ultralytics 8.2.74 add fuse_score=True BoT-SORT and ByteTrack arg (#14965)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Laughing 2024-08-06 17:29:40 +08:00 committed by GitHub
parent 8771f923c0
commit 9f59331854
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6 changed files with 8 additions and 9 deletions

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@ -14,6 +14,7 @@
49699333+dependabot[bot]@users.noreply.github.com: dependabot
52826299+Chayanonjackal@users.noreply.github.com: Chayanonjackal
53246858+hasanghaffari93@users.noreply.github.com: hasanghaffari93
60036186+mfloto@users.noreply.github.com: mfloto
61612323+Laughing-q@users.noreply.github.com: Laughing-q
62214284+Burhan-Q@users.noreply.github.com: Burhan-Q
68285002+Kayzwer@users.noreply.github.com: Kayzwer

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@ -1,6 +1,6 @@
# Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = "8.2.73"
__version__ = "8.2.74"
import os

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@ -7,8 +7,8 @@ track_low_thresh: 0.1 # threshold for the second association
new_track_thresh: 0.6 # threshold for init new track if the detection does not match any tracks
track_buffer: 30 # buffer to calculate the time when to remove tracks
match_thresh: 0.8 # threshold for matching tracks
fuse_score: True # Whether to fuse confidence scores with the iou distances before matching
# min_box_area: 10 # threshold for min box areas(for tracker evaluation, not used for now)
# mot20: False # for tracker evaluation(not used for now)
# BoT-SORT settings
gmc_method: sparseOptFlow # method of global motion compensation

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@ -7,5 +7,5 @@ track_low_thresh: 0.1 # threshold for the second association
new_track_thresh: 0.6 # threshold for init new track if the detection does not match any tracks
track_buffer: 30 # buffer to calculate the time when to remove tracks
match_thresh: 0.8 # threshold for matching tracks
fuse_score: True # Whether to fuse confidence scores with the iou distances before matching
# min_box_area: 10 # threshold for min box areas(for tracker evaluation, not used for now)
# mot20: False # for tracker evaluation(not used for now)

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@ -179,9 +179,8 @@ class BOTSORT(BYTETracker):
dists = matching.iou_distance(tracks, detections)
dists_mask = dists > self.proximity_thresh
# TODO: mot20
# if not self.args.mot20:
dists = matching.fuse_score(dists, detections)
if self.args.fuse_score:
dists = matching.fuse_score(dists, detections)
if self.args.with_reid and self.encoder is not None:
emb_dists = matching.embedding_distance(tracks, detections) / 2.0

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@ -375,9 +375,8 @@ class BYTETracker:
def get_dists(self, tracks, detections):
"""Calculates the distance between tracks and detections using IoU and fuses scores."""
dists = matching.iou_distance(tracks, detections)
# TODO: mot20
# if not self.args.mot20:
dists = matching.fuse_score(dists, detections)
if self.args.fuse_score:
dists = matching.fuse_score(dists, detections)
return dists
def multi_predict(self, tracks):