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/FCOS3D/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/FCOS3D/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/FCOS3D/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/FCOS3D/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/FCOS3D/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/FCOS3D/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/FCOS3D/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/FCOS3D/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/FCOS3D/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/FCOS3D/projects/config/fcos3d.py | model = dict(
type='FCOSMono3D',
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,
style='caffe',
init_cfg=dict(
type... | 2,432 | 29.797468 | 77 | py |
RoboBEV | RoboBEV-master/zoo/FCOS3D/projects/config/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'
# Evaluating bboxes of img_bbox
# mAP: 0.3214... | 1,268 | 39.935484 | 173 | py |
RoboBEV | RoboBEV-master/zoo/FCOS3D/projects/config/robust_test/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'
# Evaluating bboxes of img_bbox
# mAP: 0.3214... | 1,268 | 39.935484 | 173 | py |
RoboBEV | RoboBEV-master/zoo/FCOS3D/projects/mmdet3d_plugin/datasets/uda_nuscenes.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
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 Box3DMode, Coor... | 26,089 | 38.832061 | 154 | py |
RoboBEV | RoboBEV-master/zoo/FCOS3D/projects/mmdet3d_plugin/datasets/uda_nuscenes_mono.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... | 32,692 | 39.86625 | 154 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/setup.py | from setuptools import find_packages, setup
import os
import shutil
import sys
import torch
import warnings
from os import path as osp
from torch.utils.cpp_extension import (BuildExtension, CppExtension,
CUDAExtension)
def readme():
with open('README.md', encoding='utf-8') ... | 11,944 | 36.211838 | 125 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/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
def parse_args():
... | 4,414 | 34.32 | 128 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tools/test.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import mmcv
import os
import torch
import warnings
from mmcv import Config, DictAction
from mmcv.cnn import fuse_conv_bn
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (get_dist_info, init_dist, load_checkpoint,... | 9,803 | 39.512397 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/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... | 11,601 | 39.284722 | 94 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tools/swap_ema_and_non_ema.py | import torch
import sys
import os
def swap_ema_and_non_ema(load_path):
assert ".pth" in load_path
assert os.path.exists(load_path), load_path
ckpt = torch.load(load_path, map_location='cpu')
#
for k in list(ckpt['state_dict'].keys()):
if k[:4] != "ema_":
ema_name = f"ema_{k.r... | 940 | 26.676471 | 68 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tools/train.py | # Copyright (c) OpenMMLab. All rights reserved.
from __future__ import division
import argparse
import copy
import mmcv
import os
import time
import torch
import warnings
from mmcv import Config, DictAction
from mmcv.runner import get_dist_info, init_dist
from os import path as osp
from mmdet import __version__ as mm... | 8,626 | 36.508696 | 125 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/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/SOLOFusion/tools/misc/fuse_conv_bn.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import torch
from mmcv.runner import save_checkpoint
from torch import nn as nn
from mmdet3d.apis import init_model
def fuse_conv_bn(conv, bn):
"""During inference, the functionary of batch norm layers is turned off but
only the mean and var alo... | 2,242 | 31.985294 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/tools/analysis_tools/get_flops.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import torch
from mmcv import Config, DictAction
from mmdet3d.models import build_model
try:
from mmcv.cnn import get_model_complexity_info
except ImportError:
raise ImportError('Please upgrade mmcv to >0.6.2')
def parse_args():
parser = ar... | 3,578 | 31.834862 | 100 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tools/analysis_tools/visual.py | # Based on https://github.com/nutonomy/nuscenes-devkit
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
# Modified by Shaoyuan Xie
# ---------------------------------------------
import mmcv
import os
from nuscenes.nuscenes import NuScenes
from PI... | 27,938 | 42.929245 | 156 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/docs_zh-CN/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 6,384 | 30.925 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/.dev_scripts/gather_models.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Script to gather benchmarked models and prepare them for upload.
Usage:
python gather_models.py ${root_path} ${out_dir}
"""
import argparse
import glob
import json
import mmcv
import shutil
import subprocess
import torch
from os import path as osp
# build schedule l... | 7,117 | 31.502283 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_runtime/test_config.py | # Copyright (c) OpenMMLab. All rights reserved.
from os.path import dirname, exists, join, relpath
def _get_config_directory():
"""Find the predefined detector config directory."""
try:
# Assume we are running in the source mmdetection3d repo
repo_dpath = dirname(dirname(dirname(__file__)))
... | 10,571 | 37.304348 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_runtime/test_apis.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import os
import pytest
import tempfile
import torch
from mmcv.parallel import MMDataParallel
from os.path import dirname, exists, join
from mmdet3d.apis import (convert_SyncBN, inference_detector,
inference_mono_3d_detector,
... | 15,732 | 42.461326 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_detectors.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import random
import torch
from os.path import dirname, exists, join
from mmdet3d.core.bbox import (CameraInstance3DBoxes, DepthInstance3DBoxes,
LiDARInstance3DBoxes)
from mmdet3d.models.builder ... | 17,930 | 36.989407 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_forward.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Test model forward process.
CommandLine:
pytest tests/test_models/test_forward.py
xdoctest tests/test_models/test_forward.py zero
"""
import copy
import numpy as np
import torch
from os.path import dirname, exists, join
def _get_config_directory():
"""Fi... | 6,212 | 28.727273 | 78 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_backbones.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.models import build_backbone
def test_pointnet2_sa_ssg():
if not torch.cuda.is_available():
pytest.skip()
cfg = dict(
type='PointNet2SASSG',
in_channels=6,
num_points=(3... | 12,167 | 39.56 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_segmentors.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import torch
from os.path import dirname, exists, join
from mmdet3d.models.builder import build_segmentor
from mmdet.apis import set_random_seed
def _get_config_directory():
"""Find the predefined detector config directo... | 12,345 | 39.214984 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_voxel_encoder/test_voxelize.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.voxel.voxel_generator import VoxelGenerator
from mmdet3d.datasets.pipelines import LoadPointsFromFile
from mmdet3d.ops.voxel.voxelize import Voxelization
def _get_voxel_points_indices(points, coors, voxel)... | 6,729 | 39.542169 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_voxel_encoder/test_dynamic_scatter.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from torch.autograd import gradcheck
from mmdet3d.ops import DynamicScatter
def test_dynamic_scatter():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
dsmean = DynamicScatter([0.32, 0.32, 6]... | 5,497 | 40.969466 | 78 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_voxel_encoder/test_voxel_encoders.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.models.builder import build_voxel_encoder
def test_pillar_feature_net():
pillar_feature_net_cfg = dict(
type='PillarFeatureNet',
in_channels=5,
feat_channels=[64],
with_distance=False,
voxel_size=(0.... | 1,146 | 31.771429 | 68 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_fusion/test_point_fusion.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Tests the core function of point fusion.
CommandLine:
pytest tests/test_models/test_fusion/test_point_fusion.py
"""
import torch
from mmdet3d.models.fusion_layers import PointFusion
def test_sample_single():
# this function makes sure the rewriting of 3d c... | 2,123 | 33.258065 | 75 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_fusion/test_vote_fusion.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Tests the core function of vote fusion.
CommandLine:
pytest tests/test_models/test_fusion/test_vote_fusion.py
"""
import torch
from mmdet3d.models.fusion_layers import VoteFusion
def test_vote_fusion():
img_meta = {
'ori_shape': (530, 730, 3),
... | 14,832 | 44.922601 | 78 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_fusion/test_fusion_coord_trans.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Tests coords transformation in fusion modules.
CommandLine:
pytest tests/test_models/test_fusion/test_fusion_coord_trans.py
"""
import torch
from mmdet3d.models.fusion_layers import apply_3d_transformation
def test_coords_transformation():
"""Test the tran... | 4,958 | 34.934783 | 76 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_common_modules/test_roiaware_pool3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.ops.roiaware_pool3d import (RoIAwarePool3d, points_in_boxes_batch,
points_in_boxes_cpu,
points_in_boxes_gpu)
def test_RoIAwarePool3d():
# RoIAw... | 5,798 | 43.607692 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_common_modules/test_vote_module.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
def test_vote_module():
from mmdet3d.models.model_utils import VoteModule
vote_loss = dict(
type='ChamferDistance',
mode='l1',
reduction='none',
loss_dst_weight=10.0)
self = VoteModule(vote_per_seed=3, in_channel... | 1,380 | 33.525 | 77 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_common_modules/test_paconv_modules.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
def test_paconv_sa_module_msg():
if not torch.cuda.is_available():
pytest.skip()
from mmdet3d.ops import PAConvSAModuleMSG
# paconv_num_kernels should have same length as mlp_channels
with pytest.rai... | 10,480 | 33.820598 | 74 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_common_modules/test_pointnet_ops.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.ops import (ball_query, furthest_point_sample,
furthest_point_sample_with_dist, gather_points,
grouping_operation, knn, three_interpolate, three_nn)
def test_fps():
if not tor... | 20,649 | 49.862069 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_common_modules/test_middle_encoders.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.models.builder import build_middle_encoder
def test_sparse_encoder():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
sparse_encoder_cfg = dict(
type='SparseEncoder',
... | 1,036 | 36.035714 | 76 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_common_modules/test_paconv_ops.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.ops import PAConv, PAConvCUDA, assign_score_withk
def test_paconv_assign_scores():
if not torch.cuda.is_available():
pytest.skip()
scores = torch.tensor([[[[0.06947571, 0.6065746], [0.28462553, 0.8378516],
... | 12,945 | 54.562232 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_common_modules/test_pointnet_modules.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
def test_pointnet_sa_module_msg():
if not torch.cuda.is_available():
pytest.skip()
from mmdet3d.ops import PointSAModuleMSG
self = PointSAModuleMSG(
num_point=16,
radii=[0.2, 0.4],
... | 7,125 | 31.244344 | 74 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_common_modules/test_sparse_unet.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.ops import SparseBasicBlock
from mmdet3d.ops import spconv as spconv
def test_SparseUNet():
from mmdet3d.models.middle_encoders.sparse_unet import SparseUNet
self = SparseUNet(in_channels=4, sparse_shape=[41, 1600, 1408])
# test e... | 5,844 | 41.355072 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_heads/test_roi_extractors.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.models.roi_heads.roi_extractors import Single3DRoIAwareExtractor
def test_single_roiaware_extractor():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
roi_layer_cfg = dict(
... | 1,313 | 40.0625 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_heads/test_semantic_heads.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.core.bbox import LiDARInstance3DBoxes
def test_PointwiseSemanticHead():
# PointwiseSemanticHead only support gpu version currently.
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')... | 3,037 | 35.60241 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_heads/test_paconv_decode_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmcv.cnn.bricks import ConvModule
from mmdet3d.models.builder import build_head
def test_paconv_decode_head_loss():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
paco... | 3,018 | 34.940476 | 71 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_heads/test_heads.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import random
import torch
from os.path import dirname, exists, join
from mmdet3d.core.bbox import (Box3DMode, CameraInstance3DBoxes,
DepthInstance3DBoxes, LiDARInstance3DBoxes)
from mmdet3d.mode... | 47,258 | 37.578776 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_heads/test_pointnet2_decode_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmcv.cnn.bricks import ConvModule
from mmdet3d.models.builder import build_head
def test_pn2_decode_head_loss():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
pn2_dec... | 3,002 | 34.75 | 71 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_heads/test_parta2_bbox_head.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmcv import Config
from torch.nn import BatchNorm1d, ReLU
from mmdet3d.core.bbox import Box3DMode, LiDARInstance3DBoxes
from mmdet3d.core.bbox.samplers import IoUNegPiecewiseSampler
from mmdet3d.models import PartA2BboxHead
from mmdet3d.op... | 20,614 | 40.646465 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_models/test_necks/test_necks.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.models.builder import build_backbone, build_neck
def test_centerpoint_fpn():
second_cfg = dict(
type='SECOND',
in_channels=64,
out_channels=[64, 128, 256],
layer_nums=[3, 5, 5],
layer_... | 1,834 | 29.583333 | 72 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_dataset_wrappers.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.datasets.builder import build_dataset
def test_getitem():
np.random.seed(1)
torch.manual_seed(1)
point_cloud_range = [-50, -50, -5, 50, 50, 3]
file_client_args = dict(backend='disk')
class_names = [
... | 2,891 | 35.15 | 78 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_kitti_mono_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pytest
import torch
from mmdet3d.datasets import KittiMonoDataset
def test_getitem():
np.random.seed(0)
class_names = ['Pedestrian', 'Cyclist', 'Car']
img_norm_cfg = dict(
mean=[103.530, 116.280, 123.675], std=[... | 8,734 | 39.439815 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_kitti_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import os
import pytest
import tempfile
import torch
from mmdet3d.core.bbox import LiDARInstance3DBoxes
from mmdet3d.datasets import KittiDataset
def _generate_kitti_dataset_config():
data_root = 'tests/data/kitti'
ann_file = 'tests/data/kitt... | 18,679 | 40.789709 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_scannet_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
import torch
from mmdet3d.datasets import ScanNetDataset, ScanNetSegDataset
def test_getitem():
np.random.seed(0)
root_path = './tests/data/scannet/'
ann_file = './tests/data/scannet/scannet_infos.pkl'
class_... | 27,055 | 38.555556 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_nuscenes_mono_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pytest
import tempfile
import torch
from os import path as osp
from mmdet3d.datasets import NuScenesMonoDataset
def test_getitem():
np.random.seed(0)
class_names = [
'car', 'truck', 'trailer', 'bus', 'construction_v... | 7,531 | 38.434555 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_waymo_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import tempfile
import torch
from mmdet3d.datasets import WaymoDataset
def _generate_waymo_train_dataset_config():
data_root = 'tests/data/waymo/kitti_format/'
ann_file = 'tests/data/waymo/kitti_format/waymo_infos_train.pkl'
... | 10,825 | 40.163498 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_s3dis_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.datasets import S3DISDataset, S3DISSegDataset
def test_getitem():
np.random.seed(0)
root_path = './tests/data/s3dis/'
ann_file = './tests/data/s3dis/s3dis_infos.pkl'
class_names = ('table', 'cha... | 13,524 | 37.864943 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_sunrgbd_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.datasets import SUNRGBDDataset
def _generate_sunrgbd_dataset_config():
root_path = './tests/data/sunrgbd'
ann_file = './tests/data/sunrgbd/sunrgbd_infos.pkl'
class_names = ('bed', 'table', 'sofa', '... | 13,290 | 40.534375 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_nuscene_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import tempfile
import torch
from mmdet3d.datasets import NuScenesDataset
def test_getitem():
np.random.seed(0)
point_cloud_range = [-50, -50, -5, 50, 50, 3]
file_client_args = dict(backend='disk')
class_names = [
'car', 'truc... | 4,308 | 35.82906 | 78 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_datasets/test_lyft_dataset.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import tempfile
import torch
from mmdet3d.datasets import LyftDataset
def test_getitem():
np.random.seed(0)
torch.manual_seed(0)
root_path = './tests/data/lyft'
ann_file = './tests/data/lyft/lyft_infos.pkl'
class_names... | 7,590 | 43.652941 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_pipelines/test_outdoor_pipeline.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.bbox import LiDARInstance3DBoxes
from mmdet3d.datasets.pipelines import Compose
def test_outdoor_aug_pipeline():
point_cloud_range = [0, -40, -3, 70.4, 40, 1]
class_names = ['Car']
np.random.seed(0)
tra... | 10,243 | 39.650794 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_pipelines/test_indoor_pipeline.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import torch
from os import path as osp
from mmdet3d.core.bbox import DepthInstance3DBoxes
from mmdet3d.datasets.pipelines import Compose
def test_scannet_pipeline():
class_names = ('cabinet', 'bed', 'chair', 'sofa', 'table', 'door',
... | 12,922 | 38.519878 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_pipelines/test_augmentations/test_transforms_3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pytest
import torch
from mmdet3d.core import (Box3DMode, CameraInstance3DBoxes,
DepthInstance3DBoxes, LiDARInstance3DBoxes)
from mmdet3d.core.bbox import Coord3DMode
from mmdet3d.core.points import DepthPoin... | 31,331 | 40.554377 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_pipelines/test_augmentations/test_test_augment_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.points import DepthPoints
from mmdet3d.datasets.pipelines import MultiScaleFlipAug3D
def test_multi_scale_flip_aug_3D():
np.random.seed(0)
transforms = [{
'type': 'GlobalRotScaleTrans',
'rot_rang... | 2,269 | 35.031746 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_data/test_pipelines/test_loadings/test_load_images_from_multi_views.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmcv.parallel import DataContainer
from mmdet3d.datasets.pipelines import (DefaultFormatBundle,
LoadMultiViewImageFromFiles)
def test_load_multi_view_image_from_files():
multi_view_img_loa... | 1,768 | 36.638298 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_assigners.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Tests the Assigner objects.
CommandLine:
pytest tests/test_utils/test_assigner.py
xdoctest tests/test_utils/test_assigner.py zero
"""
import torch
from mmdet3d.core.bbox.assigners import MaxIoUAssigner
def test_max_iou_assigner():
self = MaxIoUAssigner(... | 4,301 | 27.490066 | 77 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_samplers.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmdet3d.core.bbox.assigners import MaxIoUAssigner
from mmdet3d.core.bbox.samplers import IoUNegPiecewiseSampler
def test_iou_piecewise_sampler():
if not torch.cuda.is_available():
pytest.skip()
assigner = MaxIoUAssigner(
... | 1,732 | 37.511111 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_nms.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
def test_aligned_3d_nms():
from mmdet3d.core.post_processing import aligned_3d_nms
boxes = torch.tensor([[1.2261, 0.6679, -1.2678, 2.6547, 1.0428, 0.1000],
[5.0919, 0.6512, 0.7238, 5.4821, 1.2451, 2.1095... | 4,077 | 52.657895 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_bbox_coders.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.core.bbox import DepthInstance3DBoxes, LiDARInstance3DBoxes
from mmdet.core import build_bbox_coder
def test_partial_bin_based_box_coder():
box_coder_cfg = dict(
type='PartialBinBasedBBoxCoder',
num_sizes=10,
num_di... | 17,332 | 47.825352 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_points.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.points import (BasePoints, CameraPoints, DepthPoints,
LiDARPoints)
def test_base_points():
# test empty initialization
empty_boxes = []
points = BasePoints(empt... | 50,955 | 45.450319 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_coord_3d_mode.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet3d.core.bbox import (CameraInstance3DBoxes, Coord3DMode,
DepthInstance3DBoxes, LiDARInstance3DBoxes)
from mmdet3d.core.points import CameraPoints, DepthPoints, LiDARPoints
def test_points_conversi... | 15,980 | 49.572785 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_box3d.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
import unittest
from mmdet3d.core.bbox import (BaseInstance3DBoxes, Box3DMode,
CameraInstance3DBoxes, DepthInstance3DBoxes,
LiDARInstance3DBoxes, bbox3d2roi,
... | 64,168 | 47.356443 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_merge_augs.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import pytest
import torch
from mmdet3d.core import merge_aug_bboxes_3d
from mmdet3d.core.bbox import DepthInstance3DBoxes
def test_merge_aug_bboxes_3d():
if not torch.cuda.is_available():
pytest.skip('test requires GPU and torch+cuda')
img_... | 2,603 | 40.333333 | 78 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_anchors.py | # Copyright (c) OpenMMLab. All rights reserved.
"""
CommandLine:
pytest tests/test_utils/test_anchor.py
xdoctest tests/test_utils/test_anchor.py zero
"""
import torch
from mmdet3d.core.anchor import build_prior_generator
def test_anchor_3d_range_generator():
if torch.cuda.is_available():
device ... | 9,343 | 37.933333 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_utils/test_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet3d.core import draw_heatmap_gaussian
def test_gaussian():
heatmap = torch.zeros((128, 128))
ct_int = torch.tensor([64, 64], dtype=torch.int32)
radius = 2
draw_heatmap_gaussian(heatmap, ct_int, radius)
assert torch.isclose(torc... | 369 | 27.461538 | 77 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_metrics/test_kitti_eval.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.evaluation.kitti_utils.eval import (do_eval, eval_class,
kitti_eval)
def test_do_eval():
if not torch.cuda.is_available():
pytest.skip('tes... | 12,056 | 48.413934 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_metrics/test_losses.py | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from torch import nn as nn
def test_chamfer_disrance():
from mmdet3d.models.losses import ChamferDistance, chamfer_distance
with pytest.raises(AssertionError):
# test invalid mode
ChamferDistance(mode='smoothl1')
... | 4,738 | 41.3125 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_metrics/test_seg_eval.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.evaluation.seg_eval import seg_eval
def test_indoor_eval():
if not torch.cuda.is_available():
pytest.skip()
seg_preds = [
torch.Tensor([
0, 0, 1, 0, 0, 2, 1, 3, 1, 2, 1,... | 1,086 | 26.175 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/tests/test_metrics/test_indoor_eval.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
from mmdet3d.core.evaluation.indoor_eval import average_precision, indoor_eval
def test_indoor_eval():
if not torch.cuda.is_available():
pytest.skip()
from mmdet3d.core.bbox.structures import Box3DMode, Dept... | 6,630 | 34.084656 | 79 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/configs/bevdet4d/bevdet4d-r50.py | # Copyright (c) Phigent Robotics. All rights reserved.
_base_ = ['../_base_/datasets/nus-3d.py',
'../_base_/default_runtime.py']
# Global
# If point cloud range is changed, the models should also change their point
# cloud range accordingly
point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]
# For nuSc... | 9,966 | 35.509158 | 91 | py |
RoboBEV | RoboBEV-master/zoo/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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/SOLOFusion/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 |
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