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Commit 1a47acdd authored by Jingwei Zhang's avatar Jingwei Zhang Committed by ZwwWayne
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[CI] Add github action CI && refactor `tests/utils/` (#2012) 

* update github action ci

* install torch in ci

* fix ci on win

* add __init__ in tests/utils

* add mmdet3d/testing for modeule importing in UT in win

* fix diff path sep on UT

* reduce RAM in voxel_generator

* reduce RAM in anchor_generator

* remove print in UT

* fix lint

* fix pvrcnn ut

* fix lint

* reduce channels in second_fpn
parent 139c6f0c
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.github/workflows/lint.yml 0 → 100644
View file @ 1a47acdd
name: lint
on: [push, pull_request]
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Set up Python 3.7
uses: actions/setup-python@v2
with:
python-version: 3.7
- name: Install pre-commit hook
run: |
pip install pre-commit
pre-commit install
- name: Linting
run: pre-commit run --all-files
- name: Check docstring coverage
run: |
pip install interrogate
interrogate -v --ignore-init-method --ignore-module --ignore-nested-functions --ignore-regex "__repr__" --fail-under 90 mmdet3d
.github/workflows/merge_stage_test.yml 0 → 100644
View file @ 1a47acdd
name: merge_stage_test
on:
push:
paths-ignore:
- 'README.md'
- 'README_zh-CN.md'
- 'docs/**'
- 'demo/**'
- '.dev_scripts/**'
- '.circleci/**'
branches:
- dev-1.x
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build_cpu_py:
runs-on: ubuntu-18.04
strategy:
matrix:
python-version: [3.7, 3.8, 3.9]
torch: [1.8.1]
include:
- torch: 1.8.1
torchvision: 0.9.1
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install MMEngine
run: pip install git+https://github.com/open-mmlab/mmengine.git@main
- name: Install MMCV
run: |
pip install -U openmim
mim install 'mmcv >= 2.0.0rc1'
- name: Install MMDet
run: pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
- name: Install other dependencies
run: pip install -r requirements/tests.txt
- name: Build and install
run: rm -rf .eggs && pip install -e .
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmdet3d -m pytest tests/
coverage xml
coverage report -m
build_cpu_pt:
runs-on: ubuntu-18.04
strategy:
matrix:
python-version: [3.7]
torch: [1.6.0, 1.7.1, 1.8.1, 1.9.1, 1.10.1, 1.11.0, 1.12.1]
include:
- torch: 1.6.0
torchvision: 0.7.0
- torch: 1.7.1
torchvision: 0.8.2
- torch: 1.8.1
torchvision: 0.9.1
- torch: 1.9.1
torchvision: 0.10.1
- torch: 1.10.1
torchvision: 0.11.2
- torch: 1.11.0
torchvision: 0.12.0
- torch: 1.12.1
torchvision: 0.13.1
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install MMEngine
run: pip install git+https://github.com/open-mmlab/mmengine.git@main
- name: Install MMCV
run: |
pip install -U openmim
mim install 'mmcv >= 2.0.0rc1'
- name: Install MMDet
run: pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
- name: Install other dependencies
run: pip install -r requirements/tests.txt
- name: Build and install
run: rm -rf .eggs && pip install -e .
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmdet3d -m pytest tests/
coverage xml
coverage report -m
# Only upload coverage report for python3.7 && pytorch1.8.1 cpu
- name: Upload coverage to Codecov
if: ${{matrix.torch == '1.8.1' && matrix.python-version == '3.7'}}
uses: codecov/codecov-action@v1.0.14
with:
file: ./coverage.xml
flags: unittests
env_vars: OS,PYTHON
name: codecov-umbrella
fail_ci_if_error: false
build_cu102:
runs-on: ubuntu-18.04
container:
image: pytorch/pytorch:1.8.1-cuda10.2-cudnn7-devel
strategy:
matrix:
python-version: [3.7]
include:
- torch: 1.8.1
cuda: 10.2
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Fetch GPG keys
run: |
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
- name: Install Python-dev
run: apt-get update && apt-get install -y python${{matrix.python-version}}-dev
if: ${{matrix.python-version != 3.9}}
- name: Install system dependencies
run: |
apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6
- name: Install PyTorch
run: python -m pip install torch==1.8.1+cu102 torchvision==0.9.1+cu102 -f https://download.pytorch.org/whl/torch_stable.html
- name: Install mmdet3d dependencies
run: |
pip install git+https://github.com/open-mmlab/mmengine.git@main
pip install -U openmim
mim install 'mmcv >= 2.0.0rc1'
pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
pip install -r requirements/tests.txt
- name: Build and install
run: |
python setup.py check -m -s
TORCH_CUDA_ARCH_LIST=7.0 pip install -e .
build_windows:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [windows-2022]
python: [3.7]
platform: [cpu, cu111]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Install lmdb
run: pip install lmdb
- name: Install PyTorch
run: pip install torch==1.8.1+${{matrix.platform}} torchvision==0.9.1+${{matrix.platform}} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
- name: Install mmdet3d dependencies
run: |
pip install git+https://github.com/open-mmlab/mmengine.git@main
pip install -U openmim
mim install 'mmcv >= 2.0.0rc1'
pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
pip install -r requirements/tests.txt
- name: Build and install
run: |
pip install -e .
- name: Run unittests and generate coverage report
run: |
pytest tests/
.github/workflows/pr_stage_test.yml 0 → 100644
View file @ 1a47acdd
name: pr_stage_test
on:
pull_request:
paths-ignore:
- 'README.md'
- 'README_zh-CN.md'
- 'docs/**'
- 'demo/**'
- '.dev_scripts/**'
- '.circleci/**'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build_cpu:
runs-on: ubuntu-18.04
strategy:
matrix:
python-version: [3.7]
include:
- torch: 1.8.1
torchvision: 0.9.1
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install MMEngine
run: pip install git+https://github.com/open-mmlab/mmengine.git@main
- name: Install MMCV
run: |
pip install -U openmim
mim install 'mmcv >= 2.0.0rc1'
- name: Install MMDet
run: pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
- name: Install other dependencies
run: pip install -r requirements/tests.txt
- name: Build and install
run: rm -rf .eggs && pip install -e .
- name: Run unittests and generate coverage report
run: |
coverage run --branch --source mmdet3d -m pytest tests/
coverage xml
coverage report -m
# Upload coverage report for python3.7 && pytorch1.8.1 cpu
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v1.0.14
with:
file: ./coverage.xml
flags: unittests
env_vars: OS,PYTHON
name: codecov-umbrella
fail_ci_if_error: false
build_cu102:
runs-on: ubuntu-18.04
container:
image: pytorch/pytorch:1.8.1-cuda10.2-cudnn7-devel
strategy:
matrix:
python-version: [3.8]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Fetch GPG keys
run: |
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub
- name: Install Python-dev
run: apt-get update && apt-get install -y python${{matrix.python-version}}-dev
if: ${{matrix.python-version != 3.9}}
- name: Install system dependencies
run: |
apt-get update
apt-get install -y ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libxrender-dev
- name: Install PyTorch
run: python -m pip install torch==1.8.1+cu102 torchvision==0.9.1+cu102 -f https://download.pytorch.org/whl/torch_stable.html
- name: Install mmdet3d dependencies
run: |
pip install git+https://github.com/open-mmlab/mmengine.git@main
pip install -U openmim
mim install 'mmcv >= 2.0.0rc1'
pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
pip install -r requirements/tests.txt
- name: Build and install
run: |
python setup.py check -m -s
TORCH_CUDA_ARCH_LIST=7.0 pip install -e .
build_windows:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [windows-2022]
python: [3.7]
platform: [cpu, cu111]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python }}
- name: Upgrade pip
run: python -m pip install pip --upgrade
- name: Install lmdb
run: pip install lmdb
- name: Install PyTorch
run: pip install torch==1.8.1+${{matrix.platform}} torchvision==0.9.1+${{matrix.platform}} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
- name: Install mmdet3d dependencies
run: |
pip install git+https://github.com/open-mmlab/mmengine.git@main
pip install -U openmim
mim install 'mmcv >= 2.0.0rc1'
pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
pip install -r requirements/tests.txt
- name: Build and install
run: |
pip install -e .
- name: Run unittests and generate coverage report
run: |
pytest tests/
.github/workflows/test_mim.yml 0 → 100644
View file @ 1a47acdd
name: test-mim
on:
push:
paths:
- 'model-index.yml'
- 'configs/**'
pull_request:
paths:
- 'model-index.yml'
- 'configs/**'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
build_cpu:
runs-on: ubuntu-18.04
strategy:
matrix:
python-version: [3.7]
torch: [1.8.0]
include:
- torch: 1.8.0
torch_version: torch1.8
torchvision: 0.9.0
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Upgrade pip
run: pip install pip --upgrade
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install openmim
run: pip install openmim
- name: Build and install
run: rm -rf .eggs && mim install -e .
- name: test commands of mim
run: mim search mmdet3d
mmdet3d/datasets/det3d_dataset.py
View file @ 1a47acdd
# Copyright (c) OpenMMLab. All rights reserved. # Copyright (c) OpenMMLab. All rights reserved.
import copy import copy
import os
from os import path as osp from os import path as osp
from typing import Callable, List, Optional, Set, Union from typing import Callable, List, Optional, Set, Union
...@@ -287,7 +288,7 @@ class Det3DDataset(BaseDataset): ...@@ -287,7 +288,7 @@ class Det3DDataset(BaseDataset):
if 'lidar_sweeps' in info: if 'lidar_sweeps' in info:
for sweep in info['lidar_sweeps']: for sweep in info['lidar_sweeps']:
file_suffix = sweep['lidar_points']['lidar_path'].split( file_suffix = sweep['lidar_points']['lidar_path'].split(
'/')[-1] os.sep)[-1]
if 'samples' in sweep['lidar_points']['lidar_path']: if 'samples' in sweep['lidar_points']['lidar_path']:
sweep['lidar_points']['lidar_path'] = osp.join( sweep['lidar_points']['lidar_path'] = osp.join(
self.data_prefix['pts'], file_suffix) self.data_prefix['pts'], file_suffix)
......
mmdet3d/testing/__init__.py 0 → 100644
View file @ 1a47acdd
# Copyright (c) OpenMMLab. All rights reserved.
from .data_utils import (create_data_info_after_loading,
create_dummy_data_info,
create_mono3d_data_info_after_loading)
from .model_utils import (create_detector_inputs, get_detector_cfg,
get_model_cfg, setup_seed)
__all__ = [
'create_dummy_data_info', 'create_data_info_after_loading',
'create_mono3d_data_info_after_loading', 'create_detector_inputs',
'get_detector_cfg', 'get_model_cfg', 'setup_seed'
]
tests/utils/data_utils.py → mmdet3d/testing/data_utils.py
View file @ 1a47acdd
...@@ -3,6 +3,7 @@ import numpy as np ...@@ -3,6 +3,7 @@ import numpy as np
# create a dummy `results` to test the pipeline # create a dummy `results` to test the pipeline
from mmdet3d.datasets import LoadAnnotations3D, LoadPointsFromFile from mmdet3d.datasets import LoadAnnotations3D, LoadPointsFromFile
from mmdet3d.datasets.transforms.loading import LoadImageFromFileMono3D
from mmdet3d.structures import LiDARInstance3DBoxes from mmdet3d.structures import LiDARInstance3DBoxes
...@@ -20,6 +21,10 @@ def create_dummy_data_info(with_ann=True): ...@@ -20,6 +21,10 @@ def create_dummy_data_info(with_ann=True):
-1.5808]])), -1.5808]])),
'gt_labels_3d': 'gt_labels_3d':
np.array([1]), np.array([1]),
'centers_2d':
np.array([[765.04, 214.56]]),
'depths':
np.array([8.410]),
'num_lidar_pts': 'num_lidar_pts':
np.array([377]), np.array([377]),
'difficulty': 'difficulty':
...@@ -134,6 +139,9 @@ def create_dummy_data_info(with_ann=True): ...@@ -134,6 +139,9 @@ def create_dummy_data_info(with_ann=True):
], ],
'bbox_label_3d': 'bbox_label_3d':
-1, -1,
'center_2d': [765.04, 214.56],
'depth':
8.410,
'num_lidar_pts': 'num_lidar_pts':
377, 377,
'difficulty': 'difficulty':
...@@ -168,3 +176,17 @@ def create_data_info_after_loading(): ...@@ -168,3 +176,17 @@ def create_data_info_after_loading():
data_info = load_points_transform(data_info) data_info = load_points_transform(data_info)
data_info_after_loading = load_anns_transform(data_info) data_info_after_loading = load_anns_transform(data_info)
return data_info_after_loading return data_info_after_loading
def create_mono3d_data_info_after_loading():
load_anns_transform = LoadAnnotations3D(
with_bbox=True,
with_label=True,
with_bbox_3d=True,
with_label_3d=True,
with_bbox_depth=True)
load_img_transform = LoadImageFromFileMono3D()
data_info = create_dummy_data_info()
data_info = load_img_transform(data_info)
data_info_after_loading = load_anns_transform(data_info)
return data_info_after_loading
tests/utils/model_utils.py → mmdet3d/testing/model_utils.py
View file @ 1a47acdd
...@@ -12,7 +12,7 @@ from mmdet3d.structures import (CameraInstance3DBoxes, DepthInstance3DBoxes, ...@@ -12,7 +12,7 @@ from mmdet3d.structures import (CameraInstance3DBoxes, DepthInstance3DBoxes,
PointData) PointData)
def _setup_seed(seed): def setup_seed(seed):
torch.manual_seed(seed) torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed) torch.cuda.manual_seed_all(seed)
np.random.seed(seed) np.random.seed(seed)
...@@ -44,7 +44,7 @@ def _get_config_module(fname): ...@@ -44,7 +44,7 @@ def _get_config_module(fname):
return config_mod return config_mod
def _get_model_cfg(fname): def get_model_cfg(fname):
"""Grab configs necessary to create a model. """Grab configs necessary to create a model.
These are deep copied to allow for safe modification of parameters without These are deep copied to allow for safe modification of parameters without
...@@ -56,7 +56,7 @@ def _get_model_cfg(fname): ...@@ -56,7 +56,7 @@ def _get_model_cfg(fname):
return model return model
def _get_detector_cfg(fname): def get_detector_cfg(fname):
"""Grab configs necessary to create a detector. """Grab configs necessary to create a detector.
These are deep copied to allow for safe modification of parameters without These are deep copied to allow for safe modification of parameters without
...@@ -73,19 +73,19 @@ def _get_detector_cfg(fname): ...@@ -73,19 +73,19 @@ def _get_detector_cfg(fname):
return model return model
def _create_detector_inputs(seed=0, def create_detector_inputs(seed=0,
with_points=True, with_points=True,
with_img=False, with_img=False,
img_size=10, img_size=10,
num_gt_instance=20, num_gt_instance=20,
num_points=10, num_points=10,
points_feat_dim=4, points_feat_dim=4,
num_classes=3, num_classes=3,
gt_bboxes_dim=7, gt_bboxes_dim=7,
with_pts_semantic_mask=False, with_pts_semantic_mask=False,
with_pts_instance_mask=False, with_pts_instance_mask=False,
bboxes_3d_type='lidar'): bboxes_3d_type='lidar'):
_setup_seed(seed) setup_seed(seed)
assert bboxes_3d_type in ('lidar', 'depth', 'cam') assert bboxes_3d_type in ('lidar', 'depth', 'cam')
bbox_3d_class = { bbox_3d_class = {
'lidar': LiDARInstance3DBoxes, 'lidar': LiDARInstance3DBoxes,
......
tests/test_datasets/test_lyft_dataset.py
View file @ 1a47acdd
...@@ -54,9 +54,8 @@ def test_getitem(): ...@@ -54,9 +54,8 @@ def test_getitem():
lyft_dataset.prepare_data(0) lyft_dataset.prepare_data(0)
input_dict = lyft_dataset.get_data_info(0) input_dict = lyft_dataset.get_data_info(0)
# assert the the path should contains data_prefix and data_root # assert the the path should contains data_prefix and data_root
assert input_dict['lidar_points'][ assert data_prefix['pts'] in input_dict['lidar_points']['lidar_path']
'lidar_path'] == 'tests/data/lyft/lidar/host-a017_lidar1_' \ assert data_root in input_dict['lidar_points']['lidar_path']
'1236118886901125926.bin'
ann_info = lyft_dataset.parse_ann_info(input_dict) ann_info = lyft_dataset.parse_ann_info(input_dict)
......
tests/test_datasets/test_nuscenes_dataset.py
View file @ 1a47acdd
...@@ -58,10 +58,8 @@ def test_getitem(): ...@@ -58,10 +58,8 @@ def test_getitem():
input_dict = nus_dataset.get_data_info(0) input_dict = nus_dataset.get_data_info(0)
# assert the the path should contains data_prefix and data_root # assert the the path should contains data_prefix and data_root
assert data_prefix['pts'] in input_dict['lidar_points']['lidar_path'] assert data_prefix['pts'] in input_dict['lidar_points']['lidar_path']
assert input_dict['lidar_points'][ assert data_root in input_dict['lidar_points']['lidar_path']
'lidar_path'] == 'tests/data/nuscenes/samples/LIDAR_TOP/' \
'n015-2018-08-02-17-16-37+0800__LIDAR_TOP__' \
'1533201470948018.pcd.bin'
for cam_id, img_info in input_dict['images'].items(): for cam_id, img_info in input_dict['images'].items():
if 'img_path' in img_info: if 'img_path' in img_info:
assert data_prefix['img'] in img_info['img_path'] assert data_prefix['img'] in img_info['img_path']
......
tests/test_datasets/test_transforms/test_formating.py
View file @ 1a47acdd
...@@ -3,10 +3,10 @@ import unittest ...@@ -3,10 +3,10 @@ import unittest
import torch import torch
from mmengine.testing import assert_allclose from mmengine.testing import assert_allclose
from utils import create_data_info_after_loading
from mmdet3d.datasets.transforms.formating import Pack3DDetInputs from mmdet3d.datasets.transforms.formating import Pack3DDetInputs
from mmdet3d.structures import LiDARInstance3DBoxes from mmdet3d.structures import LiDARInstance3DBoxes
from mmdet3d.testing import create_data_info_after_loading
class TestPack3DDetInputs(unittest.TestCase): class TestPack3DDetInputs(unittest.TestCase):
......
tests/test_datasets/test_transforms/test_loading.py
View file @ 1a47acdd
...@@ -4,12 +4,12 @@ import unittest ...@@ -4,12 +4,12 @@ import unittest
import numpy as np import numpy as np
import torch import torch
from mmengine.testing import assert_allclose from mmengine.testing import assert_allclose
from utils import create_dummy_data_info
from mmdet3d.datasets.transforms import PointSegClassMapping from mmdet3d.datasets.transforms import PointSegClassMapping
from mmdet3d.datasets.transforms.loading import (LoadAnnotations3D, from mmdet3d.datasets.transforms.loading import (LoadAnnotations3D,
LoadPointsFromFile) LoadPointsFromFile)
from mmdet3d.structures import DepthPoints, LiDARPoints from mmdet3d.structures import DepthPoints, LiDARPoints
from mmdet3d.testing import create_dummy_data_info
class TestLoadPointsFromFile(unittest.TestCase): class TestLoadPointsFromFile(unittest.TestCase):
......
tests/test_datasets/test_transforms/test_transforms_3d.py
View file @ 1a47acdd
...@@ -5,10 +5,10 @@ import unittest ...@@ -5,10 +5,10 @@ import unittest
import numpy as np import numpy as np
import torch import torch
from mmengine.testing import assert_allclose from mmengine.testing import assert_allclose
from utils import create_data_info_after_loading
from mmdet3d.datasets import GlobalAlignment, RandomFlip3D from mmdet3d.datasets import GlobalAlignment, RandomFlip3D
from mmdet3d.datasets.transforms import GlobalRotScaleTrans from mmdet3d.datasets.transforms import GlobalRotScaleTrans
from mmdet3d.testing import create_data_info_after_loading
class TestGlobalRotScaleTrans(unittest.TestCase): class TestGlobalRotScaleTrans(unittest.TestCase):
......
tests/test_models/test_dense_heads/test_fcaf3d_head.py
View file @ 1a47acdd
...@@ -6,7 +6,7 @@ import torch ...@@ -6,7 +6,7 @@ import torch
from mmdet3d import * # noqa from mmdet3d import * # noqa
from mmdet3d.models.dense_heads import FCAF3DHead from mmdet3d.models.dense_heads import FCAF3DHead
from tests.utils.model_utils import _create_detector_inputs from mmdet3d.testing import create_detector_inputs
class TestAnchor3DHead(TestCase): class TestAnchor3DHead(TestCase):
...@@ -63,7 +63,7 @@ class TestAnchor3DHead(TestCase): ...@@ -63,7 +63,7 @@ class TestAnchor3DHead(TestCase):
x = (x1, x2, x3, x4) x = (x1, x2, x3, x4)
# fake annotation # fake annotation
packed_inputs = _create_detector_inputs( packed_inputs = create_detector_inputs(
with_points=False, with_points=False,
with_img=False, with_img=False,
num_gt_instance=3, num_gt_instance=3,
......
tests/test_models/test_dense_heads/test_freeanchors.py
View file @ 1a47acdd
...@@ -4,8 +4,8 @@ import torch ...@@ -4,8 +4,8 @@ import torch
from mmengine import DefaultScope from mmengine import DefaultScope
from mmdet3d.registry import MODELS from mmdet3d.registry import MODELS
from tests.utils.model_utils import (_create_detector_inputs, from mmdet3d.testing import (create_detector_inputs, get_detector_cfg,
_get_detector_cfg, _setup_seed) setup_seed)
class TestFreeAnchor(unittest.TestCase): class TestFreeAnchor(unittest.TestCase):
...@@ -15,8 +15,8 @@ class TestFreeAnchor(unittest.TestCase): ...@@ -15,8 +15,8 @@ class TestFreeAnchor(unittest.TestCase):
assert hasattr(mmdet3d.models.dense_heads, 'FreeAnchor3DHead') assert hasattr(mmdet3d.models.dense_heads, 'FreeAnchor3DHead')
DefaultScope.get_instance('test_freeanchor', scope_name='mmdet3d') DefaultScope.get_instance('test_freeanchor', scope_name='mmdet3d')
_setup_seed(0) setup_seed(0)
freeanchor_cfg = _get_detector_cfg( freeanchor_cfg = get_detector_cfg(
'free_anchor/pointpillars_hv_regnet-1.6gf_fpn_head-free-anchor' 'free_anchor/pointpillars_hv_regnet-1.6gf_fpn_head-free-anchor'
'_sbn-all_8xb4-2x_nus-3d.py') '_sbn-all_8xb4-2x_nus-3d.py')
# decrease channels to reduce cuda memory. # decrease channels to reduce cuda memory.
...@@ -29,14 +29,14 @@ class TestFreeAnchor(unittest.TestCase): ...@@ -29,14 +29,14 @@ class TestFreeAnchor(unittest.TestCase):
freeanchor_cfg.pts_bbox_head.in_channels = 1 freeanchor_cfg.pts_bbox_head.in_channels = 1
model = MODELS.build(freeanchor_cfg) model = MODELS.build(freeanchor_cfg)
num_gt_instance = 3 num_gt_instance = 3
packed_inputs = _create_detector_inputs( packed_inputs = create_detector_inputs(
num_gt_instance=num_gt_instance, gt_bboxes_dim=9) num_gt_instance=num_gt_instance, gt_bboxes_dim=9)
# TODO: Support aug_test # TODO: Support aug_test
# aug_data = [ # aug_data = [
# _create_detector_inputs( # create_detector_inputs(
# num_gt_instance=num_gt_instance, gt_bboxes_dim=9), # num_gt_instance=num_gt_instance, gt_bboxes_dim=9),
# _create_detector_inputs( # create_detector_inputs(
# num_gt_instance=num_gt_instance + 1, gt_bboxes_dim=9) # num_gt_instance=num_gt_instance + 1, gt_bboxes_dim=9)
# ] # ]
# # test_aug_test # # test_aug_test
......
tests/test_models/test_dense_heads/test_ssn.py
View file @ 1a47acdd
...@@ -4,8 +4,8 @@ import torch ...@@ -4,8 +4,8 @@ import torch
from mmengine import DefaultScope from mmengine import DefaultScope
from mmdet3d.registry import MODELS from mmdet3d.registry import MODELS
from tests.utils.model_utils import (_create_detector_inputs, from mmdet3d.testing import (create_detector_inputs, get_detector_cfg,
_get_detector_cfg, _setup_seed) setup_seed)
class TestSSN(unittest.TestCase): class TestSSN(unittest.TestCase):
...@@ -15,8 +15,8 @@ class TestSSN(unittest.TestCase): ...@@ -15,8 +15,8 @@ class TestSSN(unittest.TestCase):
assert hasattr(mmdet3d.models.dense_heads, 'ShapeAwareHead') assert hasattr(mmdet3d.models.dense_heads, 'ShapeAwareHead')
DefaultScope.get_instance('test_ssn', scope_name='mmdet3d') DefaultScope.get_instance('test_ssn', scope_name='mmdet3d')
_setup_seed(0) setup_seed(0)
ssn_cfg = _get_detector_cfg( ssn_cfg = get_detector_cfg(
'ssn/ssn_hv_secfpn_sbn-all_16xb2-2x_nus-3d.py') 'ssn/ssn_hv_secfpn_sbn-all_16xb2-2x_nus-3d.py')
ssn_cfg.pts_voxel_encoder.feat_channels = [1, 1] ssn_cfg.pts_voxel_encoder.feat_channels = [1, 1]
ssn_cfg.pts_middle_encoder.in_channels = 1 ssn_cfg.pts_middle_encoder.in_channels = 1
...@@ -28,14 +28,14 @@ class TestSSN(unittest.TestCase): ...@@ -28,14 +28,14 @@ class TestSSN(unittest.TestCase):
ssn_cfg.pts_bbox_head.feat_channels = 1 ssn_cfg.pts_bbox_head.feat_channels = 1
model = MODELS.build(ssn_cfg) model = MODELS.build(ssn_cfg)
num_gt_instance = 50 num_gt_instance = 50
packed_inputs = _create_detector_inputs( packed_inputs = create_detector_inputs(
num_gt_instance=num_gt_instance, gt_bboxes_dim=9) num_gt_instance=num_gt_instance, gt_bboxes_dim=9)
# TODO: Support aug_test # TODO: Support aug_test
# aug_data = [ # aug_data = [
# _create_detector_inputs( # create_detector_inputs(
# num_gt_instance=num_gt_instance, gt_bboxes_dim=9), # num_gt_instance=num_gt_instance, gt_bboxes_dim=9),
# _create_detector_inputs( # create_detector_inputs(
# num_gt_instance=num_gt_instance + 1, gt_bboxes_dim=9) # num_gt_instance=num_gt_instance + 1, gt_bboxes_dim=9)
# ] # ]
# test_aug_test # test_aug_test
......
tests/test_models/test_detectors/test_3dssd.py
View file @ 1a47acdd
...@@ -4,8 +4,8 @@ import torch ...@@ -4,8 +4,8 @@ import torch
from mmengine import DefaultScope from mmengine import DefaultScope
from mmdet3d.registry import MODELS from mmdet3d.registry import MODELS
from tests.utils.model_utils import (_create_detector_inputs, from mmdet3d.testing import (create_detector_inputs, get_detector_cfg,
_get_detector_cfg, _setup_seed) setup_seed)
class Test3DSSD(unittest.TestCase): class Test3DSSD(unittest.TestCase):
...@@ -15,11 +15,11 @@ class Test3DSSD(unittest.TestCase): ...@@ -15,11 +15,11 @@ class Test3DSSD(unittest.TestCase):
assert hasattr(mmdet3d.models, 'SSD3DNet') assert hasattr(mmdet3d.models, 'SSD3DNet')
DefaultScope.get_instance('test_ssd3d', scope_name='mmdet3d') DefaultScope.get_instance('test_ssd3d', scope_name='mmdet3d')
_setup_seed(0) setup_seed(0)
voxel_net_cfg = _get_detector_cfg('3dssd/3dssd_4xb4_kitti-3d-car.py') voxel_net_cfg = get_detector_cfg('3dssd/3dssd_4xb4_kitti-3d-car.py')
model = MODELS.build(voxel_net_cfg) model = MODELS.build(voxel_net_cfg)
num_gt_instance = 3 num_gt_instance = 3
packed_inputs = _create_detector_inputs( packed_inputs = create_detector_inputs(
num_gt_instance=num_gt_instance, num_classes=1) num_gt_instance=num_gt_instance, num_classes=1)
if torch.cuda.is_available(): if torch.cuda.is_available():
......
tests/test_models/test_detectors/test_center_point.py
View file @ 1a47acdd
...@@ -4,8 +4,8 @@ import torch ...@@ -4,8 +4,8 @@ import torch
from mmengine import DefaultScope from mmengine import DefaultScope
from mmdet3d.registry import MODELS from mmdet3d.registry import MODELS
from tests.utils.model_utils import (_create_detector_inputs, from mmdet3d.testing import (create_detector_inputs, get_detector_cfg,
_get_detector_cfg, _setup_seed) setup_seed)
class TestCenterPoint(unittest.TestCase): class TestCenterPoint(unittest.TestCase):
...@@ -15,14 +15,14 @@ class TestCenterPoint(unittest.TestCase): ...@@ -15,14 +15,14 @@ class TestCenterPoint(unittest.TestCase):
assert hasattr(mmdet3d.models, 'CenterPoint') assert hasattr(mmdet3d.models, 'CenterPoint')
_setup_seed(0) setup_seed(0)
DefaultScope.get_instance('test_center_point', scope_name='mmdet3d') DefaultScope.get_instance('test_center_point', scope_name='mmdet3d')
centerpoint_net_cfg = _get_detector_cfg( centerpoint_net_cfg = get_detector_cfg(
'centerpoint/centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py' # noqa 'centerpoint/centerpoint_voxel01_second_secfpn_8xb4-cyclic-20e_nus-3d.py' # noqa
) )
model = MODELS.build(centerpoint_net_cfg) model = MODELS.build(centerpoint_net_cfg)
num_gt_instance = 50 num_gt_instance = 50
packed_inputs = _create_detector_inputs( packed_inputs = create_detector_inputs(
with_img=True, num_gt_instance=num_gt_instance, points_feat_dim=5) with_img=True, num_gt_instance=num_gt_instance, points_feat_dim=5)
for sample_id in range(len(packed_inputs['data_samples'])): for sample_id in range(len(packed_inputs['data_samples'])):
......
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