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()