ashutoshsatapathy1990

# DPN-68
name: "DPN-68"
layer {
  name: "train-data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 224

ashutoshsatapathy1990

#Xception50
name: "Xception50"
layer {
  name: "train-data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 224

ashutoshsatapathy1990

# Inception V4
name: "Inception V4"
layer {
  name: "train-data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 299

ashutoshsatapathy1990

%%%%%%%%%%%%%%%%%%%%%%%%%% READ THE FOLDER PATH %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Dir = 'Directory Path';
%%%%%%%%%%%%%%%%%%%% LIST ALL IMAGES IN THE FOLDER %%%%%%%%%%%%%%%%%%%%%%%%%%%%
S = dir(fullfile(Dir, '*.jpg'));
for K = 1:numel(S)
    F = fullfile(Dir, S(K).name);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%% READ AN IMAGE %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    I = imread(F);
%%%%%%%%%%%%%%%%%%%%%%%%% RESIZE IMAGE [300 x 300] %%%%%%%%%%%%%%%%%%%%%%%%%%%%
    I = imresize(I, [300, 300]);

ashutoshsatapathy1990

%....................................................................
% // Uniform Random Noise in The Range [0, 1] Scaled by k =  0.3.   |
% // Rayleigh Noise with its [A = 0, B = 1] Scaled by k = 0.3.      |
% // Exponential Noise Scaled By 0.2 Where The Value of A = 1.      |
% // Gamma (Erlang) Noise where [A, B ] = [2, 5] and SF 'K' = 0.1.  |
% // imnoise2.m File Function Is Called Inside This Program.        |
%...................................................................|

%// Read an Image from The Given Path.
img = imread('input/img.bmp');

ashutoshsatapathy1990

%....................................................................
% // Calculate Mean and Variance of An Input Image [M x N].         |
% // Compute Local Variance of Size [M x N]  from The above Image.  |
% // Use Mean and Variance to Introduce Gaussian Noise.             |
% // Use Local Variance to Introduce Localvar Noise in The Image.   |
%...................................................................|

%// Read an Image from The Given Path
img = imread('input/img.bmp');

ashutoshsatapathy1990

%......................................................................
%                      PERFORMANCE METICES                            |
%.....................................................................|
% ENTROPY | PEAK SIGNAL TO NOISE RATIO (PSNR) | SIGNAL TO NOISE RATIO |
% MEAN ABSOLUTE ERROR (MAE) | MEAN SQUARE ERROR (MSE)| CORRELATION    |
% ROOT MEAN SQUARE ERROR (RMSE) | STRUCTURAL SIMILARITY INDEX (SSIM)  |
%       STANDARD DEVIATION (SD) | PERCENTAGE FIT ERROR (PFE)          |
%.....................................................................|

%%%%%%%%%%%%%%%%%%% START OF THE PROGRAM %%%%%%%%%%%%%%%%%%%%%%%%%

ashutoshsatapathy1990

# ResNeXt50
name: "ResNeXt50"
layer {
  name: "train-data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 224

ashutoshsatapathy1990

#ResNet50
name: "ResNet50"
layer {
  name: "train-data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 224

ashutoshsatapathy1990

# ResNet34
name: "ResNet34"
layer {
  name: "train-data"
  type: "Data"
  top: "data"
  top: "label"
  transform_param {
    mirror: true
    crop_size: 224