From 2f49c3df63e22373292a5fa9a43035800fe9b0be Mon Sep 17 00:00:00 2001 From: sooahleex Date: Wed, 25 Sep 2024 17:02:34 +0900 Subject: [PATCH] Update structure to support subset --- .../plugins/data_formats/kitti_3d/base.py | 44 ++++++--- .../plugins/data_formats/kitti_3d/format.py | 31 ++++++ .../plugins/data_formats/kitti_3d/importer.py | 8 +- .../kitti_3d/{training => }/calib/000001.txt | 0 .../{training => }/image_2/000001.png | Bin .../{training => }/label_2/000001.txt | 0 .../kitti_3d/training/velodyne/000001.bin | Bin 298080 -> 0 bytes .../kitti_3d/training/velodyne/000002.bin | Bin 2030256 -> 0 bytes .../kitti_3d/training/velodyne/000003.bin | Bin 1809760 -> 0 bytes .../calib/test/000002.txt | 7 ++ .../calib/train/000000.txt | 7 ++ .../kitti_3d_with_subset/calib/val/000001.txt | 7 ++ .../image_2/test/000002.png | Bin 0 -> 94 bytes .../image_2/train/000000.png | Bin 0 -> 94 bytes .../image_2/val/000001.png | Bin 0 -> 94 bytes .../label_2/test/000002.txt | 2 + .../label_2/train/000000.txt | 1 + .../label_2/val/000001.txt | 2 + tests/unit/test_kitti_3d_format.py | 93 ++++++++++++------ 19 files changed, 158 insertions(+), 44 deletions(-) rename tests/assets/kitti_dataset/kitti_3d/{training => }/calib/000001.txt (100%) rename tests/assets/kitti_dataset/kitti_3d/{training => }/image_2/000001.png (100%) rename tests/assets/kitti_dataset/kitti_3d/{training => }/label_2/000001.txt (100%) delete mode 100644 tests/assets/kitti_dataset/kitti_3d/training/velodyne/000001.bin delete mode 100644 tests/assets/kitti_dataset/kitti_3d/training/velodyne/000002.bin delete mode 100644 tests/assets/kitti_dataset/kitti_3d/training/velodyne/000003.bin create mode 100755 tests/assets/kitti_dataset/kitti_3d_with_subset/calib/test/000002.txt create mode 100755 tests/assets/kitti_dataset/kitti_3d_with_subset/calib/train/000000.txt create mode 100755 tests/assets/kitti_dataset/kitti_3d_with_subset/calib/val/000001.txt create mode 100755 tests/assets/kitti_dataset/kitti_3d_with_subset/image_2/test/000002.png create mode 100755 tests/assets/kitti_dataset/kitti_3d_with_subset/image_2/train/000000.png create mode 100755 tests/assets/kitti_dataset/kitti_3d_with_subset/image_2/val/000001.png create mode 100644 tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/test/000002.txt create mode 100644 tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/train/000000.txt create mode 100644 tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/val/000001.txt diff --git a/src/datumaro/plugins/data_formats/kitti_3d/base.py b/src/datumaro/plugins/data_formats/kitti_3d/base.py index 79958b4846..c385512e2e 100644 --- a/src/datumaro/plugins/data_formats/kitti_3d/base.py +++ b/src/datumaro/plugins/data_formats/kitti_3d/base.py @@ -4,17 +4,18 @@ import glob import logging +import os import os.path as osp from typing import List, Optional, Type, TypeVar -from datumaro.components.annotation import AnnotationType, Bbox, LabelCategories +from datumaro.components.annotation import AnnotationType, Bbox from datumaro.components.dataset_base import DatasetItem, SubsetBase from datumaro.components.errors import InvalidAnnotationError from datumaro.components.importer import ImportContext -from datumaro.components.media import Image, PointCloud +from datumaro.components.media import Image from datumaro.util.image import find_images -from .format import Kitti3dPath +from .format import Kitti3DLabelMap, Kitti3dPath, make_kitti3d_categories T = TypeVar("T") @@ -30,27 +31,38 @@ def __init__( ctx: Optional[ImportContext] = None, ): assert osp.isdir(path), path - super().__init__(subset=subset, media_type=PointCloud, ctx=ctx) self._path = path - common_attrs = {"truncated", "occluded", "alpha", "dimensions", "location", "rotation_y"} - self._categories = {AnnotationType.label: LabelCategories(attributes=common_attrs)} + if not subset: + folder_path = path.rsplit(Kitti3dPath.LABEL_DIR, 1)[0] + img_dir = osp.join(folder_path, Kitti3dPath.IMAGE_DIR) + if any(os.path.isdir(os.path.join(img_dir, item)) for item in os.listdir(img_dir)): + subset = osp.split(path)[-1] + self._path = folder_path + super().__init__(subset=subset, ctx=ctx) + + self._categories = make_kitti3d_categories(Kitti3DLabelMap) self._items = self._load_items() def _load_items(self) -> List[DatasetItem]: items = [] + image_dir = osp.join(self._path, Kitti3dPath.IMAGE_DIR) image_path_by_id = { - osp.splitext(osp.relpath(p, image_dir))[0]: p + osp.split(osp.splitext(osp.relpath(p, image_dir))[0])[-1]: p for p in find_images(image_dir, recursive=True) } + if self._subset == "default": + ann_dir = osp.join(self._path, Kitti3dPath.LABEL_DIR) + else: + ann_dir = osp.join(self._path, Kitti3dPath.LABEL_DIR, self._subset) + label_categories = self._categories[AnnotationType.label] - subset = osp.split(self._path)[-1] - for labels_path in sorted(glob.glob(osp.join(self._path, "*.txt"), recursive=True)): - item_id = osp.splitext(osp.relpath(labels_path, self._path))[0] + for labels_path in sorted(glob.glob(osp.join(ann_dir, "**", "*.txt"), recursive=True)): + item_id = osp.splitext(osp.relpath(labels_path, ann_dir))[0] anns = [] try: @@ -116,14 +128,18 @@ def _load_items(self) -> List[DatasetItem]: if image: image = Image.from_file(path=image) + if self._subset == "default": + calib_path = osp.join(self._path, Kitti3dPath.CALIB_DIR, item_id + ".txt") + else: + calib_path = osp.join( + self._path, Kitti3dPath.CALIB_DIR, self._subset, item_id + ".txt" + ) items.append( DatasetItem( id=item_id, - subset=subset, + subset=self._subset, media=image, - attributes={ - "calib_path": osp.join(self._path, Kitti3dPath.CALIB_DIR, item_id + ".txt") - }, + attributes={"calib_path": calib_path}, annotations=anns, ) ) diff --git a/src/datumaro/plugins/data_formats/kitti_3d/format.py b/src/datumaro/plugins/data_formats/kitti_3d/format.py index 98a883428d..c61f2b1f3f 100644 --- a/src/datumaro/plugins/data_formats/kitti_3d/format.py +++ b/src/datumaro/plugins/data_formats/kitti_3d/format.py @@ -4,9 +4,40 @@ import os.path as osp +from datumaro.components.annotation import AnnotationType, LabelCategories + class Kitti3dPath: PCD_DIR = osp.join("velodyne") IMAGE_DIR = "image_2" LABEL_DIR = "label_2" CALIB_DIR = "calib" + + +Kitti3DLabelMap = [ + "DontCare", + "Car", + "Pedestrian", + "Van", + "Truck", + "Cyclist", + "Sitter", + "Train", + "Motorcycle", + "Bus", + "Misc", +] + + +def make_kitti3d_categories(label_map=None): + if label_map is None: + label_map = Kitti3DLabelMap + + categories = {} + common_attrs = {"truncated", "occluded", "alpha", "dimensions", "location", "rotation_y"} + label_categories = LabelCategories(attributes=common_attrs) + for label in label_map: + label_categories.add(label) + categories[AnnotationType.label] = label_categories + + return categories diff --git a/src/datumaro/plugins/data_formats/kitti_3d/importer.py b/src/datumaro/plugins/data_formats/kitti_3d/importer.py index b74f6de34e..af249a08e9 100644 --- a/src/datumaro/plugins/data_formats/kitti_3d/importer.py +++ b/src/datumaro/plugins/data_formats/kitti_3d/importer.py @@ -17,7 +17,6 @@ class Kitti3dImporter(Importer): @classmethod def detect(cls, context: FormatDetectionContext) -> FormatDetectionConfidence: - context.require_file(f"{Kitti3dPath.PCD_DIR}/*.bin") cls._check_ann_file(context.require_file(f"{Kitti3dPath.LABEL_DIR}/*.txt"), context) return FormatDetectionConfidence.MEDIUM @@ -43,6 +42,11 @@ def get_file_extensions(cls) -> List[str]: @classmethod def find_sources(cls, path): - return cls._find_sources_recursive( + # return [{"url": path, "format": "kitti3d"}] + sources = cls._find_sources_recursive( path, "", "kitti3d", dirname=Kitti3dPath.LABEL_DIR, file_filter=lambda p: osp.isdir(p) ) + if len(sources) == 0: + return [{"url": path, "format": "kitti3d"}] + else: + return sources diff --git a/tests/assets/kitti_dataset/kitti_3d/training/calib/000001.txt b/tests/assets/kitti_dataset/kitti_3d/calib/000001.txt similarity index 100% rename from tests/assets/kitti_dataset/kitti_3d/training/calib/000001.txt rename to tests/assets/kitti_dataset/kitti_3d/calib/000001.txt diff --git a/tests/assets/kitti_dataset/kitti_3d/training/image_2/000001.png b/tests/assets/kitti_dataset/kitti_3d/image_2/000001.png similarity index 100% rename from tests/assets/kitti_dataset/kitti_3d/training/image_2/000001.png rename to tests/assets/kitti_dataset/kitti_3d/image_2/000001.png diff --git a/tests/assets/kitti_dataset/kitti_3d/training/label_2/000001.txt b/tests/assets/kitti_dataset/kitti_3d/label_2/000001.txt similarity index 100% rename from tests/assets/kitti_dataset/kitti_3d/training/label_2/000001.txt rename to tests/assets/kitti_dataset/kitti_3d/label_2/000001.txt diff --git a/tests/assets/kitti_dataset/kitti_3d/training/velodyne/000001.bin 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0000000000000000000000000000000000000000..e6f3cff877de784dadbef2831bf78b5e1cab64f7 GIT binary patch literal 94 zcmeAS@N?(olHy`uVBq!ia0vp^AT}2V6Od#IhB?Wc})s`>#g`% p+RlHFv^$*sgJ=Fj;~F4`S9%_U=4|mFJAq0VJYD@<);T3K0RX3`87%++ literal 0 HcmV?d00001 diff --git a/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/test/000002.txt b/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/test/000002.txt new file mode 100644 index 0000000000..3aca4b3e55 --- /dev/null +++ b/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/test/000002.txt @@ -0,0 +1,2 @@ +Car 0.88 3 -0.69 0 190 400 380 1.60 1.57 3.23 -2.70 1.74 3.68 -1.29 +DontCare -1 -1 -10 800 160 825 185 -1 -1 -1 -1000 -1000 -1000 -10 diff --git a/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/train/000000.txt b/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/train/000000.txt new file mode 100644 index 0000000000..9d035bc092 --- /dev/null +++ b/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/train/000000.txt @@ -0,0 +1 @@ +Pedestrian 0.00 0 -0.20 700 150 800 300 1.89 0.48 1.20 1.84 1.47 8.41 0.01 diff --git a/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/val/000001.txt b/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/val/000001.txt new file mode 100644 index 0000000000..2bac65fc4a --- /dev/null +++ b/tests/assets/kitti_dataset/kitti_3d_with_subset/label_2/val/000001.txt @@ -0,0 +1,2 @@ +Pedestrian 0.00 0 1.94 330 180 360 240 1.87 0.96 0.65 -8.50 2.07 23.02 1.59 +DontCare -1 -1 -10 600 170 620 185 -1 -1 -1 -1000 -1000 -1000 -10 diff --git a/tests/unit/test_kitti_3d_format.py b/tests/unit/test_kitti_3d_format.py index c6ffa2fbf3..3dbadb2507 100644 --- a/tests/unit/test_kitti_3d_format.py +++ b/tests/unit/test_kitti_3d_format.py @@ -14,8 +14,8 @@ from tests.utils.assets import get_test_asset_path from tests.utils.test_utils import compare_datasets_3d -DUMMY_DATASET_DIR = get_test_asset_path("kitti_dataset", "kitti_3d", "training") -DUMMY_SUBSET_DATASET_DIR = get_test_asset_path("kitti_dataset", "kitti_3d", "subset") +DUMMY_DATASET_DIR = get_test_asset_path("kitti_dataset", "kitti_3d") +DUMMY_SUBSET_DATASET_DIR = get_test_asset_path("kitti_dataset", "kitti_3d_with_subset") class Kitti3DImporterTest(TestCase): @@ -40,16 +40,27 @@ def test_can_load(self): 2. Load the dataset from the KITTI3D format. 3. Compare the loaded dataset with the expected dataset. """ - pcd1 = osp.join(DUMMY_DATASET_DIR, "velodyne", "000001.bin") image1 = Image.from_file(path=osp.join(DUMMY_DATASET_DIR, "image_2", "000001.png")) expected_label_cat = LabelCategories( attributes={"occluded", "truncated", "alpha", "dimensions", "location", "rotation_y"} ) - expected_label_cat.add("Truck") - expected_label_cat.add("Car") - expected_label_cat.add("DontCare") + expected_label_list = [ + "DontCare", + "Car", + "Pedestrian", + "Van", + "Truck", + "Cyclist", + "Sitter", + "Train", + "Motorcycle", + "Bus", + "Misc", + ] + for label in expected_label_list: + expected_label_cat.add(label) expected_dataset = Dataset.from_iterable( [ DatasetItem( @@ -60,7 +71,7 @@ def test_can_load(self): 150, # y1 30, # x2-x1 40, # y2-y1 - label=0, + label=4, id=0, attributes={ "truncated": 0.0, @@ -92,7 +103,7 @@ def test_can_load(self): 170, # y1 90, # x2-x1 20, # y2-y1 - label=2, + label=0, id=2, attributes={ "truncated": -1.0, @@ -104,12 +115,11 @@ def test_can_load(self): }, ), ], - media=PointCloud.from_file(path=pcd1, extra_images=[image1]), + media=image1, attributes={"calib_path": osp.join(DUMMY_DATASET_DIR, "calib", "000001.txt")}, ), ], categories={AnnotationType.label: expected_label_cat}, - media_type=PointCloud, ) parsed_dataset = Dataset.import_from(DUMMY_DATASET_DIR, "kitti3d") @@ -134,20 +144,33 @@ def test_can_load_with_subset(self): expected_label_cat = LabelCategories( attributes={"occluded", "truncated", "alpha", "dimensions", "location", "rotation_y"} ) - expected_label_cat.add("Pedestrian") - expected_label_cat.add("DontCare") - expected_label_cat.add("Car") + expected_label_list = [ + "DontCare", + "Car", + "Pedestrian", + "Van", + "Truck", + "Cyclist", + "Sitter", + "Train", + "Motorcycle", + "Bus", + "Misc", + ] + for label in expected_label_list: + expected_label_cat.add(label) expected_dataset = Dataset.from_iterable( [ DatasetItem( id="000000", + subset="train", annotations=[ Bbox( - 100, # x1 + 700, # x1 150, # y1 100, # x2-x1 150, # y2-y1 - label=0, + label=2, id=0, attributes={ "truncated": 0.0, @@ -159,20 +182,25 @@ def test_can_load_with_subset(self): }, ), ], - media=Image.from_numpy(data=np.ones((1, 5, 3))), + media=Image.from_file( + path=osp.join(DUMMY_SUBSET_DATASET_DIR, "image_2", "train", "000000.png") + ), attributes={ - "calib_path": osp.join(DUMMY_SUBSET_DATASET_DIR, "calib", "000000.txt") + "calib_path": osp.join( + DUMMY_SUBSET_DATASET_DIR, "calib", "train", "000000.txt" + ) }, ), DatasetItem( id="000001", + subset="val", annotations=[ Bbox( 330, # x1 180, # y1 30, # x2-x1 60, # y2-y1 - label=0, + label=2, id=0, attributes={ "truncated": 0.0, @@ -188,8 +216,8 @@ def test_can_load_with_subset(self): 170, # y1 20, # x2-x1 15, # y2-y1 - label=1, - id=0, + label=0, + id=1, attributes={ "truncated": -1, "occluded": -1, @@ -200,20 +228,25 @@ def test_can_load_with_subset(self): }, ), ], - media=Image.from_numpy(data=np.ones((1, 5, 3))), + media=Image.from_file( + path=osp.join(DUMMY_SUBSET_DATASET_DIR, "image_2", "val", "000001.png") + ), attributes={ - "calib_path": osp.join(DUMMY_SUBSET_DATASET_DIR, "calib", "000001.txt") + "calib_path": osp.join( + DUMMY_SUBSET_DATASET_DIR, "calib", "val", "000001.txt" + ) }, ), DatasetItem( id="000002", + subset="test", annotations=[ Bbox( 0, # x1 190, # y1 400, # x2-x1 190, # y2-y1 - label=2, + label=1, id=0, attributes={ "truncated": 0.88, @@ -228,9 +261,9 @@ def test_can_load_with_subset(self): 800, # x1 160, # y1 25, # x2-x1 - 15, # y2-y1 - label=1, - id=0, + 25, # y2-y1 + label=0, + id=1, attributes={ "truncated": -1, "occluded": -1, @@ -241,9 +274,13 @@ def test_can_load_with_subset(self): }, ), ], - media=Image.from_numpy(data=np.ones((1, 5, 3))), + media=Image.from_file( + path=osp.join(DUMMY_SUBSET_DATASET_DIR, "image_2", "test", "000002.png") + ), attributes={ - "calib_path": osp.join(DUMMY_SUBSET_DATASET_DIR, "calib", "000002.txt") + "calib_path": osp.join( + DUMMY_SUBSET_DATASET_DIR, "calib", "test", "000002.txt" + ) }, ), ],