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 ). (by xuarehere)
yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite (by ultralytics)
| yolo_series_deepsort_pytorch | yolov5 | |
|---|---|---|
| 1 | 129 | |
| 93 | 47,071 | |
| - | 1.8% | |
| 0.0 | 8.8 | |
| about 1 year ago | 5 days ago | |
| Python | Python | |
| MIT License | GNU Affero General Public License v3.0 |
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.
yolo_series_deepsort_pytorch
Posts with mentions or reviews of yolo_series_deepsort_pytorch.
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)
git clone https://github.com/xuarehere/yolovx_deepsort_pytorch.git
yolov5
Posts with mentions or reviews of yolov5.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-12.
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จำแนกสายพันธ์ุหมากับแมวง่ายๆด้วยYoLoV5
Ref https://www.youtube.com/watch?v=0GwnxFNfZhM https://github.com/ultralytics/yolov5 https://dev.to/gfstealer666/kaaraich-yolo-alkrithuemainkaartrwcchcchabwatthu-object-detection-3lef https://www.kaggle.com/datasets/devdgohil/the-oxfordiiit-pet-dataset/data
- How would i go about having YOLO v5 return me a list from left to right of all detected objects in an image?
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Building a Drowsiness Detection Web App from scratch - pt2
!git clone https://github.com/ultralytics/yolov5.git ## Navigate to the model %cd yolov5/ ## Install requirements !pip install -r requirements.txt ## Download the YOLOv5 model !wget https://github.com/ultralytics/yolov5/releases/download/v6.0/yolov5s.pt
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[Help: Project] Transfer Learning on YOLOv8
Specifically what I did was take the coco128.yaml, added 6 new classes from Dataset A (which have already been converted to YOLO Darknet TXT), from index 0-5 and subsequently adjusted the indices of the other COCO classes. The I proceeded to train and validate on Dataset A for 20 epochs.
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Changing labels of default YOLOv5 model
I am using the default YOLOv5m6 model here with sahi/yolov5 library for my object detection project. I want to change just some of labels - for example when YOLO detects a human, I want it to label the human as "threat", not "person". Is there any way I can do it just changing some code, or I should train the model from scratch by just changing labels?
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First time working with computer vision, need help figuring out a problem in my model
You should add them without annotations. Go through this.
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AI Camera?
You are correct and if you check the firmware, it's yet another famous 3rd party project without attribution, namely https://github.com/ultralytics/yolov5
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First non-default print on K1 - success
On one side, being a Linux user for 24 years now, it annoys me that they rip off code and claiming it as theirs again, thus violating licenses, but on the other thanks to k3d's exploit I'm able to tinker more with the machine and if needed do (selective) updates by hand then with a closed source system. It's not just "klipper", with klipper, fluidd and moonraker, it's also ffmpeg and mjpegstreamer. It's gonna be interesting since they also use a project that isn't just GPL, but APGL (in short "If your software gives service online, you have to publish the source code of it and any library that it borrows functions from.") - they use yolov5 (for AI).
- How does the background class work in object detection?
What are some alternatives?
When comparing yolo_series_deepsort_pytorch and yolov5 you can also consider the following projects:
deep_sort - Simple Online Realtime Tracking with a Deep Association Metric
mmdetection - OpenMMLab Detection Toolbox and Benchmark
PPYOLOE_pytorch - An unofficial implementation of Pytorch version PP-YOLOE,based on Megvii YOLOX training code.
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
hcaptcha-challenger - 🥂 Gracefully face hCaptcha challenge with MoE(ONNX) embedded solution.
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
segment-anything-video - MetaSeg: Packaged version of the Segment Anything repository
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
ScaledYOLOv4 - Scaled-YOLOv4: Scaling Cross Stage Partial Network
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
deep_sort_realtime - A really more real-time adaptation of deep sort
OpenCV - Open Source Computer Vision Library
yolo_series_deepsort_pytorch vs deep_sort
yolov5 vs mmdetection
yolo_series_deepsort_pytorch vs PPYOLOE_pytorch
yolov5 vs detectron2
yolo_series_deepsort_pytorch vs hcaptcha-challenger
yolov5 vs darknet
yolo_series_deepsort_pytorch vs segment-anything-video
yolov5 vs Deep-SORT-YOLOv4
yolo_series_deepsort_pytorch vs ScaledYOLOv4
yolov5 vs yolor
yolo_series_deepsort_pytorch vs deep_sort_realtime
yolov5 vs OpenCV