tunable parameters
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nagadomi
parent
cf862782a5
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3ea16b3b86
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@ -11,25 +11,44 @@ local function pcacov(x)
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local ce, cv = torch.symeig(c, 'V')
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return ce, cv
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end
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function data_augmentation.color_noise(src, factor)
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function data_augmentation.color_noise(src, p, factor)
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factor = factor or 0.1
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local src, conversion = iproc.byte2float(src)
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local src_t = src:reshape(src:size(1), src:nElement() / src:size(1)):t():contiguous()
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local ce, cv = pcacov(src_t)
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local color_scale = torch.Tensor(3):uniform(1 / (1 + factor), 1 + factor)
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pca_space = torch.mm(src_t, cv):t():contiguous()
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for i = 1, 3 do
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pca_space[i]:mul(color_scale[i])
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end
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local dest = torch.mm(pca_space:t(), cv:t()):t():contiguous():resizeAs(src)
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dest[torch.lt(dest, 0.0)] = 0.0
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dest[torch.gt(dest, 1.0)] = 1.0
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if torch.uniform() < p then
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local src, conversion = iproc.byte2float(src)
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local src_t = src:reshape(src:size(1), src:nElement() / src:size(1)):t():contiguous()
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local ce, cv = pcacov(src_t)
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local color_scale = torch.Tensor(3):uniform(1 / (1 + factor), 1 + factor)
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pca_space = torch.mm(src_t, cv):t():contiguous()
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for i = 1, 3 do
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pca_space[i]:mul(color_scale[i])
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end
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local dest = torch.mm(pca_space:t(), cv:t()):t():contiguous():resizeAs(src)
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dest[torch.lt(dest, 0.0)] = 0.0
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dest[torch.gt(dest, 1.0)] = 1.0
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if conversion then
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dest = iproc.float2byte(dest)
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if conversion then
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dest = iproc.float2byte(dest)
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end
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return dest
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else
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return src
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end
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end
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function data_augmentation.overlay(src, p)
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if torch.uniform() < p then
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local r = torch.uniform()
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local src, conversion = iproc.byte2float(src)
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src = src:contiguous()
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local flip = data_augmentation.flip(src)
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flip:mul(r):add(src * (1.0 - r))
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if conversion then
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flip = iproc.float2byte(flip)
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end
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return flip
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else
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return src
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end
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return dest
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end
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function data_augmentation.shift_1px(src)
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-- reducing the even/odd issue in nearest neighbor scaler.
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@ -76,20 +95,4 @@ function data_augmentation.flip(src)
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end
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return dest
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end
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function data_augmentation.overlay(src, p)
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p = p or 0.25
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if torch.uniform() < p then
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local r = torch.uniform(0.2, 0.8)
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local src, conversion = iproc.byte2float(src)
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src = src:contiguous()
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local flip = data_augmentation.flip(src)
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flip:mul(r):add(src * (1.0 - r))
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if conversion then
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flip = iproc.float2byte(flip)
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end
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return flip
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else
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return src
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end
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end
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return data_augmentation
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@ -6,9 +6,8 @@ local data_augmentation = require 'data_augmentation'
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local pairwise_transform = {}
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local function random_half(src, p)
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p = p or 0.25
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local filter = ({"Box","Box","Blackman","SincFast","Jinc"})[torch.random(1, 5)]
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if p < torch.uniform() and (src:size(2) > 768 and src:size(3) > 1024) then
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if torch.uniform() < p then
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local filter = ({"Box","Box","Blackman","SincFast","Jinc"})[torch.random(1, 5)]
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return iproc.scale(src, src:size(3) * 0.5, src:size(2) * 0.5, filter)
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else
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return src
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@ -34,17 +33,11 @@ local function crop_if_large(src, max_size)
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end
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local function preprocess(src, crop_size, options)
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local dest = src
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if options.random_half then
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dest = random_half(dest)
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end
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dest = random_half(dest, options.random_half_rate)
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dest = crop_if_large(dest, math.max(crop_size * 2, options.max_size))
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dest = data_augmentation.flip(dest)
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if options.color_noise then
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dest = data_augmentation.color_noise(dest)
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end
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if options.overlay then
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dest = data_augmentation.overlay(dest)
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end
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dest = data_augmentation.color_noise(dest, options.random_color_noise_rate)
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dest = data_augmentation.overlay(dest, options.random_overlay_rate)
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dest = data_augmentation.shift_1px(dest)
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return dest
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@ -26,19 +26,19 @@ cmd:option("-method", "scale", 'method to training (noise|scale)')
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cmd:option("-noise_level", 1, '(1|2)')
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cmd:option("-style", "art", '(art|photo)')
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cmd:option("-color", 'rgb', '(y|rgb)')
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cmd:option("-color_noise", 0, 'data augmentation using color noise (1|0)')
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cmd:option("-overlay", 0, 'data augmentation using overlay (1|0)')
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cmd:option("-random_color_noise_rate", 0.0, 'data augmentation using color noise (0.0-1.0)')
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cmd:option("-random_overlay_rate", 0.0, 'data augmentation using flipped image overlay (0.0-1.0)')
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cmd:option("-random_half_rate", 0.0, 'data augmentation using half resolution image (0.0-1.0)')
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cmd:option("-scale", 2.0, 'scale factor (2)')
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cmd:option("-learning_rate", 0.00025, 'learning rate for adam')
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cmd:option("-random_half", 0, 'data augmentation using half resolution image (0|1)')
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cmd:option("-crop_size", 46, 'crop size')
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cmd:option("-max_size", 256, 'if image is larger than max_size, image will be crop to max_size randomly')
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cmd:option("-batch_size", 8, 'mini batch size')
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cmd:option("-epoch", 200, 'number of total epochs to run')
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cmd:option("-thread", -1, 'number of CPU threads')
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cmd:option("-jpeg_sampling_factors", 444, '(444|420)')
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cmd:option("-validation_rate", 0.05, 'validation-set rate of data')
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cmd:option("-validation_crops", 80, 'number of region per image in validation')
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cmd:option("-validation_rate", 0.05, 'validation-set rate (number_of_training_images * validation_rate > 1)')
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cmd:option("-validation_crops", 80, 'number of cropping region per image in validation')
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cmd:option("-active_cropping_rate", 0.5, 'active cropping rate')
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cmd:option("-active_cropping_tries", 10, 'active cropping tries')
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cmd:option("-nr_rate", 0.7, 'trade-off between reducing noise and erasing details (0.0-1.0)')
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@ -69,21 +69,6 @@ if not (settings.style == "art" or
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settings.style == "photo") then
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error(string.format("unknown style: %s", settings.style))
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end
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if settings.random_half == 1 then
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settings.random_half = true
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else
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settings.random_half = false
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end
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if settings.color_noise == 1 then
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settings.color_noise = true
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else
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settings.color_noise = false
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end
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if settings.overlay == 1 then
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settings.overlay = true
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else
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settings.overlay = false
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end
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if settings.thread > 0 then
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torch.setnumthreads(tonumber(settings.thread))
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46
train.lua
46
train.lua
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@ -85,20 +85,20 @@ local function transformer(x, is_validation, n, offset)
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x = compression.decompress(x)
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n = n or settings.batch_size;
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if is_validation == nil then is_validation = false end
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local color_noise = nil
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local overlay = nil
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local random_color_noise_rate = nil
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local random_overlay_rate = nil
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local active_cropping_rate = nil
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local active_cropping_tries = nil
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if is_validation then
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active_cropping_rate = 0
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active_cropping_tries = 0
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color_noise = false
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overlay = false
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random_color_noise_rate = 0.0
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random_overlay_rate = 0.0
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else
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active_cropping_rate = settings.active_cropping_rate
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active_cropping_tries = settings.active_cropping_tries
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color_noise = settings.color_noise
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overlay = settings.overlay
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random_color_noise_rate = settings.random_color_noise_rate
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random_overlay_rate = settings.random_overlay_rate
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end
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if settings.method == "scale" then
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@ -106,13 +106,14 @@ local function transformer(x, is_validation, n, offset)
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settings.scale,
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settings.crop_size, offset,
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n,
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{ color_noise = color_noise,
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overlay = overlay,
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random_half = settings.random_half,
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max_size = settings.max_size,
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active_cropping_rate = active_cropping_rate,
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active_cropping_tries = active_cropping_tries,
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rgb = (settings.color == "rgb")
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{
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random_half_rate = settings.random_half_rate,
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random_color_noise_rate = random_color_noise_rate,
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random_overlay_rate = random_overlay_rate,
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max_size = settings.max_size,
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active_cropping_rate = active_cropping_rate,
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active_cropping_tries = active_cropping_tries,
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rgb = (settings.color == "rgb")
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})
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elseif settings.method == "noise" then
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return pairwise_transform.jpeg(x,
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@ -120,15 +121,16 @@ local function transformer(x, is_validation, n, offset)
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settings.noise_level,
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settings.crop_size, offset,
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n,
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{ color_noise = color_noise,
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overlay = overlay,
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random_half = settings.random_half,
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max_size = settings.max_size,
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jpeg_sampling_factors = settings.jpeg_sampling_factors,
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active_cropping_rate = active_cropping_rate,
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active_cropping_tries = active_cropping_tries,
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nr_rate = settings.nr_rate,
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rgb = (settings.color == "rgb")
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{
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random_half_rate = settings.random_half_rate,
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random_color_noise_rate = random_color_noise_rate,
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random_overlay_rate = random_overlay_rate,
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max_size = settings.max_size,
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jpeg_sampling_factors = settings.jpeg_sampling_factors,
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active_cropping_rate = active_cropping_rate,
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active_cropping_tries = active_cropping_tries,
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nr_rate = settings.nr_rate,
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rgb = (settings.color == "rgb")
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})
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end
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end
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