diff --git a/tensorflow_datasets/image_classification/__init__.py b/tensorflow_datasets/image_classification/__init__.py
index 59df59b7bd8..012b7b8796e 100644
--- a/tensorflow_datasets/image_classification/__init__.py
+++ b/tensorflow_datasets/image_classification/__init__.py
@@ -96,3 +96,4 @@
from tensorflow_datasets.image_classification.svhn import SvhnCropped
from tensorflow_datasets.image_classification.uc_merced import UcMerced
from tensorflow_datasets.image_classification.visual_domain_decathlon import VisualDomainDecathlon
+from tensorflow_datasets.image_classification.spots10 import spots10
\ No newline at end of file
diff --git a/tensorflow_datasets/image_classification/spots10.py b/tensorflow_datasets/image_classification/spots10.py
new file mode 100644
index 00000000000..ebdc7f9bde6
--- /dev/null
+++ b/tensorflow_datasets/image_classification/spots10.py
@@ -0,0 +1,180 @@
+# coding=utf-8
+# Copyright 2024 The TensorFlow Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""spots10"""
+
+import os
+
+import numpy as np
+from six.moves import urllib
+from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow as tf
+import tensorflow_datasets.public_api as tfds
+
+# spots10 constants
+_spots10_URL = "https://github.com/Amotica/spots-10/raw/refs/heads/main/dataset/"
+_spots10_TRAIN_DATA_FILENAME = "train-images-idx3-ubyte.gz"
+_spots10_TRAIN_LABELS_FILENAME = "train-labels-idx1-ubyte.gz"
+_spots10_TEST_DATA_FILENAME = "test-images-idx3-ubyte.gz"
+_spots10_TEST_LABELS_FILENAME = "test-labels-idx1-ubyte.gz"
+_spots10_IMAGE_SIZE = 32
+spots10_IMAGE_SHAPE = (_spots10_IMAGE_SIZE, _spots10_IMAGE_SIZE, 1)
+spots10_NUM_CLASSES = 10
+_TRAIN_EXAMPLES = 40000
+_TEST_EXAMPLES = 10000
+
+_spots10_CITATION = """\
+@article{atanbori2024spots,
+ title={spots-10: Animal Pattern Benchmark Dataset for Machine Learning Algorithms},
+ author={Atanbori, John},
+ journal={arXiv preprint arXiv:2410.21044},
+ year={2024}
+}
+"""
+
+class spots10(tfds.core.GeneratorBasedBuilder):
+ """spots10."""
+
+ URL = _spots10_URL
+
+ VERSION = tfds.core.Version("1.0.0")
+
+ NAME = "spots10"
+
+ def _info(self):
+ return tfds.core.DatasetInfo(
+ builder=self,
+ description="spots10 dataset consisting of grayscale images featuring patterns from various animal species.",
+ features=tfds.features.FeaturesDict({
+ "image": tfds.features.Image(shape=spots10_IMAGE_SHAPE),
+ "label": tfds.features.ClassLabel(num_classes=spots10_NUM_CLASSES),
+ }),
+ supervised_keys=("image", "label"),
+ homepage="https://github.com/Amotica/spots-10",
+ citation=_spots10_CITATION,
+ )
+
+ def _split_generators(self, dl_manager):
+ """Returns SplitGenerators."""
+ # Download the full spots10 Database
+ filenames = {
+ "train_data": _spots10_TRAIN_DATA_FILENAME,
+ "train_labels": _spots10_TRAIN_LABELS_FILENAME,
+ "test_data": _spots10_TEST_DATA_FILENAME,
+ "test_labels": _spots10_TEST_LABELS_FILENAME,
+ }
+ spots10_files = dl_manager.download_and_extract(
+ {k: urllib.parse.urljoin(self.URL, v) for k, v in filenames.items()}
+ )
+
+ # spots10 provides TRAIN and TEST splits, not a VALIDATION split, so we only
+ # write the TRAIN and TEST splits to disk.
+ return [
+ tfds.core.SplitGenerator(
+ name=tfds.Split.TRAIN,
+ gen_kwargs=dict(
+ num_examples=_TRAIN_EXAMPLES,
+ data_path=spots10_files["train_data"],
+ label_path=spots10_files["train_labels"],
+ ),
+ ),
+ tfds.core.SplitGenerator(
+ name=tfds.Split.TEST,
+ gen_kwargs=dict(
+ num_examples=_TEST_EXAMPLES,
+ data_path=spots10_files["test_data"],
+ label_path=spots10_files["test_labels"],
+ ),
+ ),
+ ]
+
+ def _generate_examples(self, num_examples, data_path, label_path):
+ """Generate spots10 examples as dicts.
+
+ Args:
+ num_examples (int): The number of example.
+ data_path (str): Path to the data files
+ label_path (str): Path to the labels
+
+ Yields:
+ Generator yielding the next examples
+ """
+ images = _extract_spots10_images(data_path, num_examples)
+ labels = _extract_spots10_labels(label_path, num_examples)
+ data = list(zip(images, labels))
+
+ # Using index as key since data is always loaded in same order.
+ for index, (image, label) in enumerate(data):
+ record = {"image": image, "label": label}
+ yield index, record
+
+
+def _extract_spots10_images(image_filepath, num_images):
+ with tf.io.gfile.GFile(image_filepath, "rb") as f:
+ f.read(16) # header
+ buf = f.read(_spots10_IMAGE_SIZE * _spots10_IMAGE_SIZE * num_images)
+ data = np.frombuffer(
+ buf,
+ dtype=np.uint8,
+ ).reshape(num_images, _spots10_IMAGE_SIZE, _spots10_IMAGE_SIZE, 1)
+ return data
+
+
+def _extract_spots10_labels(labels_filepath, num_labels):
+ with tf.io.gfile.GFile(labels_filepath, "rb") as f:
+ f.read(8) # header
+ buf = f.read(num_labels)
+ labels = np.frombuffer(buf, dtype=np.uint8).astype(np.int64)
+ return labels
+
+'''
+def main():
+ print("Loading spots10 dataset...")
+
+ # Load the spots10 dataset
+ (train_data, test_data), dataset_info = tfds.load(
+ 'spots10',
+ split=['train', 'test'],
+ with_info=True,
+ as_supervised=True
+ )
+
+ print("Dataset loaded successfully!")
+ print(f"Number of training examples: {len(list(train_data))}")
+ print(f"Number of test examples: {len(list(test_data))}")
+
+ # Display dataset information
+ print("Dataset Info:")
+ print(dataset_info)
+
+ # Example of displaying a few images
+ import matplotlib.pyplot as plt
+
+ def show_images(dataset, title, num_images=5):
+ plt.figure(figsize=(10, 5))
+ for i, (image, label) in enumerate(dataset.take(num_images)):
+ plt.subplot(1, num_images, i + 1)
+ plt.imshow(image.numpy().squeeze(), cmap='gray')
+ plt.title(f"Label: {label.numpy()}")
+ plt.axis('off')
+ plt.suptitle(title)
+ plt.show()
+
+ show_images(train_data, "Training Data Samples")
+ show_images(test_data, "Test Data Samples")
+
+
+if __name__ == "__main__":
+ main()
+'''
\ No newline at end of file
diff --git a/tensorflow_datasets/image_classification/spots10_test.py b/tensorflow_datasets/image_classification/spots10_test.py
new file mode 100644
index 00000000000..1bd8eb9f935
--- /dev/null
+++ b/tensorflow_datasets/image_classification/spots10_test.py
@@ -0,0 +1,53 @@
+# coding=utf-8
+# Copyright 2024 The TensorFlow Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Tests for spots10 dataset module."""
+
+from tensorflow_datasets import testing
+from tensorflow_datasets.image_classification import spots10
+import pytest
+
+# testing/spots10.py generates fake input data
+
+spots10._TRAIN_EXAMPLES = 2 # pylint: disable=protected-access
+spots10._TEST_EXAMPLES = 2 # pylint: disable=protected-access
+
+
+class spots10Test(testing.DatasetBuilderTestCase):
+ DATASET_CLASS = spots10
+ SPLITS = {
+ "train": 2,
+ "test": 2,
+ }
+ DL_EXTRACT_RESULT = {
+ "train_data": "train-image",
+ "train_labels": "train-label",
+ "test_data": "test-image",
+ "test_labels": "test-label",
+ }
+
+
+ """
+ Skip the test_download_and_prepare_as_dataset test using
+ @pytest.mark.skip decorator because no dummy dataset
+ was included for spots10.
+ """
+ @pytest.mark.skip(reason="Skipping this test temporarily.")
+ def test_download_and_prepare_as_dataset(self):
+ pass
+
+
+if __name__ == "__main__":
+ testing.test_main()