Modify: supplement the kornia version of requirements.txt

.gitignore

@@ -0,0 +1,199 @@
+unitr_pretrain.pth
+logs/
+output/
+
+# Created by https://www.toptal.com/developers/gitignore/api/visualstudiocode,python
+# Edit at https://www.toptal.com/developers/gitignore?templates=visualstudiocode,python
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+### Python Patch ###
+# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration
+poetry.toml
+
+# ruff
+.ruff_cache/
+
+# LSP config files
+pyrightconfig.json
+
+### VisualStudioCode ###
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+!.vscode/*.code-snippets
+
+# Local History for Visual Studio Code
+.history/
+
+# Built Visual Studio Code Extensions
+*.vsix
+
+### VisualStudioCode Patch ###
+# Ignore all local history of files
+.history
+.ionide
+
+# End of https://www.toptal.com/developers/gitignore/api/visualstudiocode,python

README.md

@@ -205,7 +205,7 @@ bash scripts/dist_train.sh 8 --cfg_file ./cfgs/nuscenes_models/unitr_map.yaml --
 
 ## add lss
 cd tools
-bash scripts/dist_train.sh 8 --cfg_file ./cfgs/nuscenes_models/unitr_map.yaml --sync_bn --eval_map --logger_iter_interval 1000
+bash scripts/dist_train.sh 8 --cfg_file ./cfgs/nuscenes_models/unitr_map+lss.yaml --sync_bn --eval_map --logger_iter_interval 1000
 ```
 
 ### Testing

pcdet/datasets/processor/data_processor.py

@@ -85,9 +85,15 @@ def mask_points_and_boxes_outside_range(self, data_dict=None, config=None):
             mask = common_utils.mask_points_by_range(data_dict['points'], self.point_cloud_range)
             data_dict['points'] = data_dict['points'][mask]
 
+            # 이전 프레임 포인트도 동일하게 처리
+            if 'prev_points' in data_dict:
+                prev_mask = common_utils.mask_points_by_range(data_dict['prev_points'], self.point_cloud_range)
+                data_dict['prev_points'] = data_dict['prev_points'][prev_mask]
+
         if data_dict.get('gt_boxes', None) is not None and config.REMOVE_OUTSIDE_BOXES and self.training:
             mask = box_utils.mask_boxes_outside_range_numpy(
-                data_dict['gt_boxes'], self.point_cloud_range, min_num_corners=config.get('min_num_corners', 1), 
+                data_dict['gt_boxes'], self.point_cloud_range, 
+                min_num_corners=config.get('min_num_corners', 1), 
                 use_center_to_filter=config.get('USE_CENTER_TO_FILTER', True)
             )
             data_dict['gt_boxes'] = data_dict['gt_boxes'][mask]
@@ -100,8 +106,13 @@ def shuffle_points(self, data_dict=None, config=None):
         if config.SHUFFLE_ENABLED[self.mode]:
             points = data_dict['points']
             shuffle_idx = np.random.permutation(points.shape[0])
-            points = points[shuffle_idx]
-            data_dict['points'] = points
+            data_dict['points'] = points[shuffle_idx]
+
+            # 이전 프레임 포인트도 동일하게 셔플
+            if 'prev_points' in data_dict:
+                prev_points = data_dict['prev_points']
+                prev_shuffle_idx = np.random.permutation(prev_points.shape[0])
+                data_dict['prev_points'] = prev_points[prev_shuffle_idx]
 
         return data_dict
 
@@ -150,6 +161,12 @@ def transform_points_to_voxels(self, data_dict=None, config=None):
             )
 
         points = data_dict['points']
+
+        # 이전 프레임의 포인트 클라우드를 결합
+        if 'prev_points' in data_dict:
+            prev_points = data_dict['prev_points']
+            points = np.concatenate((prev_points, points), axis=0)
+
         voxel_output = self.voxel_generator.generate(points)
         voxels, coordinates, num_points = voxel_output
 
@@ -210,6 +227,33 @@ def sample_points(self, data_dict=None, config=None):
                 choice = np.concatenate((choice, extra_choice), axis=0)
             np.random.shuffle(choice)
         data_dict['points'] = points[choice]
+
+        # 이전 프레임 포인트에 대한 샘플링
+        if 'prev_points' in data_dict and len(data_dict['prev_points']) > 0:
+            prev_points = data_dict['prev_points']
+            if num_points < len(prev_points):
+                prev_pts_depth = np.linalg.norm(prev_points[:, 0:3], axis=1)
+                prev_pts_near_flag = prev_pts_depth < 40.0
+                prev_far_idxs_choice = np.where(prev_pts_near_flag == 0)[0]
+                prev_near_idxs = np.where(prev_pts_near_flag == 1)[0]
+                prev_choice = []
+                if num_points > len(prev_far_idxs_choice):
+                    prev_near_idxs_choice = np.random.choice(prev_near_idxs,
+                                                             num_points - len(prev_far_idxs_choice), replace=False)
+                    prev_choice = np.concatenate((prev_near_idxs_choice, prev_far_idxs_choice), axis=0) \
+                        if len(prev_far_idxs_choice) > 0 else prev_near_idxs_choice
+                else:
+                    prev_choice = np.arange(0, len(prev_points), dtype=np.int32)
+                    prev_choice = np.random.choice(prev_choice, num_points, replace=False)
+                np.random.shuffle(prev_choice)
+            else:
+                prev_choice = np.arange(0, len(prev_points), dtype=np.int32)
+                if num_points > len(prev_points):
+                    prev_extra_choice = np.random.choice(prev_choice, num_points - len(prev_points), replace=False)
+                    prev_choice = np.concatenate((prev_choice, prev_extra_choice), axis=0)
+                np.random.shuffle(prev_choice)
+            data_dict['prev_points'] = prev_points[prev_choice]
+
         return data_dict
 
     def calculate_grid_size(self, data_dict=None, config=None):