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Update fcn_v1

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nagadomi 2016-10-24 09:10:17 +09:00
parent f16950438c
commit 74ed227f48
1 changed files with 30 additions and 17 deletions
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47
lib/srcnn.lua
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@ -439,46 +439,60 @@ end
-- for segmentation
function srcnn.fcn_v1(backend, ch)
-- input size = 128
-- input_size = 120
local model = nn.Sequential()
--i = 120
--model:cuda()
--print(model:forward(torch.Tensor(32, ch, i, i):uniform():cuda()):size())
model:add(SpatialConvolution(backend, ch, 32, 5, 5, 2, 2, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 32, 32, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialMaxPooling(backend, 2, 2, 2, 2))
model:add(SpatialConvolution(backend, 32, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 64, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialMaxPooling(backend, 2, 2, 2, 2))
model:add(SpatialConvolution(backend, 64, 128, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialMaxPooling(backend, 2, 2, 2, 2))
model:add(SpatialConvolution(backend, 128, 256, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 256, 256, 3, 3, 1, 1, 0, 0))
model:add(SpatialConvolution(backend, 128, 128, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialMaxPooling(backend, 2, 2, 2, 2))
model:add(SpatialFullConvolution(backend, 256, 128, 4, 4, 2, 2, 2, 2))
model:add(SpatialConvolution(backend, 128, 256, 1, 1, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialFullConvolution(backend, 128, 64, 4, 4, 2, 2, 2, 2))
model:add(nn.Dropout(0.5, false, true))
model:add(SpatialConvolution(backend, 256, 256, 1, 1, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialFullConvolution(backend, 64, 32, 4, 4, 2, 2, 2, 2))
model:add(nn.Dropout(0.5, false, true))
model:add(SpatialFullConvolution(backend, 256, 128, 2, 2, 2, 2, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialFullConvolution(backend, 32, ch, 4, 4, 2, 2, 2, 2))
model:add(SpatialFullConvolution(backend, 128, 128, 2, 2, 2, 2, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 128, 64, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialFullConvolution(backend, 64, 64, 2, 2, 2, 2, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialConvolution(backend, 64, 32, 3, 3, 1, 1, 0, 0))
model:add(nn.LeakyReLU(0.1, true))
model:add(SpatialFullConvolution(backend, 32, ch, 4, 4, 2, 2, 3, 3))
model:add(w2nn.InplaceClip01())
model:add(nn.View(-1):setNumInputDims(3))
model.w2nn_arch_name = "fcn_v1"
model.w2nn_offset = 39
model.w2nn_offset = 36
model.w2nn_scale_factor = 1
model.w2nn_channels = ch
--model:cuda()
--print(model:forward(torch.Tensor(32, ch, 128, 128):uniform():cuda()):size())
model.w2nn_input_size = 120
return model
end
function srcnn.create(model_name, backend, color)
model_name = model_name or "vgg_7"
backend = backend or "cunn"
@ -500,9 +514,8 @@ function srcnn.create(model_name, backend, color)
end
end
--[[
local model = srcnn.srresnet_2x("cunn", 3):cuda()
local model = srcnn.fcn_v1("cunn", 3):cuda()
print(model:forward(torch.Tensor(1, 3, 108, 108):zero():cuda()):size())
print(model)
print(model:forward(torch.Tensor(1, 3, 128, 128):zero():cuda()):size())
--]]
return srcnn