Comments (1)
To use SORT out-of-the-box in a realtime application you will need a realtime detector. Maybe something like SqueezeDet.
SORT only has a simple prediction component based on a linear Kalman filter. You will need to change this to suit your problem. I would suggest using some optical flow based or a per instance based tracker that uses both appearance and inter-frame motion like HART.
If you don't need realtime and can wait for you next detection you could use SORT on every 30th frame. If the displacement is large (due to low framerate), then consider DeepSORT which used appearance features for better association, but (for now) daily only works on pedestrians.
Closing as this is not an issue.
from sort.
Related Issues (20)
- from sort import * causes dead Kenel HOT 1
- running SORT on custom dataset
- missing intermediate IDs HOT 2
- Using SORT when the number of elements to track is constant and known - ideas to recover missidentification and missmatches HOT 6
- C-Python implementation of SORT
- Multi-class multi-object tracking HOT 3
- error in iou__batches HOT 7
- Tracking other objects HOT 2
- Why are FP and FN different for each Tracker method in the paper?
- Preparing RLE for MOTS20 evaluation
- SORT ID for new detection between other old detections
- Logic Error? trk.hit_streak >=self.min_hits, ret.append(...)
- multiclass tracking HOT 3
- can I use this for windows ? because it still show me the same error ?
- No issue, just here for `lap` -> `lapx`
- instalation error
- How to get next state KalmanFilter
- ValueError: operands could not be broadcast together with shapes (0,) (1,3) HOT 1
- Python Version support for SORT
- Converting into Grayscale increasing the inference time ? Is there any way we can increase the model inference time ? HOT 1
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from sort.