From 3f0e8c31bcf4eb9c1e9346a4275d535f2101b65c Mon Sep 17 00:00:00 2001
From: HombreLaser <sebastian-440@live.com>
Date: Mon, 23 Oct 2023 17:53:59 -0600
Subject: Improve dataset class

---
 dataset.py        | 33 +++++++++++++++++++++------------
 neural_network.py |  6 +-----
 2 files changed, 22 insertions(+), 17 deletions(-)

diff --git a/dataset.py b/dataset.py
index 78d4691..e81e7ec 100644
--- a/dataset.py
+++ b/dataset.py
@@ -1,26 +1,35 @@
 import numpy as np
 from PIL import Image
 from pathlib import Path
+from alphabet import CYRILLIC_ALPHABET
+import random
 
 """Class to interface the training and testing data."""
 
+DATASET_SIZE=15480
 
 class Dataset:
     def __init__(self) -> None:
         self.data_path = Path('./data')
+        self.already_used = set()
 
-    """Convert the dataset to a 2 dimension array."""
-    def data(self):
-        for dir in self.data_path.iterdir():
-            if not dir.is_dir():
-                continue
+    """
+    Yield a random sample of the dataset with each call.
+    """
+    def data(self, batch_size=DATASET_SIZE):
+        for i in range(batch_size):
+            random_letter = random.choice(CYRILLIC_ALPHABET)
+            images = list((self.data_path/random_letter).glob('*.png'))
+            file_to_yield = random.choice(images).name
 
-            for file in dir.glob('*.png'):
-                image = Image.open(str(file))
-                image_array = self._img_to_array(image)
-                # Return the image's pixel values as an array alongside
-                # the character that it represents.
-                yield (dir.name, image_array)
+            if file_to_yield in self.already_used:
+                continue
+            
+            self.already_used.add(file_to_yield)
+            image = Image.open(str(self.data_path/random_letter/file_to_yield))
+            image_array = self._img_to_array(image)
+            
+            yield (random_letter, image_array)
 
     """
     Get an image from the dataset.
@@ -37,7 +46,7 @@ class Dataset:
     Grab the image in RGB, add a white background, and return it as
     a black and white array.
     """
-    def _img_to_array(self, image: Image):
+    def _img_to_array(self, image):
         fill_color = (255, 255, 255)  # White background.
         background = Image.new(image.mode[:-1], image.size, fill_color)
         background.paste(image, image.split()[-1])
diff --git a/neural_network.py b/neural_network.py
index 6c44ddb..2163173 100644
--- a/neural_network.py
+++ b/neural_network.py
@@ -2,11 +2,7 @@ import numpy as np
 import math
 from scipy.special import expit
 from secrets import token_hex
-
-CYRILLIC_ALPHABET = ['I', 'А', 'Б', 'В', 'Г', 'Д', 'Е', 'Ë', 'Ж', 'З',
-                     'И', 'Й', 'К', 'Л', 'М', 'Н', 'О', 'П', 'Р', 'С',
-                     'Т', 'У', 'Ф', 'Х', 'Ц', 'Ч', 'Ш', 'Щ', 'Ъ', 'Ы',
-                     'Ь', 'Э', 'Ю', 'Я']
+from alphabet import CYRILLIC_ALPHABET
 
 """The neural network class."""
 
-- 
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