fix: Image Feature in Datasets Library Fails to Handle bytearray Objects from Spark DataFrames (#7517)

src/datasets/features/audio.py

@@ -74,7 +74,7 @@ class Audio:
     def __call__(self):
         return self.pa_type
 
-    def encode_example(self, value: Union[str, bytes, dict]) -> dict:
+    def encode_example(self, value: Union[str, bytes, bytearray, dict]) -> dict:
         """Encode example into a format for Arrow.
 
         Args:
@@ -90,7 +90,7 @@ def encode_example(self, value: Union[str, bytes, dict]) -> dict:
             raise ImportError("To support encoding audio data, please install 'soundfile'.") from err
         if isinstance(value, str):
             return {"bytes": None, "path": value}
-        elif isinstance(value, bytes):
+        elif isinstance(value, (bytes, bytearray)):
             return {"bytes": value, "path": None}
         elif "array" in value:
             # convert the audio array to wav bytes

src/datasets/features/image.py

@@ -91,7 +91,7 @@ class Image:
     def __call__(self):
         return self.pa_type
 
-    def encode_example(self, value: Union[str, bytes, dict, np.ndarray, "PIL.Image.Image"]) -> dict:
+    def encode_example(self, value: Union[str, bytes, bytearray, dict, np.ndarray, "PIL.Image.Image"]) -> dict:
         """Encode example into a format for Arrow.
 
         Args:
@@ -111,7 +111,7 @@ def encode_example(self, value: Union[str, bytes, dict, np.ndarray, "PIL.Image.I
 
         if isinstance(value, str):
             return {"path": value, "bytes": None}
-        elif isinstance(value, bytes):
+        elif isinstance(value, (bytes, bytearray)):
             return {"path": None, "bytes": value}
         elif isinstance(value, np.ndarray):
             # convert the image array to PNG/TIFF bytes

src/datasets/features/pdf.py

@@ -75,7 +75,7 @@ class Pdf:
     def __call__(self):
         return self.pa_type
 
-    def encode_example(self, value: Union[str, bytes, dict, "pdfplumber.pdf.PDF"]) -> dict:
+    def encode_example(self, value: Union[str, bytes, bytearray, dict, "pdfplumber.pdf.PDF"]) -> dict:
         """Encode example into a format for Arrow.
 
         Args:
@@ -92,7 +92,7 @@ def encode_example(self, value: Union[str, bytes, dict, "pdfplumber.pdf.PDF"]) -
 
         if isinstance(value, str):
             return {"path": value, "bytes": None}
-        elif isinstance(value, bytes):
+        elif isinstance(value, (bytes, bytearray)):
             return {"path": None, "bytes": value}
         elif pdfplumber is not None and isinstance(value, pdfplumber.pdf.PDF):
             # convert the pdfplumber.pdf.PDF to bytes

src/datasets/features/video.py

@@ -71,7 +71,7 @@ class Video:
     def __call__(self):
         return self.pa_type
 
-    def encode_example(self, value: Union[str, bytes, Example, np.ndarray, "VideoReader"]) -> Example:
+    def encode_example(self, value: Union[str, bytes, bytearray, Example, np.ndarray, "VideoReader"]) -> Example:
         """Encode example into a format for Arrow.
 
         Args:
@@ -92,7 +92,7 @@ def encode_example(self, value: Union[str, bytes, Example, np.ndarray, "VideoRea
 
         if isinstance(value, str):
             return {"path": value, "bytes": None}
-        elif isinstance(value, bytes):
+        elif isinstance(value, (bytes, bytearray)):
             return {"path": None, "bytes": value}
         elif isinstance(value, np.ndarray):
             # convert the video array to bytes

src/datasets/keyhash.py

@@ -35,14 +35,14 @@
 from huggingface_hub.utils import insecure_hashlib
 
 
-def _as_bytes(hash_data: Union[str, int, bytes]) -> bytes:
+def _as_bytes(hash_data: Union[str, int, bytes, bytearray]) -> bytes:
     """
     Returns the input hash_data in its bytes form
 
     Args:
     hash_data: the hash salt/key to be converted to bytes
     """
-    if isinstance(hash_data, bytes):
+    if isinstance(hash_data, (bytes, bytearray)):
         # Data already in bytes, returns as it as
         return hash_data
     elif isinstance(hash_data, str):

tests/packaged_modules/test_spark.py

@@ -1,8 +1,10 @@
 from unittest.mock import patch
 
+import numpy as np
 import pyspark
 import pytest
 
+from datasets import Features, Image, IterableDataset
 from datasets.builder import InvalidConfigName
 from datasets.data_files import DataFilesList
 from datasets.packaged_modules.spark.spark import (
@@ -131,3 +133,38 @@ def test_repartition_df_if_needed_max_num_df_rows():
     spark_builder._repartition_df_if_needed(max_shard_size=1)
     # The new number of partitions should not be greater than the number of rows.
     assert spark_builder.df.rdd.getNumPartitions() == 100
+
+
+@require_not_windows
+@require_dill_gt_0_3_2
+def test_iterable_image_features():
+    spark = pyspark.sql.SparkSession.builder.master("local[*]").appName("pyspark").getOrCreate()
+    img_bytes = np.zeros((10, 10, 3), dtype=np.uint8).tobytes()
+    data = [(img_bytes,)]
+    df = spark.createDataFrame(data, "image: binary")
+    features = Features({"image": Image(decode=False)})
+    dset = IterableDataset.from_spark(df, features=features)
+    item = next(iter(dset))
+    assert item.keys() == {"image"}
+    assert item == {"image": {"path": None, "bytes": img_bytes}}
+
+
+@require_not_windows
+@require_dill_gt_0_3_2
+def test_iterable_image_features_decode():
+    from io import BytesIO
+
+    import PIL.Image
+
+    spark = pyspark.sql.SparkSession.builder.master("local[*]").appName("pyspark").getOrCreate()
+    img = PIL.Image.fromarray(np.zeros((10, 10, 3), dtype=np.uint8), "RGB")
+    buffer = BytesIO()
+    img.save(buffer, format="PNG")
+    img_bytes = bytes(buffer.getvalue())
+    data = [(img_bytes,)]
+    df = spark.createDataFrame(data, "image: binary")
+    features = Features({"image": Image()})
+    dset = IterableDataset.from_spark(df, features=features)
+    item = next(iter(dset))
+    assert item.keys() == {"image"}
+    assert isinstance(item["image"], PIL.Image.Image)