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Merge branch 'develop' of https://github.com/AntonioConsiglio/supervision into develop

This commit is contained in:
Antonio Consiglio 2023-10-07 19:15:04 +02:00
parent 30994243ae 99707582bc
commit a550aaa812
1 changed files with 13 additions and 12 deletions
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25
supervision/tracker/byte_tracker/core.py
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@ -235,8 +235,7 @@ class ByteTrack:
```
"""
tracks = self.update_with_tensors(
tensors=detections2boxes(detections=detections),
masks = detections.mask
tensors=detections2boxes(detections=detections), masks=detections.mask
)
detections = Detections.empty()
if len(tracks) > 0:
@ -252,16 +251,16 @@ class ByteTrack:
detections.confidence = np.array(
[t.score for t in tracks], dtype=np.float32
)
detections.mask = np.array(
[t.mask for t in tracks], dtype=bool
)
detections.mask = np.array([t.mask for t in tracks], dtype=bool)
else:
detections.tracker_id = np.array([], dtype=int)
return detections
def update_with_tensors(self, tensors: np.ndarray, masks:np.ndarray = None) -> List[STrack]:
def update_with_tensors(
self, tensors: np.ndarray, masks: np.ndarray = None
) -> List[STrack]:
"""
Updates the tracker with the provided tensors and returns the updated tracks.
@ -292,8 +291,8 @@ class ByteTrack:
masks_hs = masks[remain_inds]
masks_ls = masks[inds_second]
else:
masks_hs = np.array([None]*len(remain_inds))
masks_ls = np.array([None]*len(inds_second))
masks_hs = np.array([None] * len(remain_inds))
masks_ls = np.array([None] * len(inds_second))
scores_keep = scores[remain_inds]
scores_second = scores[inds_second]
@ -303,8 +302,8 @@ class ByteTrack:
if len(dets) > 0:
"""Detections"""
detections = [
STrack(STrack.tlbr_to_tlwh(tlbr), s, c,m)
for (tlbr, s, c,m) in zip(dets, scores_keep, class_ids_keep,masks_hs)
STrack(STrack.tlbr_to_tlwh(tlbr), s, c, m)
for (tlbr, s, c, m) in zip(dets, scores_keep, class_ids_keep, masks_hs)
]
else:
detections = []
@ -344,8 +343,10 @@ class ByteTrack:
if len(dets_second) > 0:
"""Detections"""
detections_second = [
STrack(STrack.tlbr_to_tlwh(tlbr), s, c,m)
for (tlbr, s, c, m) in zip(dets_second, scores_second, class_ids_second,masks_ls)
STrack(STrack.tlbr_to_tlwh(tlbr), s, c, m)
for (tlbr, s, c, m) in zip(
dets_second, scores_second, class_ids_second, masks_ls
)
]
else:
detections_second = []