update examples

Author: taigw

README.md

@@ -1,5 +1,5 @@
-# CRF_wrap
-Matlab and Python wrap of conditional random field (CRF) and fully connected (dense) CRF for 2D and 3D image segmentation, according to the following papers:
+# SimpleCRF
+Matlab and Python wrap of Conditional Random Field (CRF) and fully connected (dense) CRF for 2D and 3D image segmentation, according to the following papers:
 
 [1] Yuri Boykov and Vladimir Kolmogorov, "An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision", in IEEE TPAMI, 2004.
 
@@ -9,7 +9,9 @@ Pushmeet Kohli and Philip H.S. Torr. "Efficiently solving dynamic markov random
 
 [3] Kamnitsas et al. "Multi-scale 3D convolutional neural networks for lesion segmentation in brain MRI", in Proceeding of ISLES challenge, MICCAI, 2015.
 
-![crf_2d](./data/crf_2d.png)
+![maxflow](./data/maxflow.png)
+![densecrf1](./data/densecrf1.png)
+![densecrf2](./data/densecrf2.png)
 
 # Dependency
 This repository depends on the following packages:
@@ -19,3 +21,12 @@ This repository depends on the following packages:
 * DenceCRF http://graphics.stanford.edu/projects/drf/
 
 * 3D Fully Connected CRF https://github.com/Kamnitsask/dense3dCrf
+
+# Examples
+Some demos of using this package are:
+
+* `examples/demo_maxflow.py`: using maxflow for automatic and interactive segmentation of 2D and 3D images.
+
+* `examples/demo_densecrf.py`: using dense CRF for 2D gray scale and RGB image segmentation.
+
+* `examples/demo_densecrf3d.py`: using 3D dense CRF for 3D multi-modal image segmentation.