semvec/pypi-packages huggingface dataset:
ternausnet 0.0.1
UNet with VGG encoders
License: MIT

# TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation

By [Vladimir Iglovikov](https://www.linkedin.com/in/iglovikov/) and [Alexey Shvets](https://www.linkedin.com/in/shvetsiya/)

# Introduction

TernausNet is a modification of the celebrated UNet architecture that is widely used for binary Image Segmentation. For more details, please refer to our [arXiv paper](https://arxiv.org/abs/1801.05746).

![UNet11](https://habrastorage.org/webt/hu/ji/ir/hujiirvpgpf7eswq88h_x7ahliw.png)

(Network architecure)

![loss_curve](https://habrastorage.org/webt/no/up/xq/noupxqqk_ivqwv3e7btyxtemt0m.png)

Pre-trained encoder speeds up convergence even on the datasets with a different semantic features. Above curve shows validation Jaccard Index (IOU) as a function of epochs for [Aerial Imagery](https://project.inria.fr/aerialimagelabeling/)

This architecture was a part of the [winning solutiuon](http://blog.kaggle.com/2017/12/22/carvana-image-masking-first-place-interview/) (1st out of 735 teams) in the [Carvana Image Masking Challenge](https://www.kaggle.com/c/carvana-image-masking-challenge).

# Citing TernausNet
Please cite TernausNet in your publications if it helps your research:

```
@ARTICLE{arXiv:1801.05746,
         author = {V. Iglovikov and A. Shvets},
          title = {TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation},
        journal = {ArXiv e-prints},
         eprint = {1801.05746}, 
           year = 2018
        }
```

# Example of the train and test pipeline

https://github.com/ternaus/robot-surgery-segmentation
okerr 0.1.3
A simple Result with match functionality for Python
License: MIT
Requires Python: >=3.6,<4.0
Keywords: result,utility-tool,rust

okerr
=====

.. image:: https://img.shields.io/github/license/ceb10n/okerr
    :target: https://img.shields.io/github/license/ceb10n/okerr

.. image:: https://circleci.com/gh/ceb10n/okerr.svg?style=shield
    :target: https://circleci.com/gh/ceb10n/okerr

.. image:: https://codecov.io/gh/ceb10n/okerr/branch/master/graph/badge.svg
  :target: https://codecov.io/gh/ceb10n/okerr

A simple Result with match functionality for Python 3 inspired by `Rust's Result Enum
<https://doc.rust-lang.org/std/result/>`__.


License
-------

MIT License