Pre processing the image as per VGG-16 Model requirement

PreprocessImageForVGG-16.lua

vgg_mean = {103.939, 116.779, 123.68}

function check_input(img)
  assert(img:dim() == 4, 'img must be N x C x H x W')
  assert(img:size(2) == 3, 'img must have three channels') 
end

function preprocess(img)
  check_input(img)
  local mean = img.new(vgg_mean):view(1, 3, 1, 1):expandAs(img)
  local perm = torch.LongTensor{3, 2, 1}
  return img:index(2, perm):mul(255):add(-1, mean)
end

input_img = image.load("hen.jpg", 3, 'float')
input_img = image.scale(input_img, 224)
H, W = input_img:size(2), input_img:size(3)
input_img = input_img:view(1, 3, H, W)
print(#input_img)


input = preprocess(input_img)