fix(pre_commit): 🎨 auto format pre-commit hooks
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pre-commit-ci[bot] committed
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2 files changed
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-232
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@@ -88,12 +88,12 @@ class KeyPoints:
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key_points = sv.KeyPoints.from_mediapipe(
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pose_landmarker_result, (image_width, image_height))
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```
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=== "Transformers"
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Use [`sv.KeyPoints.from_transformers`](/latest/keypoint/core/#supervision.key_points.core.KeyPoints.from_transformers)
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method, which accepts [ViTPose](https://huggingface.co/docs/transformers/en/model_doc/vitpose) result.
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```python
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from PIL import Image
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import requests
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@@ -650,7 +650,7 @@ class KeyPoints:
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return cls.empty()
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def __getitem__(
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self, index: int | slice | list[int] | np.ndarray | tuple | str
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self, index: int | slice | list[int] | np.ndarray | tuple | str
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) -> KeyPoints | np.ndarray | list | None:
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if isinstance(index, str):
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return self.data.get(index)
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@@ -674,22 +674,18 @@ class KeyPoints:
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j = np.flatnonzero(j)
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if (
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isinstance(i, (list, np.ndarray))
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and isinstance(j, (list, np.ndarray))
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and not np.isscalar(i)
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and not np.isscalar(j)
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isinstance(i, (list, np.ndarray))
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and isinstance(j, (list, np.ndarray))
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and not np.isscalar(i)
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and not np.isscalar(j)
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):
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i, j = np.ix_(i, j)
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xy_selected = self.xy[i, j]
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conf_selected = (
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self.confidence[i, j] if self.confidence is not None else None
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)
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conf_selected = self.confidence[i, j] if self.confidence is not None else None
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class_id_selected = (
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self.class_id[i] if self.class_id is not None else None
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)
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class_id_selected = self.class_id[i] if self.class_id is not None else None
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data_selected = get_data_item(self.data, i)
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@@ -699,13 +695,13 @@ class KeyPoints:
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conf_selected = conf_selected.reshape(1, 1)
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elif xy_selected.ndim == 2:
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if np.isscalar(index[0]) or (
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isinstance(index[0], np.ndarray) and index[0].ndim == 0
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isinstance(index[0], np.ndarray) and index[0].ndim == 0
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):
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xy_selected = xy_selected[np.newaxis, ...]
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if conf_selected is not None:
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conf_selected = conf_selected[np.newaxis, ...]
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elif np.isscalar(index[1]) or (
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isinstance(index[1], np.ndarray) and index[1].ndim == 0
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isinstance(index[1], np.ndarray) and index[1].ndim == 0
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):
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xy_selected = xy_selected[:, np.newaxis, :]
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if conf_selected is not None:
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+40
-216
@@ -1,33 +1,21 @@
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from contextlib import nullcontext as DoesNotRaise
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import numpy as np
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import pytest
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from contextlib import nullcontext as DoesNotRaise
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from supervision.key_points.core import KeyPoints
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from test.test_utils import mock_key_points
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KEY_POINTS = mock_key_points(
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xy=[
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[[0, 1],
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[2, 3],
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[4, 5],
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[6, 7],
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[8, 9]],
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[[10, 11],
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[12, 13],
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[14, 15],
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[16, 17],
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[18, 19]],
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[[20, 21],
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[22, 23],
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[24, 25],
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[26, 27],
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[28, 29]]
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[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]],
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[[10, 11], [12, 13], [14, 15], [16, 17], [18, 19]],
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[[20, 21], [22, 23], [24, 25], [26, 27], [28, 29]],
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],
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confidence=[
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[0.8, 0.2, 0.6, 0.1, 0.5],
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[0.7, 0.9, 0.3, 0.4, 0.0],
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[0.1, 0.6, 0.8, 0.2, 0.7]
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[0.1, 0.6, 0.8, 0.2, 0.7],
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],
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class_id=[0, 1, 2],
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)
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@@ -52,16 +40,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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slice(0, 1),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3],
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[4, 5],
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[6, 7],
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[8, 9]]
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],
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confidence=[
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[0.8, 0.2, 0.6, 0.1, 0.5]
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],
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xy=[[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]]],
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confidence=[[0.8, 0.2, 0.6, 0.1, 0.5]],
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class_id=[0],
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),
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DoesNotRaise(),
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@@ -71,17 +51,8 @@ KEY_POINTS = mock_key_points(
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slice(0, 2),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3],
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[4, 5],
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[6, 7],
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[8, 9]],
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[[10, 11],
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[12, 13],
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[14, 15],
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[16, 17],
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[18, 19]],
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[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]],
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[[10, 11], [12, 13], [14, 15], [16, 17], [18, 19]],
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],
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confidence=[
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[0.8, 0.2, 0.6, 0.1, 0.5],
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@@ -95,16 +66,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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0,
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3],
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[4, 5],
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[6, 7],
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[8, 9]]
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],
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confidence=[
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[0.8, 0.2, 0.6, 0.1, 0.5]
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],
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xy=[[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]]],
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confidence=[[0.8, 0.2, 0.6, 0.1, 0.5]],
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class_id=[0],
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),
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DoesNotRaise(),
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@@ -113,16 +76,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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-1,
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mock_key_points(
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xy=[
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[[20, 21],
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[22, 23],
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[24, 25],
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[26, 27],
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[28, 29]]
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],
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confidence=[
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[0.1, 0.6, 0.8, 0.2, 0.7]
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],
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xy=[[[20, 21], [22, 23], [24, 25], [26, 27], [28, 29]]],
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confidence=[[0.1, 0.6, 0.8, 0.2, 0.7]],
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class_id=[2],
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),
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DoesNotRaise(),
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@@ -132,17 +87,8 @@ KEY_POINTS = mock_key_points(
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[0, 1],
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3],
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[4, 5],
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[6, 7],
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[8, 9]],
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[[10, 11],
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[12, 13],
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[14, 15],
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[16, 17],
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[18, 19]],
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[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]],
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[[10, 11], [12, 13], [14, 15], [16, 17], [18, 19]],
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],
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confidence=[
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[0.8, 0.2, 0.6, 0.1, 0.5],
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@@ -157,17 +103,8 @@ KEY_POINTS = mock_key_points(
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np.array([0, 1]),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3],
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[4, 5],
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[6, 7],
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[8, 9]],
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[[10, 11],
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[12, 13],
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[14, 15],
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[16, 17],
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[18, 19]],
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[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]],
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[[10, 11], [12, 13], [14, 15], [16, 17], [18, 19]],
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],
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confidence=[
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[0.8, 0.2, 0.6, 0.1, 0.5],
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@@ -182,17 +119,8 @@ KEY_POINTS = mock_key_points(
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[True, True, False],
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3],
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[4, 5],
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[6, 7],
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[8, 9]],
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[[10, 11],
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[12, 13],
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[14, 15],
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[16, 17],
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[18, 19]],
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[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]],
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[[10, 11], [12, 13], [14, 15], [16, 17], [18, 19]],
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],
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confidence=[
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[0.8, 0.2, 0.6, 0.1, 0.5],
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@@ -207,17 +135,8 @@ KEY_POINTS = mock_key_points(
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np.array([True, True, False]),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3],
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[4, 5],
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[6, 7],
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[8, 9]],
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[[10, 11],
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[12, 13],
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[14, 15],
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[16, 17],
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[18, 19]],
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[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]],
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[[10, 11], [12, 13], [14, 15], [16, 17], [18, 19]],
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],
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confidence=[
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[0.8, 0.2, 0.6, 0.1, 0.5],
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@@ -237,18 +156,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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(slice(None), slice(0, 1)),
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mock_key_points(
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xy=[
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[[0, 1]],
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[[10, 11]],
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[[20, 21]]
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],
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confidence=[
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[0.8],
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[0.7],
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[0.1]
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],
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xy=[[[0, 1]], [[10, 11]], [[20, 21]]],
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confidence=[[0.8], [0.7], [0.1]],
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class_id=[0, 1, 2],
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),
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DoesNotRaise(),
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@@ -257,21 +166,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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(slice(None), slice(0, 2)),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3]],
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[[10, 11],
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[12, 13]],
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[[20, 21],
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[22, 23]]
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],
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confidence=[
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[0.8, 0.2],
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[0.7, 0.9],
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[0.1, 0.6]
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],
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xy=[[[0, 1], [2, 3]], [[10, 11], [12, 13]], [[20, 21], [22, 23]]],
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confidence=[[0.8, 0.2], [0.7, 0.9], [0.1, 0.6]],
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class_id=[0, 1, 2],
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),
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DoesNotRaise(),
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@@ -280,18 +176,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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(slice(None), 0),
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mock_key_points(
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xy=[
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[[0, 1]],
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[[10, 11]],
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[[20, 21]]
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],
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confidence=[
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[0.8],
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[0.7],
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[0.1]
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],
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xy=[[[0, 1]], [[10, 11]], [[20, 21]]],
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confidence=[[0.8], [0.7], [0.1]],
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class_id=[0, 1, 2],
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),
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DoesNotRaise(),
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@@ -300,18 +186,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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(slice(None), -1),
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mock_key_points(
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xy=[
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[[8, 9]],
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[[18, 19]],
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[[28, 29]]
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],
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confidence=[
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[0.5],
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[0.0],
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[0.7]
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],
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xy=[[[8, 9]], [[18, 19]], [[28, 29]]],
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confidence=[[0.5], [0.0], [0.7]],
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class_id=[0, 1, 2],
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),
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DoesNotRaise(),
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@@ -320,21 +196,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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(slice(None), [0, 1]),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3]],
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[[10, 11],
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[12, 13]],
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[[20, 21],
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[22, 23]]
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],
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confidence=[
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[0.8, 0.2],
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[0.7, 0.9],
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[0.1, 0.6]
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],
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xy=[[[0, 1], [2, 3]], [[10, 11], [12, 13]], [[20, 21], [22, 23]]],
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confidence=[[0.8, 0.2], [0.7, 0.9], [0.1, 0.6]],
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class_id=[0, 1, 2],
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),
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DoesNotRaise(),
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@@ -343,21 +206,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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(slice(None), np.array([0, 1])),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3]],
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[[10, 11],
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[12, 13]],
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[[20, 21],
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[22, 23]]
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],
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confidence=[
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[0.8, 0.2],
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[0.7, 0.9],
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[0.1, 0.6]
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],
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xy=[[[0, 1], [2, 3]], [[10, 11], [12, 13]], [[20, 21], [22, 23]]],
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confidence=[[0.8, 0.2], [0.7, 0.9], [0.1, 0.6]],
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class_id=[0, 1, 2],
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),
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DoesNotRaise(),
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@@ -366,21 +216,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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(slice(None), [True, True, False, False, False]),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3]],
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|
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[[10, 11],
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[12, 13]],
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|
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[[20, 21],
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[22, 23]]
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],
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confidence=[
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[0.8, 0.2],
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[0.7, 0.9],
|
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[0.1, 0.6]
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],
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xy=[[[0, 1], [2, 3]], [[10, 11], [12, 13]], [[20, 21], [22, 23]]],
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confidence=[[0.8, 0.2], [0.7, 0.9], [0.1, 0.6]],
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class_id=[0, 1, 2],
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),
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DoesNotRaise(),
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@@ -389,21 +226,8 @@ KEY_POINTS = mock_key_points(
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KEY_POINTS,
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(slice(None), np.array([True, True, False, False, False])),
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mock_key_points(
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xy=[
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[[0, 1],
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[2, 3]],
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|
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[[10, 11],
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[12, 13]],
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||||
|
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[[20, 21],
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[22, 23]]
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||||
],
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confidence=[
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[0.8, 0.2],
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[0.7, 0.9],
|
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[0.1, 0.6]
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],
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xy=[[[0, 1], [2, 3]], [[10, 11], [12, 13]], [[20, 21], [22, 23]]],
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confidence=[[0.8, 0.2], [0.7, 0.9], [0.1, 0.6]],
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class_id=[0, 1, 2],
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),
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DoesNotRaise(),
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@@ -422,7 +246,7 @@ KEY_POINTS = mock_key_points(
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),
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DoesNotRaise(),
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), # select the first anchor from the first skeleton by index
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(
|
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(
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KEY_POINTS,
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(0, -1),
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mock_key_points(
|
||||
|
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