Many fixes, now generates a single image per frame.

[dyncnn.git] / README.txt

diff --git a/README.txt b/README.txt
index 85cf8ba..e143b3c 100644 (file)
--- a/README.txt
+++ b/README.txt
@@ -5,7 +5,7 @@ the dynamics of 2D shapes as described in
   F. Fleuret. Predicting the dynamics of 2d objects with a deep
   residual network. CoRR, abs/1610.04032, 2016.
 
-  https://arxiv.org/pdf/1610.04032v1
+  https://arxiv.org/abs/1610.04032
 
 This package is composed of a simple 2d physics simulator called
 'flatland' written in C++, to generate the data-set, and a deep
@@ -16,16 +16,17 @@ script.
 
 It will
 
-  (1) generate the data-set of 50k triplets of images,
+  (1) Generate the data-set of 40k triplets of images,
 
-  (2) train the deep network, and output validation results every 100
-      epochs. This take ~30h on a GTX 1080.
+  (2) Train the deep network, and output validation results every 100
+      epochs. This takes 15h on a GTX 1080 with cuda 8.0, cudnn 5.1,
+      and recent torch.
 
-  (3) generate two pictures of the internal activations.
+  (3) Generate two pictures of the internal activations.
 
-  (4) generate a graph with the loss curves if gnuplot is installed.
+  (4) Generate a graph with the loss curves if gnuplot is installed.
 
 --
 Francois Fleuret
-Oct 21, 2016
+Nov 6, 2016
 Martigny