Fast-reid Alternatives
Similar projects and alternatives to fast-reid
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FastMOT
High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
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DOLG-pytorch
Unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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pytorch-metric-learning
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
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pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
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l2rpn-baselines
L2RPN Baselines a repository to host baselines for l2rpn competitions.
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YOLOv6
YOLOv6: a single-stage object detection framework dedicated to industrial applications.
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
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yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
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yolor
implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
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PPYOLOE_pytorch
An unofficial implementation of Pytorch version PP-YOLOE,based on Megvii YOLOX training code.
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yolovx_deepsort_pytorch
Deepsort with yolo series. This project support the existing yolo detection model algorithm (YOLOv3, YOLOV4, YOLOV4Scaled, YOLOV5, YOLOV6, YOLOV7, YOLOX, YOLOR, PPYOLOE ).
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
fast-reid reviews and mentions
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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)
Stats
JDAI-CV/fast-reid is an open source project licensed under Apache License 2.0 which is an OSI approved license.