corrected editor bug

editor.py

@@ -4,6 +4,7 @@ import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
+import matplotlib.pyplot as plt
 
 
 class Net(nn.Module):
@@ -32,17 +33,17 @@ def transform_to_rgb(value):
 
 
 def update_screen_from_array(array, screen):
-    for x in range(array.shape[0]):
-        for y in range(array.shape[1]):
+    for y in range(array.shape[0]):
+        for x in range(array.shape[1]):
             x_transformed = x * 30
             y_transformed = y * 30 + 161
 
-            color = transform_to_rgb(array[x, y])
+            color = transform_to_rgb(array[y, x])
             pygame.draw.rect(screen, color, (x_transformed, y_transformed, 30, 30), 0)
 
 
 ########################
-HARDNESS = 0.7
+HARDNESS = 1
 ########################
 
 pygame.init()
@@ -84,12 +85,17 @@ while not stopFlag:
 
         for coord in coords:
             if not coord[0] < 0 and not coord[0] > 27 and not coord[1] < 0 and not coord[1] > 27:
-                img_array[coord[0], coord[1]] += HARDNESS
+                if img_array[coord[1], coord[0]] < 1:
+                    img_array[coord[1], coord[0]] += HARDNESS
 
     # Clear image on right mouse button press
     if pygame.mouse.get_pressed()[2] == 1:
         img_array = np.zeros((28, 28))
 
+    if pygame.mouse.get_pressed()[1] == 1:
+        plt.imshow(img_array)
+        plt.show()
+
     update_screen_from_array(img_array, screen)
     # Draw vertical lines
     for i in range(30, 28 * 30, 30):
@@ -101,7 +107,7 @@ while not stopFlag:
 
     pygame.display.flip()
     clock.tick(60)
-    np.rot90(img_array, k=1)
+
     tensor = torch.from_numpy(img_array).view(1, 28 * 28).float()
     with torch.no_grad():
         prediction = torch.argmax(net(tensor))

other_scripts/setcounter.py

@@ -1,29 +1,17 @@
 from tqdm import tqdm
 import torch
 from torchvision import transforms, datasets
+import matplotlib.pyplot as plt
 
 data = datasets.MNIST('../datasets', train=True, download=True,
                       transform=transforms.Compose([
                           transforms.ToTensor()
                       ]))
 
-loader = torch.utils.data.DataLoader(data, batch_size=15, shuffle=False)
-set = {'0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0, '6': 0, '7': 0, '8': 0, '9': 0}
+loader = torch.utils.data.DataLoader(data, batch_size=1, shuffle=False)
 
 for data in loader:
-    print(data[1].shape)
+    tensor = data[0].view([28, 28])
+    plt.imshow(tensor)
+    plt.show()
 
-for _, label in tqdm(loader):
-    set[str(label[0].item())] += 1
-
-print(set)
-
-num = 0
-for x in set:
-    num += set[x]
-print(num)
-
-for x in set:
-    set[x] /= num
-    set[x] *= 100
-print(set)