Difference from SORT

[sevvalmehder]

I have had chance to deeply study this project and the original deep sort project. And I review SORT and deep sort paper. Main difference between SORT and deep SORT is deep sort uses deep features of detected objects. Main deep sort repository has a features of MOT dataset as a npc file. And it loads this features. But when we do that in real time we need a deep network for feature extractor. As far as I review this project, there is no operation for feature extract. I just saw only this line for this operation:
feature = [1] self.feature = np.asarray(feature, dtype=np.float32) in here:

TensorflowDeepSortTracking/ObjectTracking/deep_sort/detection.py

Line 38 in c538fcd

self.feature = np.asarray(feature, dtype=np.float32)

Am i miss something?

[JoyJulianGomes]

When using the MOT dataset features are already calculated. In case of new/live videos features needs to be calculated in run time. There is not much information about this in this repository and i would suggest you to checkout https://github.com/Qidian213/deep_sort_yolov3. Specifically the
the create_box_encoder from tools/generate_detections.py
Hope this helps :)

[sevvalmehder]

After i realized this situation, i am trying to the do real time feature calculation inside this project. Thanks for referring this project. I will check.