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require 'image'
-- Create an instance of the test framework
local mytester = torch.Tester()
local precision_mean = 1e-3
local test = {}
function checkPNG(imfile, depth, tensortype, want)
local img = image.load(imfile, depth, tensortype)
-- Tensors have to be converted to double, since assertTensorEq does not support ByteTensor
print('img: ', img)
print('want: ', want)
mytester:assertTensorEq(img:double(), want:double(), precision_mean,
string.format('%s: pixel values are unexpected', imfile))
end
function test.LoadPNG()
-- Gray 8-bit PNG image with width = 3, height = 1
local gray8byte = torch.ByteTensor({{{0,127,255}}})
checkPNG('gray3x1.png', 1, 'byte', gray8byte)
local gray8double = torch.DoubleTensor({{{0, 127/255, 1}}})
checkPNG('gray3x1.png', 1, 'double', gray8double)
-- Gray 16-bit PNG image with width=1, height = 2
local gray16byte = torch.ByteTensor({{{0, 255}}})
checkPNG('gray16-1x2.png', 1, 'byte', gray16byte)
local gray16float = torch.FloatTensor({{{0, 65534/65535}}})
checkPNG('gray16-1x2.png', 1, 'float', gray16float)
-- Color 8-bit PNG image with width = 2, height = 1
local rgb8byte = torch.ByteTensor({{{255, 0, 0, 127, 63, 0}}})
checkPNG('rgb2x1.png', 3, 'byte', rgb8byte)
local rgb8float = torch.FloatTensor({{{1, 0, 0, 127/255, 63/255, 0}}})
checkPNG('rgb2x1.png', 3, 'float', rgb8float)
-- Color 16-bit PNG image with width = 2, height = 1
local rgb16byte = torch.ByteTensor({{{255, 0, 0, 127, 63, 0}}})
checkPNG('rgb16-2x1.png', 3, 'byte', rgb16byte)
local rgb16float = torch.FloatTensor({{{1, 0, 0, 32767/65535, 16383/65535, 0}}})
checkPNG('rgb16-2x1.png', 3, 'float', rgb16float)
end
-- Now run the test above
mytester:add(test)
mytester:run()
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