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Fixed creation of structured array

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Signed-off-by: Jim Martens <github@2martens.de>
This commit is contained in:
Jim Martens
2019-08-29 15:00:00 +02:00
parent 9b3d9a550b
commit 343d7e9bea
1 changed files with 3 additions and 2 deletions
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5
src/twomartens/masterthesis/ssd.py
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@ -429,7 +429,7 @@ def _apply_entropy_threshold(observations: Sequence[np.ndarray], entropy_thresho
def _apply_top_k(detections: Sequence[np.ndarray], top_k: float) -> List[np.ndarray]:
final_detections = []
batch_size = len(detections)
data_type = np.dtype([('image_id', np.int32),
data_type = np.dtype([('class_id', np.int32),
('confidence', 'f4'),
('entropy', 'f4'),
('xmin', 'f4'),
@ -438,7 +438,8 @@ def _apply_top_k(detections: Sequence[np.ndarray], top_k: float) -> List[np.ndar
('ymax', 'f4')])
for i in range(batch_size):
image_detections = detections[i]
image_detections_structured = np.array(image_detections, dtype=data_type)
image_detections_structured = np.core.records.fromarrays(image_detections.transpose(),
dtype=data_type)
descending_indices = np.argsort(-image_detections_structured['confidence'])
image_detections_sorted = np.asarray(image_detections_structured[descending_indices])
top_k_indices = np.argpartition(image_detections_sorted[:, 1],