Update README.md

README.md

@@ -20,7 +20,7 @@ dataset_info:
           '10': K
           '11': L
           '12': M
-          '13': N
+          '13': 'N'
           '14': O
           '15': P
           '16': Q
@@ -31,18 +31,55 @@ dataset_info:
           '21': V
           '22': W
           '23': X
-          '24': Y
+          '24': 'Y'
           '25': Z
   splits:
   - name: train
-    num_bytes: 22453522.0
+    num_bytes: 22453522
     num_examples: 26000
   - name: test
     num_bytes: 2244964.8
     num_examples: 2600
   download_size: 8149945
   dataset_size: 24698486.8
+task_categories:
+- image-classification
+language:
+- en
+size_categories:
+- 1K<n<10K
 ---
 # Dataset Card for "letter_recognition"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+Images in this dataset was generated using the script defined below. The original dataset in CSV format and more information of the original dataset is available at [A-Z Handwritten Alphabets in .csv format](https://www.kaggle.com/datasets/sachinpatel21/az-handwritten-alphabets-in-csv-format).
+
+
+```python
+import os
+import pandas as pd
+import matplotlib.pyplot as plt
+
+CHARACTER_COUNT = 26
+
+data = pd.read_csv('./A_Z Handwritten Data.csv')
+mapping = {str(i): chr(i+65) for i in range(26)}
+
+def generate_dataset(folder, end, start=0):
+    if not os.path.exists(folder):
+        os.makedirs(folder)
+        print(f"The folder '{folder}' has been created successfully!")
+    else:
+        print(f"The folder '{folder}' already exists.")
+
+    for i in range(CHARACTER_COUNT):
+        dd = data[data['0']==i]
+        for j in range(start, end):
+            ddd = dd.iloc[j]
+            x = ddd[1:].values
+            x = x.reshape((28, 28))
+            plt.axis('off')
+            plt.imsave(f'{folder}/{mapping[str(i)]}_{j}.jpg', x, cmap='binary')
+            
+generate_dataset('./train', 1000)
+generate_dataset('./test', 1100, 1000)
+```