mmdetection VS sahi

Compare mmdetection vs sahi and see what are their differences.

Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
mmdetection sahi
23 10
27,433 3,480
1.9% 3.3%
8.7 6.6
8 days ago 9 days ago
Python Python
Apache License 2.0 MIT License
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.

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.

sahi

Posts with mentions or reviews of sahi. 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?
  • Roboflow 100: A New Object Detection Benchmark
    5 projects | news.ycombinator.com | 28 Dec 2022
    Good idea. I haven’t looked too closely yet at the “hard” datasets.

    We originally considered “fixing” the labels on these datasets by hand, but ultimately decided that label error is one of the challenges “real world” datasets have that models should work to become more robust against. There is some selection bias in that we did make sure that the datasets we chose passed the eye test (in other words, it looked like the user spent a considerable amount of time annotating & a sample of the images looked like they labeled some object of interest).

    For aerial images in particular my guess would be that these models suffer from the “small object problem”[1] where the subjects are tiny compared to the size of the image. Trying a sliding window based approach like SAHI[2] on them would probably produce much better results (at the expense of much lower inference speed).

    [1] https://blog.roboflow.com/detect-small-objects/

    [2] https://github.com/obss/sahi

  • Which model is best for detecting small objects? Yolov3? MaskRCNN, Faster-RCNN?
    2 projects | /r/computervision | 26 May 2022
    Try slicing and yolov4. https://github.com/obss/sahi

What are some alternatives?

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

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

yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

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]

PaddleDetection - Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

mmdetection3d - OpenMMLab's next-generation platform for general 3D object detection.

Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

pytorch-image-models - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

yolact - A simple, fully convolutional model for real-time instance segmentation.

yolact_edge - The first competitive instance segmentation approach that runs on small edge devices at real-time speeds.

PixelLib - Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

pytorch-deeplabv3plus-3D - Deeplabv3 plus 3D version (in pytorch)