328 lines
10 KiB
Python
328 lines
10 KiB
Python
from contextlib import ExitStack as DoesNotRaise
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import pytest
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from supervision import Detections, Position
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from typing import Optional, Union, List
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import numpy as np
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from test.utils import mock_detections
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PREDICTIONS = np.array([
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[ 2254, 906, 2447, 1353, 0.90538, 0],
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[ 2049, 1133, 2226, 1371, 0.59002, 56],
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[ 727, 1224, 838, 1601, 0.51119, 39],
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[ 808, 1214, 910, 1564, 0.45287, 39],
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[ 6, 52, 1131, 2133, 0.45057, 72],
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[ 299, 1225, 512, 1663, 0.45029, 39],
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[ 529, 874, 645, 945, 0.31101, 39],
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[ 8, 47, 1935, 2135, 0.28192, 72],
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[ 2265, 813, 2328, 901, 0.2714, 62]
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], dtype=np.float32)
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DETECTIONS = Detections(
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xyxy=PREDICTIONS[:, :4],
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confidence=PREDICTIONS[:, 4],
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class_id=PREDICTIONS[:, 5].astype(int)
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)
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@pytest.mark.parametrize(
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'detections, index, expected_result, exception',
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[
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(
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DETECTIONS,
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DETECTIONS.class_id == 0,
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mock_detections(
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xyxy=[[2254, 906, 2447, 1353]],
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confidence=[0.90538],
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class_id=[0]
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),
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DoesNotRaise()
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), # take only detections with class_id = 0
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(
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DETECTIONS,
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DETECTIONS.confidence > 0.5,
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mock_detections(
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xyxy=[
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[2254, 906, 2447, 1353],
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[2049, 1133, 2226, 1371],
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[727, 1224, 838, 1601]
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],
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confidence=[0.90538, 0.59002, 0.51119],
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class_id=[0, 56, 39]
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),
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DoesNotRaise()
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), # take only detections with confidence > 0.5
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(
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DETECTIONS,
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np.array([True, True, True, True, True, True, True, True, True], dtype=bool),
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DETECTIONS,
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DoesNotRaise()
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), # take all detections
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(
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DETECTIONS,
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np.array([False, False, False, False, False, False, False, False, False], dtype=bool),
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Detections(
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xyxy=np.empty((0, 4), dtype=np.float32),
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confidence=np.array([], dtype=np.float32),
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class_id=np.array([], dtype=int)
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),
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DoesNotRaise()
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), # take no detections
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(
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DETECTIONS,
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[0, 2],
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mock_detections(
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xyxy=[
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[2254, 906, 2447, 1353],
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[727, 1224, 838, 1601]
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],
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confidence=[0.90538, 0.51119],
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class_id=[0, 39]
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),
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DoesNotRaise()
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), # take only first and third detection using List[int] index
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(
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DETECTIONS,
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np.array([0, 2]),
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mock_detections(
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xyxy=[
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[2254, 906, 2447, 1353],
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[727, 1224, 838, 1601]
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],
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confidence=[0.90538, 0.51119],
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class_id=[0, 39]
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),
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DoesNotRaise()
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), # take only first and third detection using np.ndarray index
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(
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DETECTIONS,
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0,
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mock_detections(
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xyxy=[[2254, 906, 2447, 1353]],
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confidence=[0.90538],
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class_id=[0]
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),
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DoesNotRaise()
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), # take only first detection by index
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(
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DETECTIONS,
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slice(1, 3),
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mock_detections(
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xyxy=[
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[2049, 1133, 2226, 1371],
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[727, 1224, 838, 1601]
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],
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confidence=[0.59002, 0.51119],
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class_id=[56, 39]
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),
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DoesNotRaise()
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), # take only first detection by index slice (1, 3)
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(
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DETECTIONS,
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10,
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None,
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pytest.raises(IndexError)
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), # index out of range
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(
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DETECTIONS,
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[0, 2, 10],
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None,
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pytest.raises(IndexError)
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), # index out of range
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(
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DETECTIONS,
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np.array([0, 2, 10]),
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None,
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pytest.raises(IndexError)
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),
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(
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DETECTIONS,
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np.array([True, True, True, True, True, True, True, True, True, True, True]),
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None,
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pytest.raises(IndexError)
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)
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]
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)
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def test_getitem(
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detections: Detections,
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index: Union[int, slice, List[int], np.ndarray],
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expected_result: Optional[Detections],
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exception: Exception
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) -> None:
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with exception:
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result = detections[index]
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assert result == expected_result
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@pytest.mark.parametrize(
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'detections_list, expected_result, exception',
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[
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(
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[],
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Detections.empty(),
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DoesNotRaise()
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), # empty detections list
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(
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[
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Detections.empty()
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],
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Detections.empty(),
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DoesNotRaise()
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), # single empty detections
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(
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[
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mock_detections(xyxy=[[10, 10, 20, 20]])
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],
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mock_detections(xyxy=[[10, 10, 20, 20]]),
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DoesNotRaise()
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), # single detection with xyxy field
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(
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[
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mock_detections(xyxy=[[10, 10, 20, 20]]),
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Detections.empty()
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],
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mock_detections(xyxy=[[10, 10, 20, 20]]),
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DoesNotRaise()
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), # single detection with xyxy field + empty detection
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(
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[
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mock_detections(xyxy=[[10, 10, 20, 20]]),
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mock_detections(xyxy=[[20, 20, 30, 30]])
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],
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mock_detections(
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xyxy=[
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[10, 10, 20, 20],
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[20, 20, 30, 30]
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]),
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DoesNotRaise()
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), # two detections with xyxy field
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(
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[
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mock_detections(
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xyxy=[[10, 10, 20, 20]],
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class_id=[0]),
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mock_detections(
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xyxy=[[20, 20, 30, 30]])
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],
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mock_detections(
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xyxy=[
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[10, 10, 20, 20],
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[20, 20, 30, 30]
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]),
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DoesNotRaise()
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), # detection with xyxy, class_id fields + detection with xyxy field
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(
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[
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mock_detections(
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xyxy=[[10, 10, 20, 20]],
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class_id=[0]),
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mock_detections(
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xyxy=[[20, 20, 30, 30]],
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class_id=[1]),
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],
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mock_detections(
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xyxy=[
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[10, 10, 20, 20],
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[20, 20, 30, 30]
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],
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class_id=[0, 1]
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),
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DoesNotRaise()
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), # two detections with xyxy, class_id fields
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]
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)
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def test_merge(
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detections_list: List[Detections],
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expected_result: Optional[Detections],
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exception: Exception
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) -> None:
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with exception:
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result = Detections.merge(detections_list=detections_list)
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assert result == expected_result
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@pytest.mark.parametrize(
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'detections, anchor, expected_result, exception',
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[
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(
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Detections.empty(),
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Position.CENTER,
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np.empty((0, 2), dtype=np.float32),
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DoesNotRaise()
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), # empty detections
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(
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mock_detections(xyxy=[[10, 10, 20, 20]]),
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Position.CENTER,
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np.array([[15, 15]], dtype=np.float32),
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DoesNotRaise()
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), # single detection; center anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.CENTER,
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np.array([[15, 15], [25, 25]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; center anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.CENTER_LEFT,
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np.array([[10, 15], [20, 25]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; center left anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.CENTER_RIGHT,
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np.array([[20, 15], [30, 25]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; center right anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.TOP_CENTER,
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np.array([[15, 10], [25, 20]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; top center anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.TOP_LEFT,
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np.array([[10, 10], [20, 20]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; top left anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.TOP_RIGHT,
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np.array([[20, 10], [30, 20]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; top right anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.BOTTOM_CENTER,
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np.array([[15, 20], [25, 30]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; bottom center anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.BOTTOM_LEFT,
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np.array([[10, 20], [20, 30]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; bottom left anchor
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(
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mock_detections(xyxy=[[10, 10, 20, 20], [20, 20, 30, 30]]),
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Position.BOTTOM_RIGHT,
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np.array([[20, 20], [30, 30]], dtype=np.float32),
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DoesNotRaise()
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), # two detections; bottom right anchor
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]
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)
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def test_get_anchor_coordinates(
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detections: Detections,
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anchor: Position,
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expected_result: np.ndarray,
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exception: Exception
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) -> None:
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result = detections.get_anchor_coordinates(anchor)
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with exception:
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assert np.array_equal(result, expected_result)
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