import pyarrow.parquet as pq
import pyarrow as pa
from PIL import Image
import io
import pandas as pd

def is_image_corrupt(image_dict):
    try:
        image_bytes = image_dict['bytes']  
        image = Image.open(io.BytesIO(image_bytes))
        image.verify()
        return False
    except (IOError, SyntaxError, KeyError) as e:
        return True

def process_parquet_file(file_path, output_file_path):
    table = pq.read_table(file_path)

    df = table.to_pandas()

    image_column = 'image'

    clean_indices = []
    corrupt_indices = []

    for i, image_dict in enumerate(df[image_column]):
        if is_image_corrupt(image_dict):
            corrupt_indices.append(i)
        else:
            clean_indices.append(i)

    clean_df = df.iloc[clean_indices]

    clean_table = pa.Table.from_pandas(clean_df)

    pq.write_table(clean_table, output_file_path)

    print(f"File {file_path}: {len(corrupt_indices)} corrupt images were removed.") 

for i in range(5):
    input_file_path = f'data/train-0000{i}-of-00005.parquet'
    output_file_path = f'data/train-0000{i}-of-00005.parquet'
    process_parquet_file(input_file_path, output_file_path)