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Fix: Lightly object detection input: Key error #12

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merged 3 commits into from
Nov 15, 2023
Merged

Fix: Lightly object detection input: Key error #12

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4c25f39
Raise descriptive error if image not found
Nov 14, 2023
d35fceb
Skip labels without image
Nov 14, 2023
7cffdeb
Re Michal
Nov 15, 2023
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4 changes: 4 additions & 0 deletions src/labelformat/errors.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,4 @@
class LabelWithoutImageError(Exception):
"""Raised when a label is found without a corresponding image."""

pass
15 changes: 14 additions & 1 deletion src/labelformat/formats/lightly.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@

from labelformat import utils
from labelformat.cli.registry import Task, cli_register
from labelformat.errors import LabelWithoutImageError
from labelformat.model.bounding_box import BoundingBox, BoundingBoxFormat
from labelformat.model.category import Category
from labelformat.model.image import Image
Expand All @@ -15,7 +16,6 @@
ObjectDetectionOutput,
SingleObjectDetection,
)
from labelformat.types import JsonDict


@cli_register(format="lightly", task=Task.OBJECT_DETECTION)
Expand All @@ -34,14 +34,21 @@ def add_cli_arguments(parser: ArgumentParser) -> None:
default="../images",
help="Relative path to images folder from label folder",
)
parser.add_argument(
"--skip-labels-without-image",
action="store_true",
help="Skip labels without corresponding image",
)

def __init__(
self,
input_folder: Path,
images_rel_path: str = "../images",
skip_labels_without_image: bool = False,
) -> None:
self._input_folder = input_folder
self._images_rel_path = images_rel_path
self._skip_labels_without_image = skip_labels_without_image
self._categories = self._get_categories()

def get_categories(self) -> Iterable[Category]:
Expand All @@ -62,6 +69,12 @@ def get_labels(self) -> Iterable[ImageObjectDetection]:
if json_path.name == "schema.json":
continue
data = json.loads(json_path.read_text())
if data["file_name"] not in filename_to_image:
if self._skip_labels_without_image:
continue
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raise LabelWithoutImageError(
f"Label '{json_path.name}' does not have a corresponding image."
)
image = filename_to_image[data["file_name"]]
objects = []
for prediction in data["predictions"]:
Expand Down
221 changes: 221 additions & 0 deletions tests/unit/formats/test_lightly.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,221 @@
import json
from pathlib import Path

import pytest
from pytest_mock import MockerFixture

from labelformat.errors import LabelWithoutImageError
from labelformat.formats.lightly import (
LightlyObjectDetectionInput,
LightlyObjectDetectionOutput,
)
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,
SingleObjectDetection,
)

from ...simple_object_detection_label_input import SimpleObjectDetectionInput


class TestLightlyObjectDetectionInput:
def test_get_labels(self, tmp_path: Path, mocker: MockerFixture) -> None:
# Prepare inputs.
annotation = json.dumps(
{
"file_name": "image.jpg",
"predictions": [
{
"category_id": 1,
"bbox": [10.0, 20.0, 20.0, 20.0],
},
{
"category_id": 0,
"bbox": [50.0, 60.0, 20.0, 20.0],
},
],
}
)
label_path = tmp_path / "labels" / "image.json"
label_path.parent.mkdir(parents=True, exist_ok=True)
label_path.write_text(annotation)

schema = json.dumps(
{
"task_type": "object-detection",
"categories": [
{"name": "cat", "id": 0},
{"name": "dog", "id": 1},
{"name": "cow", "id": 2},
],
}
)
schema_path = tmp_path / "labels" / "schema.json"
schema_path.write_text(schema)

# Mock the image file.
(tmp_path / "images").mkdir()
(tmp_path / "images/image.jpg").touch()
mocker.patch("PIL.Image.open", autospec=True).return_value.size = (100, 200)

# Convert.
label_input = LightlyObjectDetectionInput(
input_folder=tmp_path / "labels",
images_rel_path="../images",
)
labels = list(label_input.get_labels())
assert labels == [
ImageObjectDetection(
image=Image(id=0, filename="image.jpg", width=100, height=200),
objects=[
SingleObjectDetection(
category=Category(id=1, name="dog"),
box=BoundingBox(
xmin=10.0,
ymin=20.0,
xmax=30.0,
ymax=40.0,
),
),
SingleObjectDetection(
category=Category(id=0, name="cat"),
box=BoundingBox(
xmin=50.0,
ymin=60.0,
xmax=70.0,
ymax=80.0,
),
),
],
)
]

def test_get_labels__raises_label_without_image(
self, tmp_path: Path, mocker: MockerFixture
) -> None:
# Prepare inputs.
annotation = json.dumps(
{
"file_name": "image.jpg",
"predictions": [
{
"category_id": 0,
"bbox": [10.0, 20.0, 20.0, 20.0],
},
{
"category_id": 1,
"bbox": [50.0, 60.0, 20.0, 20.0],
},
],
}
)
label_path = tmp_path / "labels" / "image.json"
label_path.parent.mkdir(parents=True, exist_ok=True)
label_path.write_text(annotation)

schema = json.dumps(
{
"task_type": "object-detection",
"categories": [
{"name": "cat", "id": 0},
{"name": "dog", "id": 1},
{"name": "cow", "id": 2},
],
}
)
schema_path = tmp_path / "labels" / "schema.json"
schema_path.write_text(schema)

# Try to convert.
label_input = LightlyObjectDetectionInput(
input_folder=tmp_path / "labels",
images_rel_path="../images",
)
with pytest.raises(
LabelWithoutImageError,
match="Label 'image.json' does not have a corresponding image.",
):
list(label_input.get_labels())

def test_get_labels__skip_label_without_image(
self, tmp_path: Path, mocker: MockerFixture
) -> None:
# Prepare inputs.
annotation = json.dumps(
{
"file_name": "image.jpg",
"predictions": [
{
"category_id": 0,
"bbox": [10.0, 20.0, 20.0, 20.0],
},
{
"category_id": 1,
"bbox": [50.0, 60.0, 20.0, 20.0],
},
],
}
)
label_path = tmp_path / "labels" / "image.json"
label_path.parent.mkdir(parents=True, exist_ok=True)
label_path.write_text(annotation)

schema = json.dumps(
{
"task_type": "object-detection",
"categories": [
{"name": "cat", "id": 0},
{"name": "dog", "id": 1},
{"name": "cow", "id": 2},
],
}
)
schema_path = tmp_path / "labels" / "schema.json"
schema_path.write_text(schema)
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# Convert.
label_input = LightlyObjectDetectionInput(
input_folder=tmp_path / "labels",
images_rel_path="../images",
skip_labels_without_image=True,
)
assert list(label_input.get_labels()) == []


class TestLightlyObjectDetectionOutput:
def test_save(self, tmp_path: Path) -> None:
output_folder = tmp_path / "labels"
LightlyObjectDetectionOutput(output_folder=output_folder).save(
label_input=SimpleObjectDetectionInput()
)
assert output_folder.exists()
assert output_folder.is_dir()

filepaths = sorted(list(output_folder.glob("**/*")))
assert filepaths == [
tmp_path / "labels" / "image.json",
tmp_path / "labels" / "schema.json",
]

contents = (tmp_path / "labels" / "image.json").read_text()
expected = json.dumps(
{
"file_name": "image.jpg",
"predictions": [
{
"category_id": 1,
"bbox": [10.0, 20.0, 20.0, 20.0],
"score": 0.0, # default
},
{
"category_id": 0,
"bbox": [50.0, 60.0, 20.0, 20.0],
"score": 0.0, # default
},
],
},
indent=2,
)
assert contents == expected