multi-object-tracker
norfair
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| multi-object-tracker | norfair | |
|---|---|---|
| 4 | 4 | |
| 666 | 2,289 | |
| - | 1.9% | |
| 6.4 | 7.2 | |
| 7 months ago | 15 days ago | |
| Python | Python | |
| MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
multi-object-tracker
- Multi-object trackers in Python
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Difference DeepSort and doing detection on each frame
You may find this useful: https://adipandas.github.io/multi-object-tracker/
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SORT Tracker adds extra objects
As you can see, in Frame 43, the tracker assigns the ID 10 to a metal post, but a few frames later when the tracker tracks the same metal post, it provides an ID of 11. This shows that the tracker is assigning new IDs to the same detected object. I cannot seem to find out why this happens, and how to fix it. I am using the motrackers module from this repo. I have not made any changes as such in the mot_yolov3.py file, I have just added the line to print the frame counter.
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Example Of A Simple And Well Made Python Project
I have a simple python project which has gone through at least 5 iterations since I began working on it. Please see this link: adipandas/multi-object-tracker.
norfair
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Seeking Efficient Video Object Tracking and or Video Segmentation Software for Research
If you're familiar with Python you can try using Norfair. It's a lightweight Python library for adding real-time multi-object tracking to any detector. There are lots of examples for you to try, they mostly differ on the object detector.
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Help combining custom detector (yolo) with a tracker.
Yyou can use norfair: https://github.com/tryolabs/norfair
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Empresa uruguaya que SI recomendarías
Tryolabs
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Tracker on top of YOLO algorithm?
Depending on your task normal SORT would work as well (No retraining required, just some Kallman filter and some other techniques). The library https://github.com/tryolabs/norfair has implemented SORT and can be extended with DeepSORT if you want.
What are some alternatives?
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
zero-shot-object-tracking - Object tracking implemented with the Roboflow Inference API, DeepSort, and OpenAI CLIP.
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.
Kornia - Geometric Computer Vision Library for Spatial AI
kalmanpy - Implementation of Kalman Filter in Python
Face Recognition - The world's simplest facial recognition api for Python and the command line
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.