unet VS rankseg

Compare unet vs rankseg and see what are their differences.

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unet rankseg
1 1
4,445 15
- -
0.0 4.6
27 days ago 8 months ago
Jupyter Notebook Jupyter Notebook
MIT License 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.

unet

Posts with mentions or reviews of unet. We have used some of these posts to build our list of alternatives and similar projects.
  • U-net Returning Black Square As Prediction
    1 project | /r/MLQuestions | 7 Feb 2022
    Issue with the model architecture and what I’m trying to do with it? I’ve used the model from this GitHub project (https://github.com/zhixuhao/unet), as it seemed somewhat similar to what I was trying to do. I understand what is happening from layer to layer, but not the input/output parts. (I’ll put the code for it below)

rankseg

Posts with mentions or reviews of rankseg. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing unet and rankseg you can also consider the following projects:

Human-Segmentation-PyTorch - Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

notebooks - Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

cellpose - a generalist algorithm for cellular segmentation with human-in-the-loop capabilities

ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training

Entity - EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

SegGradCAM - SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping

drrmsan - DRRMSAN: Deep Residual Regularized Multi-Scale Attention Networks for segmentation of medical images. Machine Leaning 2 (DA330) Course Project, RKMVERI.

Vision-Project-Image-Segmentation

Deep-Learning-In-Production - Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.

OneFormer - OneFormer: One Transformer to Rule Universal Image Segmentation, arxiv 2022 / CVPR 2023