From c8271af3ab467c4850d4c9a568c9764a2753495e Mon Sep 17 00:00:00 2001 From: nagadomi Date: Wed, 9 Nov 2016 03:06:26 +0900 Subject: [PATCH] add srresnet_12l --- lib/srcnn.lua | 58 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 58 insertions(+) diff --git a/lib/srcnn.lua b/lib/srcnn.lua index afed09d..416fbf4 100644 --- a/lib/srcnn.lua +++ b/lib/srcnn.lua @@ -438,6 +438,63 @@ function srcnn.srresnet_2x(backend, ch) return model end +-- large version of srresnet_2x. current best model but slow. +function srcnn.srresnet_12l(backend, ch) + local function skip(backend, i, o) + local con = nn.Concat(2) + local conv = nn.Sequential() + conv:add(SpatialConvolution(backend, i, o, 3, 3, 1, 1, 1, 1)) + conv:add(ReLU(backend)) + -- depth concat + con:add(conv) + con:add(nn.Identity()) -- skip + return con + end + local function resblock(backend, i, o) + local seq = nn.Sequential() + local con = nn.ConcatTable() + local conv = nn.Sequential() + conv:add(SpatialConvolution(backend, i, o, 3, 3, 1, 1, 0, 0)) + conv:add(nn.LeakyReLU(0.1, true)) + conv:add(SpatialConvolution(backend, o, o, 3, 3, 1, 1, 0, 0)) + conv:add(nn.LeakyReLU(0.1, true)) + con:add(conv) + if i == o then + con:add(nn.SpatialZeroPadding(-2, -2, -2, -2)) -- identity + de-padding + else + local seq = nn.Sequential() + seq:add(SpatialConvolution(backend, i, o, 1, 1, 1, 1, 0, 0)) + seq:add(nn.SpatialZeroPadding(-2, -2, -2, -2)) + con:add(seq) + end + seq:add(con) + seq:add(nn.CAddTable()) + return seq + end + local model = nn.Sequential() + model:add(SpatialConvolution(backend, ch, 32, 3, 3, 1, 1, 0, 0)) + model:add(nn.LeakyReLU(0.1, true)) + model:add(resblock(backend, 32, 64)) + model:add(resblock(backend, 64, 64)) + model:add(resblock(backend, 64, 128)) + model:add(resblock(backend, 128, 128)) + model:add(resblock(backend, 128, 256)) + model:add(resblock(backend, 256, 256)) + model:add(SpatialFullConvolution(backend, 256, ch, 4, 4, 2, 2, 3, 3):noBias()) + model:add(w2nn.InplaceClip01()) + model:add(nn.View(-1):setNumInputDims(3)) + model.w2nn_arch_name = "srresnet_12l" + model.w2nn_offset = 28 + model.w2nn_scale_factor = 2 + model.w2nn_resize = true + model.w2nn_channels = ch + + --model:cuda() + --print(model:forward(torch.Tensor(32, ch, 92, 92):uniform():cuda()):size()) + + return model +end + -- for segmentation function srcnn.fcn_v1(backend, ch) -- input_size = 120 @@ -516,4 +573,5 @@ local model = srcnn.fcn_v1("cunn", 3):cuda() print(model:forward(torch.Tensor(1, 3, 108, 108):zero():cuda()):size()) print(model) --]] + return srcnn