeadTemplate
class PointHeadSemi(PointHeadTemplate):
"""
A simple point-based segmentation head, which are used for PV-RCNN keypoint segmentaion.
Reference Paper: https://arxiv.org/abs/1912.13192
PV-RCNN: Point-Voxel Fe... | 4,820 | 38.842975 | 128 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_intra_part_head.py | import torch
from ...utils import box_coder_utils, box_utils
from .point_head_template import PointHeadTemplate
class PointIntraPartOffsetHead(PointHeadTemplate):
"""
Point-based head for predicting the intra-object part locations.
Reference Paper: https://arxiv.org/abs/1907.03670
From Points to Part... | 5,568 | 42.507813 | 107 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/IASSD_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from ...utils import box_coder_utils, box_utils, loss_utils, common_utils
from .point_head_template import PointHeadTemplate
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
class IASSD_Head(PointHeadTemplate):
"""
A simple point-base... | 42,278 | 49.212589 | 259 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/target_assigner/anchor_generator.py | import torch
class AnchorGenerator(object):
def __init__(self, anchor_range, anchor_generator_config):
super().__init__()
self.anchor_generator_cfg = anchor_generator_config
self.anchor_range = anchor_range
self.anchor_sizes = [config['anchor_sizes'] for config in anchor_generator_... | 3,990 | 48.8875 | 122 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/target_assigner/axis_aligned_target_assigner.py | import numpy as np
import torch
from ....ops.iou3d_nms import iou3d_nms_utils
from ....utils import box_utils
class AxisAlignedTargetAssigner(object):
def __init__(self, model_cfg, class_names, box_coder, match_height=False):
super().__init__()
anchor_generator_cfg = model_cfg.ANCHOR_GENERATOR_C... | 10,465 | 47.453704 | 140 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/target_assigner/atss_target_assigner.py | import torch
from ....ops.iou3d_nms import iou3d_nms_utils
from ....utils import common_utils
class ATSSTargetAssigner(object):
"""
Reference: https://arxiv.org/abs/1912.02424
"""
def __init__(self, topk, box_coder, match_height=False):
self.topk = topk
self.box_coder = box_coder
... | 6,050 | 41.612676 | 117 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/roi_head_template.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from ...utils import box_coder_utils, common_utils, loss_utils
from ..model_utils.model_nms_utils import class_agnostic_nms
from .target_assigner.proposal_target_layer import ProposalTargetLayer
class RoIHeadTemplate(nn.Module):
... | 11,557 | 43.114504 | 128 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/voxelrcnn_head.py | import torch
import torch.nn as nn
from ...ops.pointnet2.pointnet2_stack import voxel_pool_modules as voxelpool_stack_modules
from ...utils import common_utils
from .roi_head_template import RoIHeadTemplate
class VoxelRCNNHead(RoIHeadTemplate):
def __init__(self, backbone_channels, model_cfg, point_cloud_range, v... | 41,813 | 45.876682 | 128 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/pvrcnn_head_semi.py | import torch.nn as nn
import torch
import torch.nn.functional as F
from ...ops.pointnet2.pointnet2_stack import pointnet2_modules as pointnet2_stack_modules
from ...utils import common_utils
from .roi_head_template import RoIHeadTemplate
class PVRCNNHeadSemi(RoIHeadTemplate):
def __init__(self, input_channels, mo... | 11,809 | 45.679842 | 123 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/partA2_head.py | import numpy as np
import torch
import torch.nn as nn
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils.spconv_utils import spconv
from .roi_head_template import RoIHeadTemplate
class PartA2FCHead(RoIHeadTemplate):
def __init__(self, input_channels, model_cfg, num_class=1, **kwargs):
... | 10,089 | 43.844444 | 120 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/pvrcnn_head_MoE.py | import torch.nn as nn
from ...ops.pointnet2.pointnet2_stack import pointnet2_modules as pointnet2_stack_modules
from ...utils import common_utils
from .roi_head_template import RoIHeadTemplate
class PVRCNNHeadMoE(RoIHeadTemplate):
def __init__(self, input_channels, model_cfg, num_class=1, **kwargs):
super... | 8,480 | 42.050761 | 116 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/pvrcnn_head.py | import torch.nn as nn
import torch
import torch.nn.functional as F
from ...ops.pointnet2.pointnet2_stack import pointnet2_modules as pointnet2_stack_modules
from ...utils import common_utils
from .roi_head_template import RoIHeadTemplate
class PVRCNNHead(RoIHeadTemplate):
def __init__(self, input_channels, model_... | 15,017 | 41.543909 | 116 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/second_head.py | import torch
import torch.nn as nn
from .roi_head_template import RoIHeadTemplate
from ...utils import common_utils, loss_utils
class SECONDHead(RoIHeadTemplate):
def __init__(self, input_channels, model_cfg, num_class=1, **kwargs):
super().__init__(num_class=num_class, model_cfg=model_cfg)
self.m... | 15,196 | 41.449721 | 120 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/pointrcnn_head.py | import torch
import torch.nn as nn
from ...ops.pointnet2.pointnet2_batch import pointnet2_modules
from ...ops.roipoint_pool3d import roipoint_pool3d_utils
from ...utils import common_utils
from .roi_head_template import RoIHeadTemplate
class PointRCNNHead(RoIHeadTemplate):
def __init__(self, input_channels, mode... | 7,835 | 42.533333 | 116 | py |
3DTrans | 3DTrans-master/pcdet/models/roi_heads/target_assigner/proposal_target_layer.py | import numpy as np
import torch
import torch.nn as nn
from ....ops.iou3d_nms import iou3d_nms_utils
class ProposalTargetLayer(nn.Module):
def __init__(self, roi_sampler_cfg):
super().__init__()
self.roi_sampler_cfg = roi_sampler_cfg
def forward(self, batch_dict):
"""
Args:
... | 10,343 | 43.779221 | 126 | py |
3DTrans | 3DTrans-master/pcdet/models/model_utils/centernet_utils.py | # This file is modified from https://github.com/tianweiy/CenterPoint
import torch
import torch.nn.functional as F
import numpy as np
import numba
def gaussian_radius(height, width, min_overlap=0.5):
"""
Args:
height: (N)
width: (N)
min_overlap:
Returns:
"""
a1 = 1
b1 =... | 7,932 | 33.04721 | 111 | py |
3DTrans | 3DTrans-master/pcdet/models/model_utils/model_nms_utils.py | import torch
from ...ops.iou3d_nms import iou3d_nms_utils
def class_agnostic_nms(box_scores, box_preds, nms_config, score_thresh=None):
src_box_scores = box_scores
if score_thresh is not None:
scores_mask = (box_scores >= score_thresh)
box_scores = box_scores[scores_mask]
box_preds = ... | 3,422 | 37.460674 | 116 | py |
3DTrans | 3DTrans-master/pcdet/models/model_utils/basic_block_2d.py | import torch.nn as nn
class BasicBlock2D(nn.Module):
def __init__(self, in_channels, out_channels, **kwargs):
"""
Initializes convolutional block
Args:
in_channels: int, Number of input channels
out_channels: int, Number of output channels
**kwargs: Dic... | 1,038 | 28.685714 | 60 | py |
3DTrans | 3DTrans-master/pcdet/models/model_utils/ensemble.py | """
This file is to match with previous version of CenterPoint model
"""
import torch
import numpy as np
from .wbf_3d import weighted_boxes_fusion_3d
def wbf_online(boxes, scores, labels):
device = boxes.device
dtype = boxes.dtype
boxes_list = boxes.cpu().numpy()
scores_list = scores.cpu().numpy()
... | 1,000 | 24.025 | 64 | py |
3DTrans | 3DTrans-master/pcdet/models/model_utils/wbf_3d.py | """
This file is to match with previous version of CenterPoint model
"""
import copy
import numpy as np
import torch
from ...ops.iou3d_nms import iou3d_nms_utils
def prefilter_boxes(boxes, scores, labels, weights, thresh):
# Create dict with boxes stored by its label
new_boxes = dict()
for i in range(... | 6,649 | 35.141304 | 118 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_2d/base_bev_backbone.py | import numpy as np
import torch
import torch.nn as nn
# from ...utils import uni3d_norm
from ...utils import uni3d_norm as uni3d_norm_used
# from ...utils import uni3d_norm_parallel as uni3d_norm_used
class BaseBEVBackbone(nn.Module):
def __init__(self, model_cfg, input_channels):
super().__init__()
... | 7,589 | 43.127907 | 157 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_2d/map_to_bev/conv2d_collapse.py | import torch
import torch.nn as nn
from pcdet.models.model_utils.basic_block_2d import BasicBlock2D
class Conv2DCollapse(nn.Module):
def __init__(self, model_cfg, grid_size):
"""
Initializes 2D convolution collapse module
Args:
model_cfg: EasyDict, Model configuration
... | 1,451 | 36.230769 | 106 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_2d/map_to_bev/pointpillar_scatter.py | import torch
import torch.nn as nn
class PointPillarScatter(nn.Module):
def __init__(self, model_cfg, grid_size, **kwargs):
super().__init__()
self.model_cfg = model_cfg
self.num_bev_features = self.model_cfg.NUM_BEV_FEATURES
self.nx, self.ny, self.nz = grid_size
assert se... | 1,545 | 39.684211 | 123 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_2d/map_to_bev/height_compression.py | import torch.nn as nn
class HeightCompression(nn.Module):
def __init__(self, model_cfg, **kwargs):
super().__init__()
self.model_cfg = model_cfg
self.num_bev_features = self.model_cfg.NUM_BEV_FEATURES
def forward(self, batch_dict):
"""
Args:
batch_dict:
... | 870 | 31.259259 | 90 | py |
3DTrans | 3DTrans-master/pcdet/datasets/dataset.py | import torch
import copy
from pathlib import Path
from collections import defaultdict
import numpy as np
import torch.utils.data as torch_data
from .augmentor.data_augmentor import DataAugmentor
from .processor.data_processor import DataProcessor
from .processor.point_feature_encoder import PointFeatureEncoder
from ..u... | 15,032 | 40.527624 | 118 | py |
3DTrans | 3DTrans-master/pcdet/datasets/semi_dataset.py | from collections import defaultdict
from pathlib import Path
import copy
import numpy as np
import torch.utils.data as torch_data
from ..utils import common_utils
from .augmentor.data_augmentor import DataAugmentor
from .augmentor.ssl_data_augmentor import SSLDataAugmentor
from .processor.data_processor import DataPro... | 18,381 | 41.848485 | 179 | py |
3DTrans | 3DTrans-master/pcdet/datasets/__init__.py | import torch
from torch.utils.data import DataLoader
from torch.utils.data import DistributedSampler as _DistributedSampler
from pcdet.utils import common_utils
from .dataset import DatasetTemplate
from .kitti.kitti_dataset import KittiDataset
from .kitti.kitti_dataset_ada import ActiveKittiDataset
from .nuscenes.nus... | 13,075 | 36.36 | 164 | py |
3DTrans | 3DTrans-master/pcdet/datasets/waymo/waymo_dataset.py | # OpenPCDet PyTorch Dataloader and Evaluation Tools for Waymo Open Dataset
# Reference https://github.com/open-mmlab/OpenPCDet
# Written by Shaoshuai Shi, Chaoxu Guo
# All Rights Reserved 2019-2020.
import os
import io
import pickle
import copy
import numpy as np
import torch
import multiprocessing
import SharedArray
... | 28,281 | 44.035032 | 139 | py |
3DTrans | 3DTrans-master/pcdet/datasets/waymo/waymo_dataset_ada.py | import os
import io
import pickle
import copy
import numpy as np
import torch
import multiprocessing
import SharedArray
import torch.distributed as dist
from tqdm import tqdm
from pathlib import Path
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import box_utils, common_utils
from ..dataset imp... | 28,867 | 44.247649 | 139 | py |
3DTrans | 3DTrans-master/pcdet/datasets/once/once_dataset.py | import copy
import pickle
import os
import numpy as np
from PIL import Image
import torch
import torch.nn.functional as F
from pathlib import Path
from ..dataset import DatasetTemplate
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import box_utils
from .once_toolkits import Octopus
# Since w... | 18,925 | 39.353945 | 140 | py |
3DTrans | 3DTrans-master/pcdet/datasets/once/once_target_dataset.py | import copy
import pickle
import numpy as np
from ..dataset import DatasetTemplate
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import box_utils
from .once_toolkits import Octopus
class ONCEDataset(DatasetTemplate):
def __init__(self, dataset_cfg, class_names, training=True, root_path=No... | 20,276 | 39.554 | 140 | py |
3DTrans | 3DTrans-master/pcdet/datasets/once/once_dataset_ada.py | import copy
import pickle
import os
import numpy as np
from PIL import Image
import torch
import torch.nn.functional as F
from pathlib import Path
from ..dataset import DatasetTemplate
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import box_utils
from .once_toolkits import Octopus
# Since w... | 20,079 | 39.89613 | 140 | py |
3DTrans | 3DTrans-master/pcdet/datasets/lyft/lyft_dataset_ada.py | import copy
import pickle
from pathlib import Path
import os
import io
import numpy as np
from tqdm import tqdm
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import common_utils, box_utils
from ..dataset import DatasetTemplate
class ActiveLyftDataset(DatasetTemplate):
"""Petrel Ceph sto... | 22,729 | 44.009901 | 146 | py |
3DTrans | 3DTrans-master/pcdet/datasets/lyft/lyft_dataset.py | import copy
import pickle
from pathlib import Path
import os
import io
import numpy as np
from tqdm import tqdm
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import common_utils, box_utils
from ..dataset import DatasetTemplate
class LyftDataset(DatasetTemplate):
"""Petrel Ceph storage b... | 20,471 | 43.12069 | 146 | py |
3DTrans | 3DTrans-master/pcdet/datasets/augmentor/augmentor_utils.py | import torch
import numpy as np
import numba
import math
import copy
from ...utils import common_utils
from ...utils import box_utils
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...ops.iou3d_nms import iou3d_nms_utils
import warnings
try:
from numba.errors import NumbaPerformanceWarning
warn... | 35,553 | 37.3125 | 126 | py |
3DTrans | 3DTrans-master/pcdet/datasets/augmentor/database_sampler.py | import pickle
import os
import copy
import numpy as np
import SharedArray
import torch.distributed as dist
from ...ops.iou3d_nms import iou3d_nms_utils
from ...utils import box_utils, common_utils
import os
import io
class DataBaseSampler(object):
def __init__(self, root_path, sampler_cfg, class_names, logger=No... | 11,921 | 42.510949 | 120 | py |
3DTrans | 3DTrans-master/pcdet/datasets/nuscenes/nuscenes_utils.py | """
The NuScenes data pre-processing and evaluation is modified from
https://github.com/traveller59/second.pytorch and https://github.com/poodarchu/Det3D
"""
import operator
from functools import reduce
from pathlib import Path
import numpy as np
import tqdm
from nuscenes.utils.data_classes import Box
from nuscenes.u... | 19,464 | 36.005703 | 111 | py |
3DTrans | 3DTrans-master/pcdet/datasets/nuscenes/nuscenes_dataset.py | import copy
import pickle
from pathlib import Path
import os
import io
import numpy as np
from tqdm import tqdm
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import common_utils
from ..dataset import DatasetTemplate
class NuScenesDataset(DatasetTemplate):
"""Petrel Ceph storage backend.... | 22,903 | 42.461101 | 129 | py |
3DTrans | 3DTrans-master/pcdet/datasets/nuscenes/nuscenes_dataset_ada.py | import copy
import pickle
from pathlib import Path
import os
import io
import numpy as np
from tqdm import tqdm
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import common_utils
from ..dataset import DatasetTemplate
class ActiveNuScenesDataset(DatasetTemplate):
"""Petrel Ceph storage ba... | 23,617 | 42.899628 | 130 | py |
3DTrans | 3DTrans-master/pcdet/datasets/pandaset/pandaset_dataset.py | """
Dataset from Pandaset (Hesai)
"""
import pickle
import os
try:
import pandas as pd
import pandaset as ps
except:
pass
import numpy as np
from ..dataset import DatasetTemplate
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
import torch
def pose_dict_to_numpy(pose):
"""
Con... | 19,065 | 37.910204 | 157 | py |
3DTrans | 3DTrans-master/pcdet/datasets/kitti/kitti_dataset_ada.py | import copy
import pickle
import os
from random import sample
import numpy as np
from pathlib import Path
from . import kitti_utils
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import box_utils, calibration_kitti, common_utils, object3d_kitti
from ..dataset import DatasetTemplate
# using from... | 25,584 | 43.036145 | 140 | py |
3DTrans | 3DTrans-master/pcdet/datasets/kitti/kitti_dataset.py | import copy
import pickle
import os
import numpy as np
from . import kitti_utils
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import box_utils, calibration_kitti, common_utils, object3d_kitti
from ..dataset import DatasetTemplate
# using from skimage import io when preprocessing the KITTI
# ... | 24,946 | 42.766667 | 140 | py |
3DTrans | 3DTrans-master/pcdet/utils/box_utils.py | import numpy as np
import scipy
import torch
import copy
from scipy.spatial import Delaunay
from ..ops.roiaware_pool3d import roiaware_pool3d_utils
from . import common_utils
def in_hull(p, hull):
"""
:param p: (N, K) test points
:param hull: (M, K) M corners of a box
:return (N) bool
"""
try... | 11,158 | 33.981191 | 118 | py |
3DTrans | 3DTrans-master/pcdet/utils/loss_utils.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from . import box_utils
class SigmoidFocalClassificationLoss(nn.Module):
"""
Sigmoid focal cross entropy loss.
"""
def __init__(self, gamma: float = 2.0, alpha: float = 0.25):
"""
Args:
... | 20,744 | 32.622366 | 107 | py |
3DTrans | 3DTrans-master/pcdet/utils/box_coder_utils.py | import numpy as np
import torch
class ResidualCoder(object):
def __init__(self, code_size=7, encode_angle_by_sincos=False, **kwargs):
super().__init__()
self.code_size = code_size
self.encode_angle_by_sincos = encode_angle_by_sincos
if self.encode_angle_by_sincos:
self.... | 17,075 | 36.041215 | 123 | py |
3DTrans | 3DTrans-master/pcdet/utils/active_learning_2D_utils.py | import enum
import io
import os
import tqdm
import pickle
import random
import torch
import numpy as np
import torch.nn as nn
import torch.distributed as dist
import torch.nn.functional as F
from pathlib import Path
from pcdet.models import load_data_to_gpu
from pcdet.utils import common_utils, commu_utils
from sklearn... | 12,079 | 36.055215 | 127 | py |
3DTrans | 3DTrans-master/pcdet/utils/common_utils.py | import logging
import os
import pickle
import random
import shutil
import subprocess
import SharedArray
import numpy as np
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
from torch.autograd import Variable,Function
from ..utils.spconv_utils import spconv
def check_numpy_to_torch(x):... | 25,895 | 34.966667 | 137 | py |
3DTrans | 3DTrans-master/pcdet/utils/uni3d_norm_2_in.py | import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
import torch
import itertools
class _UniNorm(Module):
def __init__(self, num_features, dataset_from_flag=1, eps=1e-5, momentum=0.1, affine=True, track_running_stats=True, voxel... | 19,844 | 46.362768 | 140 | py |
3DTrans | 3DTrans-master/pcdet/utils/transform_utils.py | import math
import torch
try:
from kornia.geometry.conversions import (
convert_points_to_homogeneous,
convert_points_from_homogeneous,
)
except:
pass
# print('Warning: kornia is not installed. This package is only required by CaDDN')
def project_to_image(project, points):
"""
... | 3,092 | 32.619565 | 104 | py |
3DTrans | 3DTrans-master/pcdet/utils/uni3d_norm_parallel.py | import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
import torch
import itertools
class _UniNorm(Module):
def __init__(self, num_features, dataset_from_flag=1, eps=1e-5, momentum=0.1, affine=True, track_running_stats=True, voxel... | 20,022 | 46.112941 | 149 | py |
3DTrans | 3DTrans-master/pcdet/utils/uni3d_norm.py | import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
import torch
import itertools
class _UniNorm(Module):
def __init__(self, num_features, dataset_from_flag=1, eps=1e-5, momentum=0.1, affine=True, track_running_stats=True, voxel... | 21,012 | 46.648526 | 149 | py |
3DTrans | 3DTrans-master/pcdet/utils/self_training_utils.py | import torch
import os
import glob
import tqdm
import numpy as np
import torch.distributed as dist
from pcdet.config import cfg
from pcdet.models import load_data_to_gpu
from pcdet.utils import common_utils, commu_utils, memory_ensemble_utils
import pickle as pkl
import re
#PSEUDO_LABELS = {}
from multiprocessing impo... | 8,934 | 35.769547 | 95 | py |
3DTrans | 3DTrans-master/pcdet/utils/spconv_utils.py | from typing import Set
try:
import spconv.pytorch as spconv
except:
import spconv as spconv
import torch.nn as nn
def find_all_spconv_keys(model: nn.Module, prefix="") -> Set[str]:
"""
Finds all spconv keys that need to have weight's transposed
"""
found_keys: Set[str] = set()
for name, ... | 896 | 24.628571 | 73 | py |
3DTrans | 3DTrans-master/pcdet/utils/active_learning_utils.py | import io
import os
import tqdm
import pickle
import random
import torch
import numpy as np
import torch.distributed as dist
import torch.nn.functional as F
from pathlib import Path
from pcdet.models import load_data_to_gpu
from pcdet.utils import common_utils, commu_utils
def active_evaluate(model, target_loader, r... | 15,595 | 40.589333 | 191 | py |
3DTrans | 3DTrans-master/pcdet/utils/memory_ensemble_utils.py | import torch
import numpy as np
from scipy.optimize import linear_sum_assignment
from pcdet.utils import common_utils
from pcdet.ops.iou3d_nms import iou3d_nms_utils
from pcdet.models.model_utils.model_nms_utils import class_agnostic_nms
def consistency_ensemble(gt_infos_a, gt_infos_b, memory_ensemble_cfg):
"""
... | 14,715 | 41.90379 | 117 | py |
3DTrans | 3DTrans-master/pcdet/utils/commu_utils.py | """
This file contains primitives for multi-gpu communication.
This is useful when doing distributed training.
deeply borrow from maskrcnn-benchmark and ST3D
"""
import pickle
import time
import torch
import torch.distributed as dist
def get_world_size():
if not dist.is_available():
return 1
if not... | 5,253 | 27.710383 | 89 | py |
3DTrans | 3DTrans-master/pcdet/ops/roipoint_pool3d/roipoint_pool3d_utils.py | import torch
import torch.nn as nn
from torch.autograd import Function
from ...utils import box_utils
from . import roipoint_pool3d_cuda
class RoIPointPool3d(nn.Module):
def __init__(self, num_sampled_points=512, pool_extra_width=1.0):
super().__init__()
self.num_sampled_points = num_sampled_poin... | 2,226 | 31.75 | 112 | py |
3DTrans | 3DTrans-master/pcdet/ops/pointnet2/pointnet2_stack/voxel_query_utils.py | import torch
from torch.autograd import Variable
from torch.autograd import Function
import torch.nn as nn
from typing import List
from . import pointnet2_stack_cuda as pointnet2
from . import pointnet2_utils
class VoxelQuery(Function):
@staticmethod
def forward(ctx, max_range: int, radius: float, nsample: i... | 4,148 | 40.079208 | 134 | py |
3DTrans | 3DTrans-master/pcdet/ops/pointnet2/pointnet2_stack/pointnet2_utils.py | import torch
import torch.nn as nn
from torch.autograd import Function, Variable
from . import pointnet2_stack_cuda as pointnet2
class BallQuery(Function):
@staticmethod
def forward(ctx, radius: float, nsample: int, xyz: torch.Tensor, xyz_batch_cnt: torch.Tensor,
new_xyz: torch.Tensor, new_x... | 18,073 | 38.462882 | 127 | py |
3DTrans | 3DTrans-master/pcdet/ops/pointnet2/pointnet2_stack/voxel_pool_modules.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from . import voxel_query_utils
from typing import List
class NeighborVoxelSAModuleMSG(nn.Module):
def __init__(self, *, query_ranges: List[List[int]], radii: List[float],
nsamples: List[int], mlps: List[List[int]], use_... | 5,672 | 41.977273 | 108 | py |
3DTrans | 3DTrans-master/pcdet/ops/pointnet2/pointnet2_stack/pointnet2_modules.py | from typing import List
import torch
import torch.nn as nn
import torch.nn.functional as F
from . import pointnet2_utils
def build_local_aggregation_module(input_channels, config):
local_aggregation_name = config.get('NAME', 'StackSAModuleMSG')
if local_aggregation_name == 'StackSAModuleMSG':
mlps ... | 21,385 | 44.40552 | 132 | py |
3DTrans | 3DTrans-master/pcdet/ops/pointnet2/pointnet2_batch/pointnet2_utils.py | from typing import Tuple
import torch
import torch.nn as nn
from torch.autograd import Function, Variable
from . import pointnet2_batch_cuda as pointnet2
class FarthestPointSampling(Function):
@staticmethod
def forward(ctx, xyz: torch.Tensor, npoint: int) -> torch.Tensor:
"""
Uses iterative ... | 9,717 | 32.395189 | 118 | py |
3DTrans | 3DTrans-master/pcdet/ops/pointnet2/pointnet2_batch/pointnet2_modules.py | from typing import List
import torch
import torch.nn as nn
import torch.nn.functional as F
from . import pointnet2_utils
class _PointnetSAModuleBase(nn.Module):
def __init__(self):
super().__init__()
self.npoint = None
self.groupers = None
self.mlps = None
self.pool_meth... | 22,835 | 43.341748 | 196 | py |
3DTrans | 3DTrans-master/pcdet/ops/iou3d_nms/iou3d_nms_utils.py | """
3D IoU Calculation and Rotated NMS
Written by Shaoshuai Shi
All Rights Reserved 2019-2020.
"""
import torch
from ...utils import common_utils
from . import iou3d_nms_cuda
def boxes_bev_iou_cpu(boxes_a, boxes_b):
"""
Args:
boxes_a: (N, 7) [x, y, z, dx, dy, dz, heading]
boxes_b: (M, 7) [x, ... | 3,673 | 30.401709 | 109 | py |
3DTrans | 3DTrans-master/pcdet/ops/roiaware_pool3d/roiaware_pool3d_utils.py | import torch
import torch.nn as nn
from torch.autograd import Function
from ...utils import common_utils
from . import roiaware_pool3d_cuda
def points_in_boxes_cpu(points, boxes):
"""
Args:
points: (num_points, 3)
boxes: [x, y, z, dx, dy, dz, heading], (x, y, z) is the box center, each box DO... | 4,075 | 35.392857 | 120 | py |
GPTScore | GPTScore-main/opt_score.py | # %%
import torch
import torch.nn as nn
import traceback
from transformers import BartTokenizer, BartForConditionalGeneration
from transformers import GPT2Tokenizer, OPTForCausalLM, GPT2LMHeadModel, GPTJForCausalLM
class OPTScorer:
def __init__(self, device='cuda:0', max_length=1024, checkpoint=None):
# Se... | 3,445 | 41.54321 | 94 | py |
GPTScore | GPTScore-main/flan_score.py | # %%
import torch
import torch.nn as nn
import traceback
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
class FLANScorer:
def __init__(self, device='cuda:0', max_length=1024, checkpoint='google/flan-t5-base'):
# Set up model
self.device = device
self.max_length = max_length
... | 2,981 | 39.849315 | 97 | py |
pytorch-boat | pytorch-boat-main/BOAT-CSWin/main.py | # ------------------------------------------
# CSWin Transformer
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# written By Xiaoyi Dong
# ------------------------------------------
import argparse
import time
import yaml
import os
import logging
from collections import OrderedDict
from conte... | 36,210 | 46.272846 | 133 | py |
pytorch-boat | pytorch-boat-main/BOAT-CSWin/labeled_memcached_dataset.py | # ------------------------------------------
# CSWin Transformer
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# written By Xiaoyi Dong
# ------------------------------------------
from torch.utils.data import Dataset
import numpy as np
import io
from PIL import Image
import os
import json
i... | 1,700 | 29.375 | 80 | py |
pytorch-boat | pytorch-boat-main/BOAT-CSWin/finetune.py | # ------------------------------------------
# CSWin Transformer
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# written By Xiaoyi Dong
# ------------------------------------------
import argparse
import time
import yaml
import os
import logging
from collections import OrderedDict
from conte... | 43,476 | 45.900755 | 134 | py |
pytorch-boat | pytorch-boat-main/BOAT-CSWin/checkpoint_saver.py | # ------------------------------------------
# CSWin Transformer
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# written By Xiaoyi Dong
# ------------------------------------------
import glob
import operator
import os
import logging
import torch
from timm.utils.model import unwrap_model, ... | 6,397 | 39.751592 | 104 | py |
pytorch-boat | pytorch-boat-main/BOAT-CSWin/segmentation/backbone/cswin_transformer.py | # ------------------------------------------
# CSWin Transformer
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# written By Xiaoyi Dong
# ------------------------------------------
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
from timm.da... | 14,811 | 35.126829 | 145 | py |
pytorch-boat | pytorch-boat-main/BOAT-CSWin/segmentation/mmcv_custom/checkpoint.py | # Copyright (c) Open-MMLab. All rights reserved.
import io
import os
import os.path as osp
import pkgutil
import time
import warnings
from collections import OrderedDict
from importlib import import_module
from tempfile import TemporaryDirectory
import torch
import torchvision
from torch.optim import Optimizer
from to... | 19,055 | 36.884692 | 110 | py |
pytorch-boat | pytorch-boat-main/BOAT-CSWin/models/cswin_boat.py | # ------------------------------------------
# CSWin Transformer
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# written By Xiaoyi Dong
# ------------------------------------------
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
from timm.da... | 20,463 | 38.353846 | 183 | py |
pytorch-boat | pytorch-boat-main/BOAT-Swin/main.py | # --------------------------------------------------------
# Swin Transformer
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ze Liu
# --------------------------------------------------------
import os
import time
import random
import argparse
import datetime
impo... | 14,809 | 40.368715 | 117 | py |
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