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ultralytics 8.0.49 task, exports and metadata updates (#1197)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Mehran Ghandehari <mehran.maps@gmail.com>
Co-authored-by: Paul Guerrie <97041392+paulguerrie@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
2023-03-01 21:16:09 -08:00
committed by GitHub
parent 74e4c94806
commit 3861e6c82a
20 changed files with 111 additions and 101 deletions
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28
ultralytics/tracker/trackers/bot_sort.py
View File

@ -65,17 +65,18 @@ class BOTrack(STrack):
@staticmethod
def multi_predict(stracks):
if len(stracks) > 0:
multi_mean = np.asarray([st.mean.copy() for st in stracks])
multi_covariance = np.asarray([st.covariance for st in stracks])
for i, st in enumerate(stracks):
if st.state != TrackState.Tracked:
multi_mean[i][6] = 0
multi_mean[i][7] = 0
multi_mean, multi_covariance = BOTrack.shared_kalman.multi_predict(multi_mean, multi_covariance)
for i, (mean, cov) in enumerate(zip(multi_mean, multi_covariance)):
stracks[i].mean = mean
stracks[i].covariance = cov
if len(stracks) <= 0:
return
multi_mean = np.asarray([st.mean.copy() for st in stracks])
multi_covariance = np.asarray([st.covariance for st in stracks])
for i, st in enumerate(stracks):
if st.state != TrackState.Tracked:
multi_mean[i][6] = 0
multi_mean[i][7] = 0
multi_mean, multi_covariance = BOTrack.shared_kalman.multi_predict(multi_mean, multi_covariance)
for i, (mean, cov) in enumerate(zip(multi_mean, multi_covariance)):
stracks[i].mean = mean
stracks[i].covariance = cov
def convert_coords(self, tlwh):
return self.tlwh_to_xywh(tlwh)
@ -112,10 +113,9 @@ class BOTSORT(BYTETracker):
return []
if self.args.with_reid and self.encoder is not None:
features_keep = self.encoder.inference(img, dets)
detections = [BOTrack(xyxy, s, c, f) for (xyxy, s, c, f) in zip(dets, scores, cls, features_keep)]
return [BOTrack(xyxy, s, c, f) for (xyxy, s, c, f) in zip(dets, scores, cls, features_keep)] # detections
else:
detections = [BOTrack(xyxy, s, c) for (xyxy, s, c) in zip(dets, scores, cls)]
return detections
return [BOTrack(xyxy, s, c) for (xyxy, s, c) in zip(dets, scores, cls)] # detections
def get_dists(self, tracks, detections):
dists = matching.iou_distance(tracks, detections)

1
ultralytics/tracker/trackers/byte_tracker.py
View File

@ -92,7 +92,6 @@ class STrack(BaseTrack):
Update a matched track
:type new_track: STrack
:type frame_id: int
:type update_feature: bool
:return:
"""
self.frame_id = frame_id