yolov5 VS mmdetection

Compare yolov5 vs mmdetection and see what are their differences.

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yolov5 mmdetection
128 23
46,026 27,433
2.8% 1.9%
8.9 8.7
7 days ago 8 days ago
Python Python
GNU Affero General Public License v3.0 Apache License 2.0
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.

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.
  • Changing labels of default YOLOv5 model
    2 projects | /r/learnmachinelearning | 12 Jul 2023
    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?
  • SS: Events triggered no matter the detection zone specified
    2 projects | /r/synology | 3 May 2023
    What I did is hand off my detections to an Nvidia GPU running Yolov5 https://github.com/ultralytics/yolov5 which does the triggering if it's an object class I'm interested in. Since Synology is always caching at least 5 seconds of camera video the 50-100mS delay of grabbing a frame and analyzing before triggering recording is fine. Wish they'd implement something like this.
  • AMD ROCm 5.5 In The Process Of Being Released
    4 projects | /r/Amd | 2 May 2023
    this is about all I could find, maybe you've been getting different degrees of optimized python libs that do the image resizes. https://github.com/ultralytics/yolov5/issues/11469
  • good computer vision or deep learning projects in github
    9 projects | /r/deeplearning | 22 Apr 2023
    YOLOv5 (GitHub: https://github.com/ultralytics/yolov5) is a fast, accurate object detection model with code for training, testing, deployment, and pre-trained weights.
  • [D] Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model
    4 projects | /r/MachineLearning | 18 Apr 2023
    Those dimensions suggest you need to apply (i.e. roll your own) non-max suppresion to the outputs: relevant link
  • Thought Dump About Recent AI Advancements And Palantir
    2 projects | /r/PLTR | 29 Mar 2023
    - YOLOv5 https://github.com/ultralytics/yolov5 (open source, so not Palantir's)
  • How to build computer vision dataset labeling team in-house
    4 projects | dev.to | 28 Mar 2023
    A team of annotators and the infrastructure described in this article I needed to label my dataset, which was collected from cameras on the road (30k+ photos). This dataset was necessary to train an object detection model on six classes: [person, car, bus, bicycle, motorcycle, truck]. I released the dataset, created in this manner, as open source, and it can be downloaded here (link) together with trained YOLOv5s and YOLOv5x models from a popular repository (link) using this dataset. The license is simple: "Use it well"!
  • Flutter Object Detection App + YOLOV5 Model.
    3 projects | dev.to | 15 Feb 2023
    Before you can use YOLOv5 in your Flutter application, you'll need to train the model on your specific dataset. You can use an existing dataset or create your own dataset to train the model. For this post I am using the pretrained model of yolov5 available on https://github.com/ultralytics/yolov5 as we are performing object detection we need to converts the pretrained model weights to torchscript format.
  • NotImplementedError (YOLOv5)
    3 projects | /r/pytorch | 12 Feb 2023
    Thank you Link to the codefor taking the time to reply. I have modified the code as you suggested. And now I see the GPU being utilized. But the precision, recall, mAP is all zero. At least it displays as zero.
  • NVIDIA Jetson AGX Orin is now compatible with balena
    4 projects | dev.to | 9 Feb 2023
    Read more here about how Theia Scientific is currently using the newest NVIDIA Jetson AGX Orin on their fleet of microscopes. Theia Scientific and Volkov Labs, improved the Jetson AGX Orin inference speeds up to 30FPS. The Jetson AGX Orin running YOLOv5 tripled the Frames-per-Second (FPS) compared with the latest Jetson AGX Xavier.

mmdetection

Posts with mentions or reviews of mmdetection. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-12.
  • Semantic segementation
    2 projects | /r/computervision | 12 Apr 2023
    When I look for benchmarks I always start here https://paperswithcode.com/task/instance-segmentation/codeless it has the lists of datasets to measure models accross lots o papers. Many are very specific models with low support or community but it gives you a good idea of ​​the state of the art. It also lists repositories related to good community. https://github.com/open-mmlab/mmdetection seems very active and the one that is being used the most, you could use the models that it has integrated in its model zoo, within the same repository. It has the benchmarks to compare those same models and some of them are from 2022
  • [P] Image search with localization and open-vocabulary reranking.
    8 projects | /r/MachineLearning | 15 Dec 2022
    I wanted to have a few choices getting localization into image search (index and search time). I immediately thought of using a region proposal network (rpn) from mask-rcnn to create patches that can also be indexed and searched (and add the localisation). I figured it might be somewhat agnostic to classes. I did not want to use mmdetection or detectron2 due to their dependencies and just getting the rpn was not worth it. I was encouraged by the PyTorch native implementations of detection/segmentation models but ended up finding yolox the best.
  • MMDeploy: Deploy All the Algorithms of OpenMMLab
    22 projects | /r/u_Allent_pjlab | 21 Nov 2022
    MMDetection: OpenMMLab detection toolbox and benchmark.
  • Removing the bounding box generated by OnnxRuntime segmentation
    2 projects | /r/computervision | 4 Nov 2022
    I have a semantic segmentation model trained using the mmdetection repo. Then it is converted to the ONNX format using the mmdeploy repo.
  • Keras vs Tensorflow vs Pytorch for a Final year Project
    2 projects | /r/tensorflow | 10 Oct 2022
    E.g. If you consider it an object detection problem it is: detect and localise all the pedestrians in a frame, and classify them by their (intended) action. IMO the easiest way to do this would be with mmdetection, which is built on top of pytorch. Just label your dataset, build a config, and boom you have a model. Inference with that model in only a few lines of code, you won't really need to learn too much to get started.
  • DeepSort with PyTorch(support yolo series)
    13 projects | /r/u_No_Experience9104 | 20 Sep 2022
    MMDetection
  • Config files in plain Python
    3 projects | /r/Python | 25 Aug 2022
    MMDetection uses config Python scripting. It's easier to define nn.Module objects other than writing class name in a json config file
  • I trained a neural net to watch Super Smash Bros
    3 projects | /r/computervision | 25 Jul 2022
    I used the PointRend implementation from the mmdet project https://github.com/open-mmlab/mmdetection
  • bike classification advice sought for used bike aggregator
    3 projects | /r/computervision | 30 Mar 2022
  • I want to create a pill counter using points instead of bounding boxes. What model should I train from?
    7 projects | /r/learnmachinelearning | 1 Jan 2022
    If you are really that lazy: use bboxes of the fixed size placed in the center of the pill. The pill does not have to fit into the box - modern architectures see the image as a whole, not only the crop in the box. For example if you would train detection on labels which are shifted (add 30px to each label coordinate), the network would learn to place each box 30px next to the actual object. So just let small box represent the center of the pill. The problem will arise if you will use improperly configured architecture, i.e. if you will not change the anchors in SSD model. Try efficientdet architecture implemented in mmdetection or, the easiest, yolov5. These should work out of the box.

What are some alternatives?

When comparing yolov5 and mmdetection you can also consider the following projects:

detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.

yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)

OpenCV - Open Source Computer Vision Library

yolov5-crowdhuman - Head and Person detection using yolov5. Detection from crowd.

pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]

CenterNet - Object detection, 3D detection, and pose estimation using center point detection:

yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite

edge-tpu-tiny-yolo - Run Tiny YOLO-v3 on Google's Edge TPU USB Accelerator.

YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.