ByteTrack
zero-shot-object-tracking
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| ByteTrack | zero-shot-object-tracking | |
|---|---|---|
| 6 | 10 | |
| 4,230 | 350 | |
| - | 1.4% | |
| 0.0 | 0.6 | |
| 16 days ago | 15 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
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ByteTrack
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Multi Object Tracking from moving camera
Thanks for the suggestion! Unfortunately, unitrack code doesn't support custom data evaluation. I've found Bytetrack to be useful for my current task.
- Object tracking in videos?
- ByteTrack: Multi-Object Tracking by Associating Every Detection Box
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ByteDance Proposes An Impressive Multi-Object Tracking Architecture
Code for https://arxiv.org/abs/2110.06864 found: https://github.com/ifzhang/ByteTrack
Quick 5 Min Read | Paper | Github
- [R] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
zero-shot-object-tracking
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How to Track Flying Objects?
I’ve seen a bunch of drone-detection computer vision projects. Usually they’re detecting dromes from other drones though (Eg for autonomous racing[1] or drone-defense).
A challenge with doing it from the ground is that the drones will be quite small relative to the size of the image. With sufficient compute and several cameras a tiling-based approach[2] should work!
If you want to do unique-identification you’ll also need object tracking[3].
This is exactly the type of project Roboflow (our startup) is built to empower! Happy to chat/help further (Eg we might be able to help source a good dataset to start from). And if it’s for non-commercial use it should be completely free.
[1] https://blog.roboflow.com/drone-computer-vision-autopilot/
[2] https://blog.roboflow.com/detect-small-objects/
[3] https://blog.roboflow.com/zero-shot-object-tracking/
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Object tracking in videos?
We use CLIP for object tracking with pretty good results (with no second model train required). https://blog.roboflow.com/zero-shot-object-tracking/
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Hacker News top posts: Aug 28, 2021
Zero Shot Object Tracking\ (4 comments)
- Need help in camera selection
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Zero Shot Object Tracking
It uses an object detection model (in our example code[1], we used one from Roboflow Universe[2] but you should be able to use any object detection model) and then sends a crop of each detected box to CLIP to get the feature vector that Deep SORT uses to differentiate between and track instances across frames.
[1] https://github.com/roboflow-ai/zero-shot-object-tracking
[2] https://universe.roboflow.com
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[P] Zero-Shot Object Tracking with CLIP and Deep SORT
Repo: https://github.com/roboflow-ai/zero-shot-object-tracking
- Zero-Shot Object Tracking with CLIP and Deep SORT
- Show HN: Zero-Shot Object Tracking
What are some alternatives?
multi-object-tracker - Multi-object trackers in Python
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
FairMOT - [IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
classy-sort-yolov5 - Ready-to-use realtime multi-object tracker that works for any object category. YOLOv5 + SORT implementation.
ssd_keras - A Keras port of Single Shot MultiBox Detector
mmtracking - OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x