Kitti: Replace " " by "_"

src/labelformat/formats/kitti.py

@@ -126,9 +126,10 @@ def save(self, label_input: ObjectDetectionInput) -> None:
                     left, top, right, bottom = obj.box.to_format(
                         format=BoundingBoxFormat.XYXY
                     )
+                    category_name = obj.category.name.replace(" ", "_")
                     # Unknown values match Kitti dataset "DontCare" label values.
                     file.write(
-                        f"{obj.category.name} "
+                        f"{category_name} "
                         "-1 "  # truncated
                         "-1 "  # occluded
                         "-10 "  # alpha

tests/unit/formats/test_kitti.py

@@ -1,6 +1,5 @@
 from argparse import ArgumentParser
 from pathlib import Path
-from typing import Iterable
 
 import pytest
 from pytest_mock import MockerFixture
@@ -9,12 +8,12 @@
     KittiObjectDetectionInput,
     KittiObjectDetectionOutput,
 )
+from labelformat.formats.labelformat import LabelformatObjectDetectionInput
 from labelformat.model.bounding_box import BoundingBox
 from labelformat.model.category import Category
 from labelformat.model.image import Image
 from labelformat.model.object_detection import (
     ImageObjectDetection,
-    ObjectDetectionInput,
     SingleObjectDetection,
 )
 
@@ -96,3 +95,32 @@ def test_save(self, tmp_path: Path, with_confidence: bool) -> None:
             "cat -1 -1 -10 50.0 60.0 70.0 80.0 -1 -1 -1 -1000 -1000 -1000 -10\n"
         )
         assert contents == expected
+
+    def test_save_replaces_spaces_in_category_name(self, tmp_path: Path) -> None:
+        output_folder = tmp_path / "labels"
+        categories = [
+            Category(id=0, name="traffic light"),
+        ]
+        image = Image(id=0, filename="image.jpg", width=100, height=200)
+        label_input = LabelformatObjectDetectionInput(
+            categories=categories,
+            images=[image],
+            labels=[
+                ImageObjectDetection(
+                    image=image,
+                    objects=[
+                        SingleObjectDetection(
+                            category=categories[0],
+                            box=BoundingBox(xmin=10.0, ymin=20.0, xmax=30.0, ymax=40.0),
+                        ),
+                    ],
+                )
+            ],
+        )
+
+        KittiObjectDetectionOutput(output_folder=output_folder).save(
+            label_input=label_input
+        )
+
+        contents = (output_folder / "image.txt").read_text()
+        assert contents.startswith("traffic_light ")