Jirka Borovecandpre-commit-ci[bot]
2d0404e67c
* Extend docstrings to test cases for enhanced readability and consistency across testing modules * Extend test case docstrings across multiple modules for improved clarity and consistency * Refactor test case docstrings for clarity and consistency in `test_annotators.py` --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
190 lines
7.1 KiB
Python
190 lines
7.1 KiB
Python
from __future__ import annotations
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from contextlib import ExitStack as DoesNotRaise
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import pytest
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from supervision import DetectionDataset
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from tests.helpers import _create_detections
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@pytest.mark.parametrize(
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("dataset_list", "expected_result", "exception"),
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[
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(
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[],
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DetectionDataset(classes=[], images=[], annotations={}),
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DoesNotRaise(),
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), # empty dataset list
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(
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[DetectionDataset(classes=[], images=[], annotations={})],
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DetectionDataset(classes=[], images=[], annotations={}),
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DoesNotRaise(),
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), # single empty dataset
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(
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[
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DetectionDataset(classes=["dog", "person"], images=[], annotations={}),
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DetectionDataset(classes=["dog", "person"], images=[], annotations={}),
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],
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DetectionDataset(classes=["dog", "person"], images=[], annotations={}),
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DoesNotRaise(),
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), # two datasets; no images and annotations, the same classes
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(
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[
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DetectionDataset(classes=["dog", "person"], images=[], annotations={}),
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DetectionDataset(classes=["cat"], images=[], annotations={}),
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],
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DetectionDataset(
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classes=["cat", "dog", "person"], images=[], annotations={}
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),
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DoesNotRaise(),
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), # two datasets; no images and annotations, different classes
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(
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[
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DetectionDataset(
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classes=["dog", "person"],
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images=["image-1.png", "image-2.png"],
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annotations={
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"image-1.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[0]
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),
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"image-2.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[1]
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),
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},
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),
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DetectionDataset(classes=[], images=[], annotations={}),
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],
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DetectionDataset(
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classes=["dog", "person"],
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images=["image-1.png", "image-2.png"],
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annotations={
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"image-1.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[0]
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),
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"image-2.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[1]
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),
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},
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),
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DoesNotRaise(),
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), # two datasets; images and annotations, the same classes
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(
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[
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DetectionDataset(
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classes=["dog", "person"],
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images=["image-1.png", "image-2.png"],
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annotations={
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"image-1.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[0]
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),
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"image-2.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[1]
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),
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},
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),
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DetectionDataset(classes=["cat"], images=[], annotations={}),
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],
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DetectionDataset(
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classes=["cat", "dog", "person"],
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images=["image-1.png", "image-2.png"],
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annotations={
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"image-1.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[1]
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),
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"image-2.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[2]
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),
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},
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),
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DoesNotRaise(),
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), # two datasets; images and annotations, different classes
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(
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[
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DetectionDataset(
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classes=["dog", "person"],
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images=["image-1.png", "image-2.png"],
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annotations={
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"image-1.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[0]
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),
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"image-2.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[1]
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),
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},
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),
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DetectionDataset(
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classes=["cat"],
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images=["image-3.png"],
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annotations={
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"image-3.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[0]
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),
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},
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),
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],
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DetectionDataset(
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classes=["cat", "dog", "person"],
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images=["image-1.png", "image-2.png", "image-3.png"],
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annotations={
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"image-1.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[1]
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),
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"image-2.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[2]
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),
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"image-3.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[0]
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),
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},
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),
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DoesNotRaise(),
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), # two datasets; images and annotations, different classes
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(
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[
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DetectionDataset(
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classes=["dog", "person"],
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images=["image-1.png", "image-2.png"],
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annotations={
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"image-1.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[0]
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),
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"image-2.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[1]
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),
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},
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),
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DetectionDataset(
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classes=["dog", "person"],
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images=["image-2.png", "image-3.png"],
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annotations={
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"image-2.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[0]
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),
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"image-3.png": _create_detections(
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xyxy=[[0, 0, 10, 10]], class_id=[1]
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),
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},
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),
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],
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None,
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pytest.raises(ValueError),
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),
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],
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)
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def test_dataset_merge(
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dataset_list: list[DetectionDataset],
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expected_result: DetectionDataset | None,
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exception: Exception,
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) -> None:
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"""
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Verify that multiple DetectionDataset objects can be successfully merged.
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Ensures that multiple `DetectionDataset` objects can be merged into single dataset.
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This is vital for users who need to combine data from different sources or
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augment their datasets with additional labeled examples.
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"""
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with exception:
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result = DetectionDataset.merge(dataset_list=dataset_list)
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assert result == expected_result
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