Add convert_wang.py

convert_wang.py

@@ -0,0 +1,80 @@
+import os
+import pandas as pd
+from PIL import Image
+import codecs
+import numpy as np
+import glob
+import io
+
+def create_dataset():
+    print("Starting dataset creation...")
+    
+    # Create output directory for images
+    os.makedirs("processed_images", exist_ok=True)
+    
+    # Process wang dataset
+    print("\nProcessing wang dataset...")
+    wang_csv = "./original/wang/free_dataset.csv"
+    if os.path.exists(wang_csv):
+        df_wang = pd.read_csv(wang_csv, header=None)
+        print(f"Found {len(df_wang)} entries in wang dataset")
+        
+        data = []
+        file_count = 1
+        
+        for i, row in df_wang.iterrows():
+            if i % 100 == 0:
+                print(f"Processing wang entry {i+1}/{len(df_wang)}")
+                
+            _, text, _, filename = row
+            image_path = os.path.join("/Users/kobkrit/git/iapp-dataset/thai_handwriting_dataset/original/wang/free_dataset", filename)
+            
+            if os.path.exists(image_path):
+                try:
+                    img = Image.open(image_path)
+                    
+                    # Convert image to PNG format
+                    if img.format != 'PNG':
+                        # Create a new RGB image with white background
+                        png_img = Image.new('RGB', img.size, (255, 255, 255))
+                        # Paste the original image onto the white background
+                        png_img.paste(img, mask=img if img.mode=='RGBA' else None)
+                        img = png_img
+                        
+                    img_byte_arr = io.BytesIO()
+                    img.save(img_byte_arr, format='PNG')
+                    img_bytes = {"bytes":bytearray(img_byte_arr.getvalue())}
+                    
+                    data.append({
+                        'image': img_bytes,
+                        'text': text,
+                        'label_file': filename
+                    })
+                    
+                    # print(data)
+                    
+                    # Save every 100 rows
+                    if len(data) >= 100:
+                        print(f"\nSaving batch {file_count} with {len(data)} images")
+                        print("Converting to dataframe...")
+                        df = pd.DataFrame(data)
+                        print(f"Saving to parquet file train-{file_count:04d}.parquet...")
+                        df.to_parquet(f"train-{file_count:04d}.parquet", index=False)
+                        data = [] # Clear the data list
+                        file_count += 1
+                        
+                except Exception as e:
+                    print(f"Error processing wang image {image_path}: {e}")
+        
+        # Save any remaining data
+        if len(data) > 0:
+            print(f"\nSaving final batch {file_count} with {len(data)} images")
+            print("Converting to dataframe...")
+            df = pd.DataFrame(data)
+            print(f"Saving to parquet file train-{file_count:04d}.parquet...")
+            df.to_parquet(f"train-{file_count:04d}.parquet", index=False)
+            
+    print("Dataset creation complete!")
+
+if __name__ == "__main__":
+    create_dataset()