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Ease of use changes #9

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3e721ef
Update Demo_test_DnCNN3.m
kevinzying Jul 17, 2017
b495136
Update Demo_test_DnCNN3.m
kevinzying Jul 17, 2017
5400dde
Update Demo_test_DnCNN.m
kevinzying Jul 17, 2017
ea564ed
Add files via upload
kevinzying Jul 17, 2017
533936e
Rename hr2grey.m to testsets/hr2grey.m
kevinzying Jul 17, 2017
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11 changes: 6 additions & 5 deletions Demo_test_DnCNN.m
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Original file line number Diff line number Diff line change
Expand Up @@ -5,12 +5,12 @@

% clear; clc;
addpath('utilities');
folderTest = 'testsets\Set12'; %%% test dataset
%folderTest = 'testsets\BSD68';
testDir = 'testsets';
folderTest = 'BSD68'; %%% test dataset
folderModel = 'model';
noiseSigma = 25; %%% image noise level
showResult = 1;
useGPU = 1;
useGPU = 0; %%% GPU status
pauseTime = 1;

%%% load [specific] Gaussian denoising model
Expand All @@ -23,8 +23,8 @@
% load(fullfile(folderModel,'GD_Gray_Blind.mat'));


%%%
% net = vl_simplenn_tidy(net);
%%% uncomment if necessary for different MatConvNet versions
%net = vl_simplenn_tidy(net);

% for i = 1:size(net.layers,2)
% net.layers{i}.precious = 1;
Expand All @@ -36,6 +36,7 @@
end

%%% read images
folderTest = fullfile(testDir, folderTest);
ext = {'*.jpg','*.png','*.bmp'};
filePaths = [];
for i = 1 : length(ext)
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5 changes: 3 additions & 2 deletions Demo_test_DnCNN3.m
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Expand Up @@ -7,15 +7,15 @@

%%% testing set
tasks = {'GD','SR','DB'}; %%% three tasks
imageSets = {'BSD68','Set5','Set14','BSD100','Urben100','classic5','LIVE1'}; %%% testing dataset
imageSets = {'BSD68','Set5','Set14','BSD100','Urban100','classic5','LIVE1'}; %%% testing dataset

%%% setting
taskTest = tasks([1 2 3]); %%% choose the tasks for evaluation
setTest = {imageSets([1]),imageSets([2:5]),imageSets([6 7])}; %%% select the datasets for each tasks
showResult = [1 1 1]; %%% save the restored images
pauseTime = 1;
folderModel = 'model';
useGPU = 1; % 1 or 0, true or false
useGPU = 0; % 1 or 0, true or false

folderTest = 'testsets';
folderResult= 'results';
Expand All @@ -36,6 +36,7 @@
%%% load DnCNN-3 model
load(fullfile(folderModel,'DnCNN3.mat'));

%%% uncomment if necessary for different MatConvNet versions
%net = vl_simplenn_tidy(net);
% for i = 1:size(net.layers,2)
% net.layers{i}.precious = 1;
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