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supervision
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This commit is contained in:
SkalskiP 2023-08-06 13:24:51 +02:00
parent e0ca4ca5e7
commit 3a31ea2986
2 changed files with 7 additions and 13 deletions
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16
supervision/metrics/detection.py
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@ -23,12 +23,6 @@ def detections_to_tensor(
Returns:
(np.ndarray): Detections as numpy tensors as in (xyxy, class_id, confidence) order
"""
if len(detections) == 0:
if with_confidence:
return np.zeros((0, 6))
else:
return np.zeros((0, 5))
if detections.class_id is None:
raise ValueError(
"ConfusionMatrix can only be calculated for Detections with class_id"
@ -46,7 +40,7 @@ def detections_to_tensor(
return np.concatenate(arrays_to_concat, axis=1)
def _validate_input_tensors(predictions: List[np.ndarray], targets: List[np.ndarray]):
def validate_input_tensors(predictions: List[np.ndarray], targets: List[np.ndarray]):
"""
Checks for shape consistency of input tensors.
"""
@ -221,7 +215,7 @@ class ConfusionMatrix:
])
```
"""
_validate_input_tensors(predictions, targets)
validate_input_tensors(predictions, targets)
num_classes = len(classes)
matrix = np.zeros((num_classes + 1, num_classes + 1))
@ -521,7 +515,7 @@ class MeanAveragePrecision:
>>> mean_average_precison.map
0.2899
```
```
"""
prediction_tensors = []
target_tensors = []
@ -635,7 +629,7 @@ class MeanAveragePrecision:
0.2899
```
"""
_validate_input_tensors(predictions, targets)
validate_input_tensors(predictions, targets)
map, map50, map75 = 0, 0, 0
class_index = 4
@ -730,7 +724,7 @@ class MeanAveragePrecision:
recall (np.ndarray): The recall curve
precision (np.ndarray): The precision curve
Returns:
(np.ndarray) Average precision, precision curve, recall curve
(np.ndarray): Average precision, precision curve, recall curve
"""
mrec = np.concatenate(([0.0], recall, [1.0]))
mpre = np.concatenate(([1.0], precision, [0.0]))

4
test/metrics/test_detection.py
View File

@ -5,7 +5,7 @@ import numpy as np
import pytest
from supervision.detection.core import Detections
from supervision.metrics.detection import ConfusionMatrix
from supervision.metrics.detection import ConfusionMatrix, detections_to_tensor
from test.utils import mock_detections
CLASSES = np.arange(80)
@ -167,7 +167,7 @@ def test_detections_to_tensor(
exception: Exception
):
with exception:
result = ConfusionMatrix.detections_to_tensor(
result = detections_to_tensor(
detections=detections,
with_confidence=with_confidence
)