Giter Site home page Giter Site logo

nrahimi544 / skin-lesion-challenge Goto Github PK

View Code? Open in Web Editor NEW

This project forked from robzuazua/skin-lesion-challenge

0.0 0.0 0.0 208.77 MB

ISIC 2018 challenge

License: Apache License 2.0

Shell 0.01% Python 1.65% Makefile 0.01% HTML 0.07% Smarty 0.01% Jupyter Notebook 98.27%

skin-lesion-challenge's Introduction

fastai

The fastai deep learning library. See the fastai website to get started.

Important: as of this moment pytorch.org's pre-1.0.0 version (torch-nightly) supports:

  • linux: fully
  • mac: CPU-only
  • windows: not supported

This will change once pytorch 1.0.0 is released. Please watch for updates here.

Conda Install

To install fastai with pytorch-nightly + CUDA 9.2 simply run:

conda install -c pytorch -c fastai fastai pytorch-nightly cuda92

If your setup doesn't have CUDA support remove the cuda92 above (in which case you'll only be able to train on CPU, not GPU, which will be much slower). For different versions of the CUDA toolkit, you'll need to install the appropriate CUDA conda package based on what you've got installed on your system (i.e. instead of cuda92 in the above, pick the appropriate option for whichever toolkit version you have installed; to see a list of options type: conda search "cuda*" -c pytorch).

NB: We are currently using a re-packaged torchvision in order to support pytorch-nightly, which is required for using fastai.

PyPI Install

First install the nightly pytorch build, e.g. for CUDA 9.2:

pip install torch_nightly -f https://download.pytorch.org/whl/nightly/cu92/torch_nightly.html

If you have a different CUDA version find the right build here. Choose Preview/Linux/Pip/python3.6|python3.7 and your CUDA version and it will give you the correct install instruction.

Next, install a custom torchvision build, that is built against torch_nightly.

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ torchvision==0.2.1.post1

Now you can install fastai. Note, that this is a beta test version at the moment, please report any issues:

pip install fastai

Sometimes, the last pip command still tries to get torch-0.4.1. If that happens to you, do:

pip uninstall torchvision fastai
pip install --no-deps torchvision
pip install fastai

Developer Install

First, follow the instructions above for either PyPi or Conda. Then remove the fastai package (pip uninstall fastai or conda uninstall fastai) and replace it with a pip editable install:

git clone https://github.com/fastai/fastai
cd fastai
pip install -e .
tools/run-after-git-clone

Please refer to CONTRIBUTING.md and the developers guide for more details.

Copyright

Copyright 2017 onwards, fast.ai, Inc. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. A copy of the License is provided in the LICENSE file in this repository.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.