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August 13, 2018 13:42
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Calculate the average face on the Olivetti dataset in R
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rm(list=ls()) | |
require(dplyr) | |
load(file="images_formatted.Rdata") | |
D <- out; rm(out) | |
#------------------------------------------------------------------------------- | |
# Brief description of the data | |
# D is a 399x4096 matrix. It contains 399 images (rows) of 64x64 grayscale pixels (4096 columns) | |
# Each row represents a sample (an image) | |
# Each column represents a variable/feature (a pixel) | |
# y_df contains the label for each image (vector of size 399x1) | |
# Check | |
nrow(D) # 399 images | |
ncol(D) # 64*64 = 4096 pixels | |
# Use this function to plot images from D | |
plt_img <- function(x){ image(matrix(x, nrow = 64, byrow = T), col = grey(seq(0, 1, length = 256))) } | |
# Plot of image 1 | |
plt_img(D[1, ]) | |
#------------------------------------------------------------------------------- | |
# Average face | |
# Look for the average face. Group by label then take average of every variable (pixel) | |
AverageFace <- data.frame(D) %>% mutate(label=y_df) %>% group_by(label) %>% summarise_all(mean) | |
# Plot the average faces for labels 0, 1 and 2. | |
plt_img(as.numeric(AverageFace[1, 2:4097])) # For label 0. (1st subject) | |
plt_img(as.numeric(AverageFace[2, 2:4097])) # For label 1. (2nd subject) | |
plt_img(as.numeric(AverageFace[3, 2:4097])) # For label 2. (3rd subject) |
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