From 7ed57b21284de87a49f6be21f0c84ff51804322c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Dar=C3=ADo=20Here=C3=B1=C3=BA?= Date: Fri, 10 May 2019 14:28:35 -0300 Subject: [PATCH] Fix typo on string 107. Plus some minor proposals --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 3515adf..7941117 100644 --- a/README.md +++ b/README.md @@ -19,7 +19,7 @@ - train_segmentation.py # Step 2, segmentation with UNet Model - model_UNet.py # UNet model definition -- train_classificaion.py # Step 3, classificaiton with VGG/Inception/ResNet/DenseNet +- train_classification.py # Step 3, classification with VGG/Inception/ResNet/DenseNet - model_VGG.py # VGG model definition - model_Inception.py # Inception model definition - model_ResNet.py # ResNet model definition @@ -44,7 +44,7 @@ - regions - closing - dilation -- collect all meta information(seriesuid, shape, file_path, origin, spacing, coordinates, cover_ratio, etc.) and store in **ONE** cache file for fast training init. +- collect all meta information (seriesuid, shape, file_path, origin, spacing, coordinates, cover_ratio, etc.) and store in **ONE** cache file for fast training init. - see preprocessing in `/train_ipynbs/preprocess.ipynb` file Distribution of the lung part takes on a whole CT. @@ -104,7 +104,7 @@ Pictures tells that: **hyperparameter tunning really matters**. - `DenseNet` draws tons of experience from origin paper. [https://arxiv.org/abs/1608.06993](https://arxiv.org/abs/1608.06993) - 3 dense\_block with 5 bn\_relu\_conv layers according to paper. - - transition\_block after every dense\_block, expcet the last one. + - transition\_block after every dense\_block, except the last one. - Optional config for **DenseNet-BC**(paper called it): **1\*1\*1 depth-size seperable conv**, and **transition_block compression**.