Decreased epsilon step size to 0.025

Filter_Analysis/fgsm.py

@@ -10,7 +10,9 @@ import cv2
 from mnist import Net
 from pykuwahara import kuwahara
 
-epsilons = np.arange(0.0,0.35,0.05)
+MAX_EPSILON = 0.3
+EPSILON_STEP = 0.025
+epsilons = np.arange(0.0, MAX_EPSILON+EPSILON_STEP, EPSILON_STEP)
 pretrained_model = "mnist_cnn_unfiltered.pt"
 use_cuda=False
 
@@ -135,7 +137,7 @@ def test(model, device, test_loader, epsilon):
         snap_color_pred = output_snap_color.max(1, keepdim=True)[1]
         one_bit_pred = output_one_bit.max(1, keepdim=True)[1]
         predictions = [unfiltered_pred.item(), kuwahara_pred.item(), bilateral_pred.item(), gaussian_blur_pred.item(), random_noise_pred.item(), snap_color_pred.item(), one_bit_pred.item()]
-        plurality_pred = stats.mode(predictions)[0]
+        plurality_pred = stats.mode(predictions, keepdims=True)[0]
 
         # Count up correct classifications for each case
         if orig_pred.item() == target.item():
@@ -248,7 +250,7 @@ def filtered(data, batch_size=64, filter="kuwahara"):
                 filtered_images[i] -= min_value
     elif filter == "snap_color":
         for i in range(batch_size):
-            filtered_images[i] = (images[i]*4).astype(int).astype(float) / 4
+            filtered_images[i] = (images[i]*4).astype(int).astype(float)/4
 
     # Modify the data with the filtered image
     filtered_images = filtered_images.transpose(0,3,1,2)

Filter_Analysis/wiki/Results.md

@@ -80,6 +80,26 @@ Snapped Color Accuracy = 9913 / 10000 = 0.9913
 
 Plurality Vote Accuracy = 9889 / 10000 = 0.9889
 
+====== EPSILON: 0.025 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 9796 / 10000 = 0.9796
+
+Kuwahara Filter Accuracy = 8909 / 10000 = 0.8909
+
+Bilateral Filter Accuracy = 9184 / 10000 = 0.9184
+
+Gaussian Blur Accuracy = 9512 / 10000 = 0.9512
+
+Random Noise Accuracy = 9786 / 10000 = 0.9786
+
+Snapped Color Accuracy = 9823 / 10000 = 0.9823
+
+1 Bit Accuracy = 8644 / 10000 = 0.8644
+
+Plurality Vote Accuracy = 9746 / 10000 = 0.9746
+
 ====== EPSILON: 0.05 ======
 
 Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
@@ -98,7 +118,27 @@ Snapped Color Accuracy = 9781 / 10000 = 0.9781
 
 1 Bit Accuracy = 8409 / 10000 = 0.8409
 
-Plurality Vote Accuracy = 9600 / 10000 = 0.96
+Plurality Vote Accuracy = 9602 / 10000 = 0.9602
+
+====== EPSILON: 0.07500000000000001 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 9260 / 10000 = 0.926
+
+Kuwahara Filter Accuracy = 8447 / 10000 = 0.8447
+
+Bilateral Filter Accuracy = 8533 / 10000 = 0.8533
+
+Gaussian Blur Accuracy = 8939 / 10000 = 0.8939
+
+Random Noise Accuracy = 9221 / 10000 = 0.9221
+
+Snapped Color Accuracy = 9228 / 10000 = 0.9228
+
+1 Bit Accuracy = 8174 / 10000 = 0.8174
+
+Plurality Vote Accuracy = 9235 / 10000 = 0.9235
 
 ====== EPSILON: 0.1 ======
 
@@ -112,13 +152,33 @@ Bilateral Filter Accuracy = 8133 / 10000 = 0.8133
 
 Gaussian Blur Accuracy = 8516 / 10000 = 0.8516
 
-Random Noise Accuracy = 8696 / 10000 = 0.8696
+Random Noise Accuracy = 8702 / 10000 = 0.8702
 
 Snapped Color Accuracy = 8818 / 10000 = 0.8818
 
 1 Bit Accuracy = 7919 / 10000 = 0.7919
 
-Plurality Vote Accuracy = 8799 / 10000 = 0.8799
+Plurality Vote Accuracy = 8802 / 10000 = 0.8802
+
+====== EPSILON: 0.125 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 8104 / 10000 = 0.8104
+
+Kuwahara Filter Accuracy = 7751 / 10000 = 0.7751
+
+Bilateral Filter Accuracy = 7656 / 10000 = 0.7656
+
+Gaussian Blur Accuracy = 7989 / 10000 = 0.7989
+
+Random Noise Accuracy = 8022 / 10000 = 0.8022
+
+Snapped Color Accuracy = 8621 / 10000 = 0.8621
+
+1 Bit Accuracy = 7646 / 10000 = 0.7646
+
+Plurality Vote Accuracy = 8396 / 10000 = 0.8396
 
 ====== EPSILON: 0.15000000000000002 ======
 
@@ -132,7 +192,7 @@ Bilateral Filter Accuracy = 7098 / 10000 = 0.7098
 
 Gaussian Blur Accuracy = 7415 / 10000 = 0.7415
 
-Random Noise Accuracy = 7119 / 10000 = 0.7119
+Random Noise Accuracy = 7129 / 10000 = 0.7129
 
 Snapped Color Accuracy = 8408 / 10000 = 0.8408
 
@@ -140,6 +200,26 @@ Snapped Color Accuracy = 8408 / 10000 = 0.8408
 
 Plurality Vote Accuracy = 7879 / 10000 = 0.7879
 
+====== EPSILON: 0.17500000000000002 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 6207 / 10000 = 0.6207
+
+Kuwahara Filter Accuracy = 6816 / 10000 = 0.6816
+
+Bilateral Filter Accuracy = 6410 / 10000 = 0.641
+
+Gaussian Blur Accuracy = 6741 / 10000 = 0.6741
+
+Random Noise Accuracy = 6096 / 10000 = 0.6096
+
+Snapped Color Accuracy = 7794 / 10000 = 0.7794
+
+1 Bit Accuracy = 7085 / 10000 = 0.7085
+
+Plurality Vote Accuracy = 7176 / 10000 = 0.7176
+
 ====== EPSILON: 0.2 ======
 
 Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
@@ -152,13 +232,33 @@ Bilateral Filter Accuracy = 5683 / 10000 = 0.5683
 
 Gaussian Blur Accuracy = 5983 / 10000 = 0.5983
 
-Random Noise Accuracy = 4933 / 10000 = 0.4933
+Random Noise Accuracy = 4927 / 10000 = 0.4927
 
 Snapped Color Accuracy = 7496 / 10000 = 0.7496
 
 1 Bit Accuracy = 6794 / 10000 = 0.6794
 
-Plurality Vote Accuracy = 6467 / 10000 = 0.6467
+Plurality Vote Accuracy = 6459 / 10000 = 0.6459
+
+====== EPSILON: 0.225 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 3894 / 10000 = 0.3894
+
+Kuwahara Filter Accuracy = 5773 / 10000 = 0.5773
+
+Bilateral Filter Accuracy = 5003 / 10000 = 0.5003
+
+Gaussian Blur Accuracy = 5243 / 10000 = 0.5243
+
+Random Noise Accuracy = 3828 / 10000 = 0.3828
+
+Snapped Color Accuracy = 5289 / 10000 = 0.5289
+
+1 Bit Accuracy = 6512 / 10000 = 0.6512
+
+Plurality Vote Accuracy = 5421 / 10000 = 0.5421
 
 ====== EPSILON: 0.25 ======
 
@@ -172,13 +272,33 @@ Bilateral Filter Accuracy = 4381 / 10000 = 0.4381
 
 Gaussian Blur Accuracy = 4591 / 10000 = 0.4591
 
-Random Noise Accuracy = 2876 / 10000 = 0.2876
+Random Noise Accuracy = 2855 / 10000 = 0.2855
 
 Snapped Color Accuracy = 4301 / 10000 = 0.4301
 
 1 Bit Accuracy = 6233 / 10000 = 0.6233
 
-Plurality Vote Accuracy = 4721 / 10000 = 0.4721
+Plurality Vote Accuracy = 4716 / 10000 = 0.4716
+
+====== EPSILON: 0.275 ======
+
+Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
+
+Unfiltered Accuracy = 2149 / 10000 = 0.2149
+
+Kuwahara Filter Accuracy = 4594 / 10000 = 0.4594
+
+Bilateral Filter Accuracy = 3836 / 10000 = 0.3836
+
+Gaussian Blur Accuracy = 3998 / 10000 = 0.3998
+
+Random Noise Accuracy = 2101 / 10000 = 0.2101
+
+Snapped Color Accuracy = 3992 / 10000 = 0.3992
+
+1 Bit Accuracy = 5842 / 10000 = 0.5842
+
+Plurality Vote Accuracy = 4110 / 10000 = 0.411
 
 ====== EPSILON: 0.30000000000000004 ======
 
@@ -192,10 +312,10 @@ Bilateral Filter Accuracy = 3364 / 10000 = 0.3364
 
 Gaussian Blur Accuracy = 3481 / 10000 = 0.3481
 
-Random Noise Accuracy = 1560 / 10000 = 0.156
+Random Noise Accuracy = 1544 / 10000 = 0.1544
 
 Snapped Color Accuracy = 2091 / 10000 = 0.2091
 
 1 Bit Accuracy = 5462 / 10000 = 0.5462
 
-Plurality Vote Accuracy = 3312 / 10000 = 0.3312
+Plurality Vote Accuracy = 3287 / 10000 = 0.3287