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Yolor Alternatives
Similar projects and alternatives to yolor
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Judoscale
Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
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darknet
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet ) (by AlexeyAB)
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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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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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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
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tensorflow-yolov4-tflite
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.3.1, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite (by haroonshakeel)
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PPYOLOE_pytorch
An unofficial implementation of Pytorch version PP-YOLOE,based on Megvii YOLOX training code.
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yolo_series_deepsort_pytorch
Deepsort with yolo series. This project support the existing yolo detection model algorithm (YOLOV8, YOLOV7, YOLOV6, YOLOV5, YOLOV4Scaled, YOLOV4, YOLOv3', PPYOLOE, YOLOR, YOLOX ).
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InfluxDB
InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better yolor alternative or higher similarity.
yolor discussion
yolor reviews and mentions
Posts with mentions or reviews of yolor.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-20.
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Explicit and Implicit Knowledge in Object Detection (YOLOR, YOLOv7)
Fellow redditors, can you please explain to me how aforementioned structures work and applied in code? I tried to read carefully the papers on YOLOv7 and YOLOR (https://arxiv.org/pdf/2207.02696.pdf, https://arxiv.org/pdf/2105.04206.pdf) but for me it feels like explanations in text have literally no relation to implementation code (I am totally not into Torch so it makes understanding even harder) (https://github.com/WongKinYiu/yolor/blob/main/utils/layers.py)
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DeepSort with PyTorch(support yolo series)
WongKinYiu/yolor
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Build Custom Functions for YOLOv4 with TensorFlow, TFLite & TensorRT
Is there a reason to use YOLOv4 over YOLOv5 or YOLOR?
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Docker for Absolute Beginners.
I am interested in using Docker for Deep learning models use. On Github people recommend Docker environment to use the model. I am sharing the link to the Github repo. My question is how I can use this GitHub repo and create a docker container
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[Project]Vehicle Counting + Speed Calculation using YOLOR+ DeepSORT OpenCV Python
So there is a paper on YOLOR by Wong Kin Yiu https://github.com/WongKinYiu/yolor
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YOLOR (Scaled-YOLOv4-based): The best speed/accuracy ratio for Waymo autonomous driving challenge
[CVPR'21 WAD] Challenge - Waymo Open Dataset: https://waymo.com/open/challenges/2021/real-time-2d-prediction/ YOLOR (Scaled-YOLOv4-based) has the best speed/accuracy ratio on Waymo autonomous driving challenge ((Waymo Open Dataset): Real-time 2D Detection. Thanks Chien-Yao Wang from Academia Sinica and DiDi MapVision team to push Scaled-YOLOv4 further! * DIDI MapVision: https://arxiv.org/abs/2106.08713 * YOLOR https://arxiv.org/abs/2105.04206 * YOLOR-code (Pytorch): https://github.com/WongKinYiu/yolor * Scaled-YOLOv4(CVPR21): https://openaccess.thecvf.com/content/CVPR2021/html/Wang\_Scaled-YOLOv4\_Scaling\_Cross\_Stage\_Partial\_Network\_CVPR\_2021\_paper.html * Scaled-YOLOv4-code (Pytorch): https://github.com/WongKinYiu/ScaledYOLOv4 * YOLOv4: https://arxiv.org/abs/2004.10934 * YOLOv4-code (Darknet, Pytorch, TensorFlow, TRT, OpenCV…): https://github.com/AlexeyAB/darknet#yolo-v4-in-other-frameworks
The DiDi MapVision team has shown excellent results with the YOLOR and DIDI MapVision models, both based on Scaled-YOLOv4: * DIDI MapVision: https://arxiv.org/abs/2106.08713 * YOLOR https://arxiv.org/abs/2105.04206 * YOLOR-code (Pytorch): https://github.com/WongKinYiu/yolor * Scaled-YOLOv4(CVPR21): https://openaccess.thecvf.com/content/CVPR2021/html/Wang_Scaled-YOLOv4_Scaling_Cross_Stage_Partial_Network_CVPR_2021_paper.html * Scaled-YOLOv4-code (Pytorch): https://github.com/WongKinYiu/ScaledYOLOv4 * YOLOv4: https://arxiv.org/abs/2004.10934 * YOLOv4-code (Darknet, Pytorch, TensorFlow, TRT, OpenCV...): https://github.com/AlexeyAB/darknet#yolo-v4-in-other-frameworks
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[P] YOLOR (Scaled-YOLOv4-based): The best speed/accuracy ratio for Waymo autonomous driving challenge
* YOLOR-code (Pytorch): https://github.com/WongKinYiu/yolor
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A note from our sponsor - Judoscale
judoscale.com | 27 Apr 2025
Stats
Basic yolor repo stats
8
2,000
2.5
6 months ago
WongKinYiu/yolor is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.
yolor is marked as "self-hosted". This means that it can be used as a standalone application on its own.
The primary programming language of yolor is Python.
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