PyTorch_YOLOv4
PyTorch implementation of YOLOv4 (by WongKinYiu)
yolor
implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206) (by WongKinYiu)
| PyTorch_YOLOv4 | yolor | |
|---|---|---|
| 1 | 8 | |
| 1,850 | 1,972 | |
| - | - | |
| 0.0 | 3.6 | |
| 3 months ago | 5 months ago | |
| Python | Python | |
| - | GNU General Public License v3.0 only |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
PyTorch_YOLOv4
Posts with mentions or reviews of PyTorch_YOLOv4.
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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DeepSort with PyTorch(support yolo series)
WongKinYiu/PyTorch_YOLOv4
yolor
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
What are some alternatives?
When comparing PyTorch_YOLOv4 and yolor you can also consider the following projects:
mmdetection - OpenMMLab Detection Toolbox and Benchmark
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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 ).
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
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/
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.3.1, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
deep_sort - Simple Online Realtime Tracking with a Deep Association Metric
YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.
ScaledYOLOv4 - Scaled-YOLOv4: Scaling Cross Stage Partial Network
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
PyTorch_YOLOv4 vs mmdetection
yolor vs yolov5
PyTorch_YOLOv4 vs yolo_series_deepsort_pytorch
yolor vs darknet
PyTorch_YOLOv4 vs YOLOX
yolor vs tensorflow-yolov4-tflite
PyTorch_YOLOv4 vs deep_sort
yolor vs YOLOv6
PyTorch_YOLOv4 vs yolov5
yolor vs ScaledYOLOv4
PyTorch_YOLOv4 vs ScaledYOLOv4
yolor vs yolo-tf2