rleinstancesegmentationprediction Kind
Prediction with detected bounding boxes and RLE-encoded segmentation masks in form of sv.Detections(...) object.
sv.Detections(
xyxy=array([[ 127, 189, 322, 303]]),
mask=None, # Initially None, populated lazily when needed
confidence=array([ 0.95898]),
class_id=array([6]),
tracker_id=None,
data={
'class_name': array(['person'], dtype='<U6'),
'detection_id': array(['51dfa8d5-261c-4dcb-ab30-9aafe9b52379'], dtype='<U36'),
'parent_id': array(['image.[0]'], dtype='<U9'),
'image_dimensions': array([[425, 640]]),
'prediction_type': array(['rle-instance-segmentation'], dtype='<U26'),
'rle_masks': array([{'size': [425, 640], 'counts': 'encoded_rle_string'}], dtype=object),
# ... other standard fields
}
)Data representation
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Internal
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