Skip to content

zbxzc35/kaggle-rsna2018

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

25 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ChallengePneumo Solution for RSNA Pneumonia Detection Challenge (Rank 7)

Install git lfs from here to clone the repository.

The solution files are organized in two directories docker and cli. This provides two ways for reproducing our final results for kaggle.

NOTE: Using docker is our recommended way to reproduce our competition results.

Data Setup

  1. Unzip the test images stage_2_test_images.zip to a convenient path. <path>/stage_2_test_images will be used in all the examples to refer to test images path.

  2. Unzip the train images stage_2_train_images.zip to a convenient path. <path>/stage_2_train_images will be used in all the examples to refer to train images path.

  3. Place models from our_weights folder in a convenient path. <path>/weights will be used in all the examples to refer to model/weights path. You can also leave the weights in the current path in the repository.

System Setup and Requirements

NOTE: To clone the repository, make sure to have git lfs installed.

Training

  • Ubuntu (16.04 recommended)
  • 4 GPUs (NVIDIA GeForce GTX 1080Ti or up)
  • Compatible nvidia drivers
  • docker (version 18.06.1+ recommended)
  • nvidia-docker v2.0+
  • bash v4.3+
  • git lfs

Inference

  • Ubuntu (16.04 recommended)
  • At least 1 GPU (NVIDIA GeForce GTX 1080Ti or up)
  • Compatible nvidia drivers
  • docker (version 18.06.1+ recommended)
  • nvidia-docker v2.0+
  • bash v4.3+
  • git lfs

About

Team ChallengePneumo Solution for RSNA Pneumonia Detection Challenge

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 74.1%
  • C 10.9%
  • Cuda 8.9%
  • Jupyter Notebook 3.1%
  • Shell 1.6%
  • C++ 0.5%
  • Other 0.9%