mmtracking
Yolov7_StrongSORT_OSNet
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| mmtracking | Yolov7_StrongSORT_OSNet | |
|---|---|---|
| 7 | 1 | |
| 3,382 | 388 | |
| 2.5% | - | |
| 1.5 | 1.0 | |
| 7 months ago | about 2 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 only |
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.
mmtracking
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Tracking sets of Keypoints by Person
I suggest to try the top down approach with the https://openmmlab.com/ open source package. The openmmlab provides multiple algorithms, datasets and pretrained models for various computer vision tasks. Start with mmpose video demo that integrates detection and pose estimation. You can add later tracking with https://github.com/open-mmlab/mmtracking to track the poses in time.
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMTracking: OpenMMLab video perception toolbox and benchmark.
- [P]We have supported Quasi-Dense Similarity Learning for Multiple Object Tracking.
- [p]We have supported Quasi-Dense Similarity Learning for Multiple Object Tracking
- MMTracking have supported Quasi-Dense Similarity Learning for Multiple Object Tracking.
- MMTracking Supports Quasi-Dense Similarity Learning for Multiple Object Tracking
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Help combining custom detector (yolo) with a tracker.
Implementations exist, like https://github.com/open-mmlab/mmtracking
Yolov7_StrongSORT_OSNet
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Multicamera ReID
I have several cameras that stream via multiprocessing frames. With yolov7 I detect persons. Now I want to track and re-identify these persons across all streams. From the multiprocessing point of view this is no problem (shared list) but I don't know which method I can/should use. I tried something with StrongSort but there is a Kalman filter in it which would iritate the model because of wrong positions and velocities. Can someone help me? At the moment this StrongSort algorithm from Github works great. But the ReID does not take place logically there across streams.
What are some alternatives?
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
Object_Detection_Tracking - Out-of-the-box code and models for CMU's object detection and tracking system for multi-camera surveillance videos. Speed optimized Faster-RCNN model. Tensorflow based. Also supports EfficientDet. WACVW'20
PaddleDetection - Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
mmyolo - OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.
UniTrack - [NeurIPS'21] Unified tracking framework with a single appearance model. It supports Single Object Tracking (SOT), Video Object Segmentation (VOS), Multi-Object Tracking (MOT), Multi-Object Tracking and Segmentation (MOTS), Pose Tracking, Video Instance Segmentation (VIS), and class-agnostic MOT (e.g. TAO dataset).
mmflow - OpenMMLab optical flow toolbox and benchmark
pytracking - Email open and click tracking library