fast-reid
deep_sort_pytorch
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fast-reid | deep_sort_pytorch | |
---|---|---|
3 | 1 | |
3,252 | 2,688 | |
1.7% | - | |
1.2 | 0.0 | |
4 months ago | 6 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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fast-reid
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DeepSort with PyTorch(support yolo series)
fast-reid
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Assign ID and track moving object with optical flow
On failure, you can try using a re-identification methods like FastReid: https://github.com/JDAI-CV/fast-reid in combination with your detector. A good pipeline that combines everything you seem to need is here: https://github.com/GeekAlexis/FastMOT. It uses a combination of Yolov4 (detector) + Kalman filters, Optical flow (tracker) and FastReid (re-identification)
deep_sort_pytorch
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DeepSort with PyTorch(support yolo series)
ZQPei/deep_sort_pytorch
What are some alternatives?
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
l2rpn-baselines - L2RPN Baselines a repository to host baselines for l2rpn competitions.
pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
DOLG-pytorch - Unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Hekate-Toolbox - A toolbox for Hekate
apex-configs-by-deafps - Apex config & tweaks
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.
pymarl2 - Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
PPYOLOE_pytorch - An unofficial implementation of Pytorch version PP-YOLOE,based on Megvii YOLOX training code.