From fcc99afbf6f3e206c40ff0c711a63fcaf5e620a8 Mon Sep 17 00:00:00 2001
From: Aleksei Tiulpin <aleksei.tiulpin@protonmail.ch>
Date: Wed, 20 Jun 2018 13:56:28 +0300
Subject: [PATCH] added the pretrained model

---
 .gitattributes                                   |   1 +
 README.md                                        |  11 +++++------
 snapshots_knee_grading/.DS_Store                 | Bin 0 -> 8196 bytes
 .../2017_10_10_12_30_42/args.pkl                 | Bin 0 -> 433 bytes
 .../2017_10_10_12_30_42/epoch_64.pth             |   3 +++
 .../2017_10_10_12_30_42/logs.npy                 | Bin 0 -> 4080 bytes
 .../2017_10_10_12_30_46/args.pkl                 | Bin 0 -> 433 bytes
 .../2017_10_10_12_30_46/epoch_97.pth             |   3 +++
 .../2017_10_10_12_30_46/logs.npy                 | Bin 0 -> 4080 bytes
 .../2017_10_10_12_30_49/args.pkl                 | Bin 0 -> 433 bytes
 .../2017_10_10_12_30_49/epoch_96.pth             |   3 +++
 .../2017_10_10_12_30_49/logs.npy                 | Bin 0 -> 4080 bytes
 snapshots_knee_grading/mean_std.npy              | Bin 0 -> 96 bytes
 snapshots_knee_grading_resnet/.DS_Store          | Bin 0 -> 6148 bytes
 .../2017_10_17_13_10_14/args.pkl                 | Bin 0 -> 441 bytes
 .../2017_10_17_13_10_14/epoch_12.pth             |   3 +++
 .../2017_10_17_13_10_14/logs.npy                 | Bin 0 -> 1240 bytes
 snapshots_knee_grading_resnet/mean_std.npy       | Bin 0 -> 128 bytes
 18 files changed, 18 insertions(+), 6 deletions(-)
 create mode 100644 .gitattributes
 create mode 100644 snapshots_knee_grading/.DS_Store
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_42/args.pkl
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_42/epoch_64.pth
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_42/logs.npy
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_46/args.pkl
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_46/epoch_97.pth
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_46/logs.npy
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_49/args.pkl
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_49/epoch_96.pth
 create mode 100644 snapshots_knee_grading/2017_10_10_12_30_49/logs.npy
 create mode 100644 snapshots_knee_grading/mean_std.npy
 create mode 100644 snapshots_knee_grading_resnet/.DS_Store
 create mode 100644 snapshots_knee_grading_resnet/2017_10_17_13_10_14/args.pkl
 create mode 100644 snapshots_knee_grading_resnet/2017_10_17_13_10_14/epoch_12.pth
 create mode 100644 snapshots_knee_grading_resnet/2017_10_17_13_10_14/logs.npy
 create mode 100644 snapshots_knee_grading_resnet/mean_std.npy

diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000..ec4a626
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1 @@
+*.pth filter=lfs diff=lfs merge=lfs -text
diff --git a/README.md b/README.md
index 41ea71f..6de1188 100644
--- a/README.md
+++ b/README.md
@@ -13,8 +13,8 @@ Here we present the training codes and the pretrained models from each of our ex
 
 To train the networks, we used Ubuntu 14.04, CUDA 8.0 and CuDNN v.6. Below please find the other dependencies which need to be installed:
 
-* Python 3
-* pytorch with CUDA support
+* Python 3.6
+* pytorch < 0.4.0 with CUDA support
 * PIL
 * matplotlib
 * Jupyter Notebook (to work with attention maps)
@@ -31,12 +31,12 @@ However, you can run the codes as they are, just use the parameters fixed in the
 ## Attention maps examples
 Our model learns localized radiological findings as we imposed prior anatomical knowledge to teh network architecture. Here are some examples of attention maps and predictions (Kellgren-Lawrence grade 2 ground truth):
 
-<img src="https://github.com/lext/DeepKnee/blob/master/pics/15_2_R_1_1_1_3_1_0_own.jpg" width="260"/> <img src="https://github.com/lext/DeepKnee/blob/master/pics/235_2_R_3_3_0_0_1_1_own.jpg" width="260"/>  <img src="https://github.com/lext/DeepKnee/blob/master/pics/77_2_R_2_0_0_0_0_1_own.jpg" width="260"/> 
+<img src="https://github.com/lext/DeepKnee/blob/master/pics/15_2_R_1_1_1_3_1_0_own.jpg" width="260"/> <img src="https://github.com/lext/DeepKnee/blob/master/pics/235_2_R_3_3_0_0_1_1_own.jpg" width="260"/>  <img src="https://github.com/lext/DeepKnee/blob/master/pics/77_2_R_2_0_0_0_0_1_own.jpg" width="260"/>
 
-## TODO
+## What is in here
 
 - [x] Codes for the main experiements (Supplementary information of the article)
-- [ ] Pre-trained models
+- [x] Pre-trained models
 - [ ] Datasets generation scripts
 - [ ] MOST and OAI cohorts bounding box annotations
 
@@ -44,4 +44,3 @@ Our model learns localized radiological findings as we imposed prior anatomical
 ## License
 
 This code is freely available only for research purpuses.
-
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diff --git a/snapshots_knee_grading_resnet/2017_10_17_13_10_14/args.pkl b/snapshots_knee_grading_resnet/2017_10_17_13_10_14/args.pkl
new file mode 100644
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GIT binary patch
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diff --git a/snapshots_knee_grading_resnet/2017_10_17_13_10_14/epoch_12.pth b/snapshots_knee_grading_resnet/2017_10_17_13_10_14/epoch_12.pth
new file mode 100644
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diff --git a/snapshots_knee_grading_resnet/2017_10_17_13_10_14/logs.npy b/snapshots_knee_grading_resnet/2017_10_17_13_10_14/logs.npy
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diff --git a/snapshots_knee_grading_resnet/mean_std.npy b/snapshots_knee_grading_resnet/mean_std.npy
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GIT binary patch
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