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Add support for scale4 in benchmark

This commit is contained in:
nagadomi 2016-10-10 02:20:57 +09:00
parent ef8bb4b0b9
commit 16731fb634

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@ -18,7 +18,7 @@ cmd:option("-dir", "./data/test", 'test image directory')
cmd:option("-file", "", 'test image file list')
cmd:option("-model1_dir", "./models/anime_style_art_rgb", 'model1 directory')
cmd:option("-model2_dir", "", 'model2 directory (optional)')
cmd:option("-method", "scale", '(scale|noise|noise_scale|user|diff)')
cmd:option("-method", "scale", '(scale|noise|noise_scale|user|diff|scale4)')
cmd:option("-filter", "Catrom", "downscaling filter (Box|Lanczos|Catrom(Bicubic))")
cmd:option("-resize_blur", 1.0, 'blur parameter for resize')
cmd:option("-color", "y", '(rgb|y|r|g|b)')
@ -154,12 +154,24 @@ local function baseline_scale(x, filter)
x:size(2) * 2.0,
filter)
end
local function baseline_scale4(x, filter)
return iproc.scale(x,
x:size(3) * 4.0,
x:size(2) * 4.0,
filter)
end
local function transform_scale(x, opt)
return iproc.scale(x,
x:size(3) * 0.5,
x:size(2) * 0.5,
opt.filter, opt.resize_blur)
end
local function transform_scale4(x, opt)
return iproc.scale(x,
x:size(3) * 0.25,
x:size(2) * 0.25,
opt.filter, opt.resize_blur)
end
local function transform_scale_jpeg(x, opt)
x = iproc.scale(x,
@ -237,6 +249,26 @@ local function benchmark(opt, x, model1, model2)
model2_time = model2_time + (sys.clock() - t)
end
baseline_output = baseline_scale(input, opt.baseline_filter)
elseif opt.method == "scale4" then
input = transform_scale4(x[i].y, opt)
ground_truth = x[i].y
if opt.force_cudnn and i == 1 then -- run cuDNN benchmark first
model1_output = scale_f(model1, 2.0, input, opt.crop_size, opt.batch_size)
if model2 then
model2_output = scale_f(model2, 2.0, input, opt.crop_size, opt.batch_size)
end
end
t = sys.clock()
model1_output = scale_f(model1, 2.0, input, opt.crop_size, opt.batch_size)
model1_output = scale_f(model1, 2.0, model1_output, opt.crop_size, opt.batch_size)
model1_time = model1_time + (sys.clock() - t)
if model2 then
t = sys.clock()
model2_output = scale_f(model2, 2.0, input, opt.crop_size, opt.batch_size)
model2_output = scale_f(model2, 2.0, model2_output, opt.crop_size, opt.batch_size)
model2_time = model2_time + (sys.clock() - t)
end
baseline_output = baseline_scale4(input, opt.baseline_filter)
elseif opt.method == "noise" then
input = transform_jpeg(x[i].y, opt)
ground_truth = x[i].y
@ -604,7 +636,7 @@ if opt.show_progress then
print(opt)
end
if opt.method == "scale" then
if opt.method == "scale" or opt.method == "scale4" then
local f1 = path.join(opt.model1_dir, "scale2.0x_model.t7")
local f2 = path.join(opt.model2_dir, "scale2.0x_model.t7")
local s1, model1 = pcall(w2nn.load_model, f1, opt.force_cudnn)