Shaun ZhouandClaude Opus 5
d6adea5b05
88 个测试覆盖配置继承、注册表、GPU 守卫、YOLO 格式解析、数据集、模型形状、 标签模式、聚类原语与 SimCLR 损失，以及 train.py / eval.py / 聚类脚本的入口接线。 含两条回归测试： - PCA 白化放大噪声方向导致簇塌陷（默认 whiten=False 的依据） - classes 写成 data.yaml 路径时 num_classes 必须是类别数而非路径字符串长度 Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import pytest
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pytest.importorskip("numpy")
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pytest.importorskip("torch")
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import numpy as np # noqa: E402
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from datasets.target_encoder import CenterTargetEncoder, gaussian_radius # noqa: E402
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def test_gaussian_radius_is_positive_and_scales():
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assert gaussian_radius(40, 40) > gaussian_radius(10, 10) > 0
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def test_encoder_marks_single_center():
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encoder = CenterTargetEncoder(num_classes=3, stride=4)
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boxes = np.array([[40.0, 40.0, 80.0, 80.0]])
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labels = np.array([1])
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target = encoder(boxes, labels, (256, 256))
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assert target["heatmap"].shape == (3, 64, 64)
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assert target["mask"].sum() == 1
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# 中心 (60, 60) / stride 4 = (15, 15)
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assert target["mask"][15, 15] == 1
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assert target["heatmap"][1].max() == pytest.approx(1.0)
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assert target["heatmap"][0].max() == 0
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assert target["wh"][:, 15, 15].tolist() == pytest.approx([10.0, 10.0])
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def test_encoder_skips_invalid_and_out_of_range_boxes():
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encoder = CenterTargetEncoder(num_classes=2, stride=4)
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boxes = np.array([[10.0, 10.0, 5.0, 5.0], [900.0, 900.0, 950.0, 950.0]])
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target = encoder(boxes, np.array([0, 1]), (256, 256))
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assert target["mask"].sum() == 0
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def test_encoder_respects_max_objects():
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encoder = CenterTargetEncoder(num_classes=1, stride=4, max_objects=2)
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boxes = np.array([[i * 20.0, 0.0, i * 20.0 + 16, 16.0] for i in range(5)])
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target = encoder(boxes, np.zeros(5, dtype=np.int64), (256, 256))
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assert target["mask"].sum() == 2
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