Comments (1)
Hi,
I am glad that you like my repo!
I wish to merge the yolov5 bounding box with the pedestrian bounding box from deepsort
DeepSort depends on the detections made by Yolov5 for making predictions, so what you ask for makes little sense.
However, what you could do is to train Yolov5 on persons and head gear and then use Bayes' theorem to get a probability estimation of a person wearing head gear
from yolo_tracking.
Related Issues (20)
- In the boxmot project, the detection results of yolov8 are incorrect. HOT 1
- DEBUG level logs gets disabled after importing boxmot HOT 1
- 'StrongSORT' object has no attribute 'reset' HOT 2
- Questions about the ReID model in BoTSORT HOT 9
- Add SAHI techniques to detect small object for tracking task. HOT 3
- NotImplementedError HOT 1
- Is There BoxMOT package in C++ version? HOT 2
- HybridSORT fails due to Numpy Version HOT 9
- Can't create val_utils/scripts/run_mot_challenge.py HOT 1
- "--source streams.txt" cannot work HOT 1
- ID Changes with box intersection and objects going out of frame HOT 1
- can not download deepocsort's model HOT 1
- Inquiry on Replicating Experiments in Enhanced Tracking and ReID through Segmentation HOT 5
- It seems that there are several issues after updating the ultralytics version. Could you please fix the version in the requirements file so that we can easily run the yolo_tracking? HOT 2
- Predict the appearance area of an object after being obscured HOT 1
- HybridSORT errors after Numpy fix HOT 4
- Support for SMILETrack? HOT 1
- Tracker predicts the same ID more than once in a single timestep HOT 1
- mot17_sbs_S50.pt HOT 5
- Model complexity HOT 2
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from yolo_tracking.