R/get_masked_pixels_training_set.r

In surh/RosetteDetector: RosetteDetector

# (C) Copyright 2017 Sur Herrera Paredes
# 
# This file is part of RosetteDetector.
# 
# RosetteDetector is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# 
# RosetteDetector is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
# 
# You should have received a copy of the GNU General Public License
# along with RosetteDetector.  If not, see <http://www.gnu.org/licenses/>.

#' Get masked pixels in training set
#' 
#' Takes a a list of images and masks and extracts pixels and pixel features
#' from the unmasked portion of the image
#' 
#' This function extracts nine features from every pixel. Makes a table indicating pixke
#' coordinates and feature values, and then subsets the table returning only unmasked pixels.
#' 
#' The 9 features are the intensity values for the RGB space, as well as the gradient magnitude
#' and gradient orientation for each color channel.
#' 
#' @param Img A list where every element is a list with elements img and mask. See
#' output from \link{get_images_and_masks} for example.
#' 
#' @return A data.frame of pixel features for unmasked pixels.
#' 
#' @export
get_masked_pixels_training_set <- function(Img){
  # Img <- Images[[1]]
  # Img <- plant_images[[1]]
  
  # Get gradients
  Grad_R <- calculate_gradient(Img$img[,,1])
  Grad_G <- calculate_gradient(Img$img[,,2])
  Grad_B <- calculate_gradient(Img$img[,,3])
  
  # make table
  img.molten <- melt(Img$mask)
  img.molten <- cbind(img.molten,melt_channels(Img$img)[,3:5])
  img.molten$mag_R <- melt(Grad_R$magnitude)$value
  img.molten$mag_G <- melt(Grad_G$magnitude)$value
  img.molten$mag_B <- melt(Grad_B$magnitude)$value
  img.molten$or_R <- melt(Grad_R$orientation)$value
  img.molten$or_G <- melt(Grad_G$orientation)$value
  img.molten$or_B <- melt(Grad_B$orientation)$value
  img.molten[is.na(img.molten)] <- 0
  
  # select data
  Dat <- img.molten[ img.molten$value == 1, ]
  
  Dat$Var1 <- NULL
  Dat$Var2 <- NULL
  
  return(Dat)
}