diff options
| author | dkazanc <dkazanc@hotmail.com> | 2019-02-18 14:48:29 +0000 |
|---|---|---|
| committer | dkazanc <dkazanc@hotmail.com> | 2019-02-18 14:48:29 +0000 |
| commit | 787b534643d5b4cad4e6f8d9c4b524b52d804348 (patch) | |
| tree | c7b070ca2950b8abeaad93b6b295465a8dbe1413 /Readme.md | |
| parent | 69219dd3d69cc644bc858986ba71ee02e8e1952f (diff) | |
| download | regularization-787b534643d5b4cad4e6f8d9c4b524b52d804348.tar.gz regularization-787b534643d5b4cad4e6f8d9c4b524b52d804348.tar.bz2 regularization-787b534643d5b4cad4e6f8d9c4b524b52d804348.tar.xz regularization-787b534643d5b4cad4e6f8d9c4b524b52d804348.zip | |
TGV3D_GPU added, demos updated fpr Python/Matlab
Diffstat (limited to 'Readme.md')
| -rw-r--r-- | Readme.md | 4 |
1 files changed, 2 insertions, 2 deletions
@@ -33,7 +33,7 @@ 1. Rudin-Osher-Fatemi (ROF) Total Variation (explicit PDE minimisation scheme) **2D/3D CPU/GPU** (Ref. *1*) 2. Fast-Gradient-Projection (FGP) Total Variation **2D/3D CPU/GPU** (Ref. *2*) 3. Split-Bregman (SB) Total Variation **2D/3D CPU/GPU** (Ref. *5*) -4. Total Generalised Variation (TGV) model for higher-order regularisation **2D CPU/GPU** (Ref. *6*) +4. Total Generalised Variation (TGV) model for higher-order regularisation **2D/3D CPU/GPU** (Ref. *6*) 5. Linear and nonlinear diffusion (explicit PDE minimisation scheme) **2D/3D CPU/GPU** (Ref. *8*) 6. Anisotropic Fourth-Order Diffusion (explicit PDE minimisation) **2D/3D CPU/GPU** (Ref. *9*) 7. A joint ROF-LLT (Lysaker-Lundervold-Tai) model for higher-order regularisation **2D/3D CPU/GPU** (Ref. *10,11*) @@ -93,7 +93,7 @@ conda install ccpi-regulariser -c ccpi -c conda-forge #### Python (conda-build) ``` - export CIL_VERSION=0.10.3 + export CIL_VERSION=0.10.4 conda build Wrappers/Python/conda-recipe --numpy 1.12 --python 3.5 conda install ccpi-regulariser=${CIL_VERSION} --use-local --force cd demos/ |