Figure saving with proper size

Filter_Analysis/wiki/Approach.md

@@ -2,8 +2,6 @@
 
 Attacking classifier models essentially boils down to adding precisely calculated noise to the input image, thereby tricking the classifier into selecting an incorrect class. The goal is to understand the efficacy of an array of denoising algorithms as adversarial machine learning defenses.
 
-## Individual Denoising Algorithms
-
-## An Ensemble Approach
-
-## Training the Model on Filtered Data
+## Requirements
+For a given filter to be beneficial to th e
+1. The filter 

Filter_Analysis/wiki/Results.md

@@ -954,3 +954,212 @@ Bilateral Filter (strength = 7) = 1999 / 10000 = 0.1999
 
 Bilateral Filter (strength = 9) = 1444 / 10000 = 0.1444
 
+
+## Gaussian Blur 
+====== EPSILON: 0.0 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 9920 / 10000 = 0.992
+
+Gaussian Blur (strength = 1) = 9920 / 10000 = 0.992
+
+Gaussian Blur (strength = 3) = 9879 / 10000 = 0.9879
+
+Gaussian Blur (strength = 5) = 9682 / 10000 = 0.9682
+
+Gaussian Blur (strength = 7) = 7731 / 10000 = 0.7731
+
+Gaussian Blur (strength = 9) = 5250 / 10000 = 0.525
+
+====== EPSILON: 0.025 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 9796 / 10000 = 0.9796
+
+Gaussian Blur (strength = 1) = 9796 / 10000 = 0.9796
+
+Gaussian Blur (strength = 3) = 9801 / 10000 = 0.9801
+
+Gaussian Blur (strength = 5) = 9512 / 10000 = 0.9512
+
+Gaussian Blur (strength = 7) = 7381 / 10000 = 0.7381
+
+Gaussian Blur (strength = 9) = 4862 / 10000 = 0.4862
+
+====== EPSILON: 0.05 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 9600 / 10000 = 0.96
+
+Gaussian Blur (strength = 1) = 9600 / 10000 = 0.96
+
+Gaussian Blur (strength = 3) = 9674 / 10000 = 0.9674
+
+Gaussian Blur (strength = 5) = 9271 / 10000 = 0.9271
+
+Gaussian Blur (strength = 7) = 6922 / 10000 = 0.6922
+
+Gaussian Blur (strength = 9) = 4446 / 10000 = 0.4446
+
+====== EPSILON: 0.07500000000000001 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 9260 / 10000 = 0.926
+
+Gaussian Blur (strength = 1) = 9260 / 10000 = 0.926
+
+Gaussian Blur (strength = 3) = 9460 / 10000 = 0.946
+
+Gaussian Blur (strength = 5) = 8939 / 10000 = 0.8939
+
+Gaussian Blur (strength = 7) = 6427 / 10000 = 0.6427
+
+Gaussian Blur (strength = 9) = 3989 / 10000 = 0.3989
+
+====== EPSILON: 0.1 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 8753 / 10000 = 0.8753
+
+Gaussian Blur (strength = 1) = 8753 / 10000 = 0.8753
+
+Gaussian Blur (strength = 3) = 9133 / 10000 = 0.9133
+
+Gaussian Blur (strength = 5) = 8516 / 10000 = 0.8516
+
+Gaussian Blur (strength = 7) = 5881 / 10000 = 0.5881
+
+Gaussian Blur (strength = 9) = 3603 / 10000 = 0.3603
+
+====== EPSILON: 0.125 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 8104 / 10000 = 0.8104
+
+Gaussian Blur (strength = 1) = 8104 / 10000 = 0.8104
+
+Gaussian Blur (strength = 3) = 8690 / 10000 = 0.869
+
+Gaussian Blur (strength = 5) = 7989 / 10000 = 0.7989
+
+Gaussian Blur (strength = 7) = 5278 / 10000 = 0.5278
+
+Gaussian Blur (strength = 9) = 3263 / 10000 = 0.3263
+
+====== EPSILON: 0.15000000000000002 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 7229 / 10000 = 0.7229
+
+Gaussian Blur (strength = 1) = 7229 / 10000 = 0.7229
+
+Gaussian Blur (strength = 3) = 8135 / 10000 = 0.8135
+
+Gaussian Blur (strength = 5) = 7415 / 10000 = 0.7415
+
+Gaussian Blur (strength = 7) = 4710 / 10000 = 0.471
+
+Gaussian Blur (strength = 9) = 2968 / 10000 = 0.2968
+
+====== EPSILON: 0.17500000000000002 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 6207 / 10000 = 0.6207
+
+Gaussian Blur (strength = 1) = 6207 / 10000 = 0.6207
+
+Gaussian Blur (strength = 3) = 7456 / 10000 = 0.7456
+
+Gaussian Blur (strength = 5) = 6741 / 10000 = 0.6741
+
+Gaussian Blur (strength = 7) = 4224 / 10000 = 0.4224
+
+Gaussian Blur (strength = 9) = 2683 / 10000 = 0.2683
+
+====== EPSILON: 0.2 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 5008 / 10000 = 0.5008
+
+Gaussian Blur (strength = 1) = 5008 / 10000 = 0.5008
+
+Gaussian Blur (strength = 3) = 6636 / 10000 = 0.6636
+
+Gaussian Blur (strength = 5) = 5983 / 10000 = 0.5983
+
+Gaussian Blur (strength = 7) = 3755 / 10000 = 0.3755
+
+Gaussian Blur (strength = 9) = 2453 / 10000 = 0.2453
+
+====== EPSILON: 0.225 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 3894 / 10000 = 0.3894
+
+Gaussian Blur (strength = 1) = 3894 / 10000 = 0.3894
+
+Gaussian Blur (strength = 3) = 5821 / 10000 = 0.5821
+
+Gaussian Blur (strength = 5) = 5243 / 10000 = 0.5243
+
+Gaussian Blur (strength = 7) = 3359 / 10000 = 0.3359
+
+Gaussian Blur (strength = 9) = 2269 / 10000 = 0.2269
+
+====== EPSILON: 0.25 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 2922 / 10000 = 0.2922
+
+Gaussian Blur (strength = 1) = 2922 / 10000 = 0.2922
+
+Gaussian Blur (strength = 3) = 5050 / 10000 = 0.505
+
+Gaussian Blur (strength = 5) = 4591 / 10000 = 0.4591
+
+Gaussian Blur (strength = 7) = 3034 / 10000 = 0.3034
+
+Gaussian Blur (strength = 9) = 2112 / 10000 = 0.2112
+
+====== EPSILON: 0.275 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 2149 / 10000 = 0.2149
+
+Gaussian Blur (strength = 1) = 2149 / 10000 = 0.2149
+
+Gaussian Blur (strength = 3) = 4290 / 10000 = 0.429
+
+Gaussian Blur (strength = 5) = 3998 / 10000 = 0.3998
+
+Gaussian Blur (strength = 7) = 2743 / 10000 = 0.2743
+
+Gaussian Blur (strength = 9) = 1983 / 10000 = 0.1983
+
+====== EPSILON: 0.30000000000000004 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 1599 / 10000 = 0.1599
+
+Gaussian Blur (strength = 1) = 1599 / 10000 = 0.1599
+
+Gaussian Blur (strength = 3) = 3648 / 10000 = 0.3648
+
+Gaussian Blur (strength = 5) = 3481 / 10000 = 0.3481
+
+Gaussian Blur (strength = 7) = 2493 / 10000 = 0.2493
+
+Gaussian Blur (strength = 9) = 1884 / 10000 = 0.1884