fix(pre_commit): 🎨 auto format pre-commit hooks
This commit is contained in:
parent
2c67cee720
commit
2907c40ecc
|
|
@ -1,8 +1,8 @@
|
|||
"""
|
||||
Tests for Mean Average Precision ID=0 bug fix
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from supervision.detection.core import Detections
|
||||
from supervision.metrics.mean_average_precision import MeanAveragePrecision
|
||||
|
|
@ -14,13 +14,13 @@ def test_single_perfect_detection():
|
|||
detection = Detections(
|
||||
xyxy=np.array([[10, 10, 50, 50]], dtype=np.float64),
|
||||
class_id=np.array([0]),
|
||||
confidence=np.array([0.9])
|
||||
confidence=np.array([0.9]),
|
||||
)
|
||||
|
||||
|
||||
metric = MeanAveragePrecision()
|
||||
metric.update([detection], [detection])
|
||||
result = metric.compute()
|
||||
|
||||
|
||||
# Should be perfect 1.0 mAP, not 0.0 due to ID=0 bug
|
||||
assert abs(result.map50_95 - 1.0) < 1e-6
|
||||
|
||||
|
|
@ -29,19 +29,18 @@ def test_multiple_perfect_detections():
|
|||
"""Test that multiple perfect detections get 1.0 mAP"""
|
||||
# Multiple perfect detections in one image
|
||||
detections = Detections(
|
||||
xyxy=np.array([
|
||||
[10, 10, 50, 50],
|
||||
[100, 100, 140, 140],
|
||||
[200, 200, 240, 240]
|
||||
], dtype=np.float64),
|
||||
xyxy=np.array(
|
||||
[[10, 10, 50, 50], [100, 100, 140, 140], [200, 200, 240, 240]],
|
||||
dtype=np.float64,
|
||||
),
|
||||
class_id=np.array([0, 0, 0]),
|
||||
confidence=np.array([0.9, 0.9, 0.9])
|
||||
confidence=np.array([0.9, 0.9, 0.9]),
|
||||
)
|
||||
|
||||
|
||||
metric = MeanAveragePrecision()
|
||||
metric.update([detections], [detections])
|
||||
result = metric.compute()
|
||||
|
||||
|
||||
# Should be perfect 1.0 mAP
|
||||
assert abs(result.map50_95 - 1.0) < 1e-6
|
||||
|
||||
|
|
@ -52,15 +51,15 @@ def test_batch_updates_perfect_detections():
|
|||
detection = Detections(
|
||||
xyxy=np.array([[10, 10, 50, 50]], dtype=np.float64),
|
||||
class_id=np.array([0]),
|
||||
confidence=np.array([0.9])
|
||||
confidence=np.array([0.9]),
|
||||
)
|
||||
|
||||
|
||||
metric = MeanAveragePrecision()
|
||||
# Add 3 batch updates
|
||||
metric.update([detection], [detection])
|
||||
metric.update([detection], [detection])
|
||||
metric.update([detection], [detection])
|
||||
result = metric.compute()
|
||||
|
||||
|
||||
# Should be perfect 1.0 mAP across all batches
|
||||
assert abs(result.map50_95 - 1.0) < 1e-6
|
||||
assert abs(result.map50_95 - 1.0) < 1e-6
|
||||
|
|
|
|||
Loading…
Reference in New Issue