Add parquet file test

.gitattributes

@@ -3608,3 +3608,5 @@ processed_images/r31-0919.png filter=lfs diff=lfs merge=lfs -text
 processed_images/r31-1876.png filter=lfs diff=lfs merge=lfs -text
 processed_images/r32-0784.png filter=lfs diff=lfs merge=lfs -text
 handwriting/train-00000-of-00001.parquet filter=lfs diff=lfs merge=lfs -text
+train-0000.parquet filter=lfs diff=lfs merge=lfs -text
+train-0001.parquet filter=lfs diff=lfs merge=lfs -text

convert.py

@@ -1,66 +0,0 @@
-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)
-    
-    # Find all label files matching pattern
-    print("Finding label files...")
-    label_files = glob.glob("./original/test/round3?_best2019.label")
-    print(f"Found {len(label_files)} label files")
-    
-    # Parse image filenames and captions
-    data = []
-    for i, label_path in enumerate(label_files):
-        print(f"\nProcessing label file {i+1}/{len(label_files)}: {label_path}")
-        
-        # Read label file with Windows-874 encoding
-        print("Reading label file...")
-        with codecs.open(label_path, 'r', encoding='cp874') as f:
-            lines = f.readlines()
-        print(f"Found {len(lines)} entries")
-        
-        for j, line in enumerate(lines):
-            if j % 100 == 0:
-                print(f"Processing entry {j}/{len(lines)}")
-                
-            filename, caption = line.strip().split(' ', 1)
-            
-            # Get folder name from first 3 chars of filename
-            folder = filename[:3]
-            image_path = f"./original/test/{folder}/{filename}"
-            # Load and verify image exists
-            if os.path.exists(image_path):
-                try:
-                    # Load image and convert to bytes
-                    img = Image.open(image_path)
-                    img_byte_arr = io.BytesIO()
-                    img.save(img_byte_arr, format='PNG')  # Force PNG format
-                    img_bytes = {"bytes":bytearray(img_byte_arr.getvalue())}
-
-                    data.append({
-                        'image': img_bytes,  # Store as numpy array of bytes
-                        'text': caption,
-                        'label_file': os.path.basename(label_path)
-                    })
-                except Exception as e:
-                    print(f"Error processing image {image_path}: {e}")
-    print(f"\nProcessed {len(data)} total images successfully")
-    
-    # Convert to dataframe and save as parquet
-    print("Converting to dataframe...")
-    df = pd.DataFrame(data)
-    print("Saving to parquet file...")
-    df.to_parquet("train.parquet", index=False)
-    print("Dataset creation complete!")
-
-if __name__ == "__main__":
-    create_dataset()

train-0001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6f1794e3c1bd885cf620d9fcd97dd98dbe3d841b08ef9ce482d26affc0fd7c19
+size 88731703