delete corrupt images. add test.py for testing

data/train-00000-of-00005.parquet

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 version https://git-lfs.github.com/spec/v1
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+oid sha256:39c1105fb7c66746222256a1322f63599c5d044f4eaaef6e622d1092f7858b8f
+size 550878063

data/train-00001-of-00005.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 835997138
+oid sha256:33794a73660868a2c713490feb7f5d82750ee8a84df74733666bff1df5fdf4f3
+size 835192352

data/train-00002-of-00005.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 1109849995
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+size 1110002638

data/train-00003-of-00005.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+size 2688826273

data/train-00004-of-00005.parquet

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 version https://git-lfs.github.com/spec/v1
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+size 444671011

test.py

@@ -0,0 +1,43 @@
+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)