add data

.gitattributes

@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.mp3 filter=lfs diff=lfs merge=lfs -text
 *.ogg filter=lfs diff=lfs merge=lfs -text
 *.wav filter=lfs diff=lfs merge=lfs -text
+data/cartoonset10k.tgz filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,156 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# data files
+/scratch.py
+/test.py

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "python.formatting.provider": "black"
+}

cartoonset10k.py

@@ -0,0 +1,100 @@
+"""Cartoonset-10k Data Set"""
+
+
+import pickle
+
+import numpy as np
+import PIL.Image
+
+
+import datasets
+from datasets.tasks import ImageClassification
+
+
+_CITATION = """\
+@TECHREPORT{Krizhevsky09learningmultiple,
+    author = {Alex Krizhevsky},
+    title = {Learning multiple layers of features from tiny images},
+    institution = {},
+    year = {2009}
+}
+"""
+
+_DESCRIPTION = """\
+The Cartoonset-10k dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images
+per class. There are 50000 training images and 10000 test images.
+"""
+
+_DATA_URL = "https://storage.cloud.google.com/cartoonset_public_files/cartoonset10k.tgz"
+
+_NAMES = []
+
+
+class Cartoonset10k(datasets.GeneratorBasedBuilder):
+    """Cartoonset-10k Data Set"""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="cartoonset10k",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of Cartoonset-10k Data Set",
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "img": datasets.Image(),
+                    # "label": datasets.features.ClassLabel(names=_NAMES),
+                }
+            ),
+            supervised_keys=("img",),
+            homepage="https://www.cs.toronto.edu/~kriz/cifar.html",
+            citation=_CITATION,
+            # task_templates=ImageClassification(
+            #     image_column="img", label_column="label"
+            # ),
+        )
+
+    def _split_generators(self, dl_manager):
+        print("URL:", _DATA_URL)
+        archive = dl_manager.download({"train": _DATA_URL})
+
+        print(archive)
+        exit()
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "files": dl_manager.iter_archive(archive),
+                    "split": "train",
+                },
+            ),
+            # datasets.SplitGenerator(
+            #     name=datasets.Split.TEST, gen_kwargs={"files": dl_manager.iter_archive(archive), "split": "test"}
+            # ),
+        ]
+
+    def _generate_examples(self, files, split):
+        """This function returns the examples in the raw (text) form."""
+
+        # if split == "train":
+        #     batches = ["data_batch_1", "data_batch_2", "data_batch_3", "data_batch_4", "data_batch_5"]
+
+        # if split == "test":
+        #     batches = ["test_batch"]
+        # batches = [f"Cartoonset-10k-batches-py/{filename}" for filename in batches]
+        print("FILES", files)
+
+        path: str
+        for path, file_obj in files:
+
+            if path.endswith(".png"):
+                image = PIL.Image.open(path)
+
+                yield path, {
+                    "img": np.asarray(image),
+                }

data/cartoonset10k.tgz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:902145ad5096af10ca9ee200b648e2a60e8b6b83dd2f4dc5356817988be8ff43
+size 476635078

dataset_infos.json

@@ -0,0 +1,39 @@
+{
+    "plain_text": {
+        "description": "The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images\nper class. There are 20000 training images and 10000 test images.\n",
+        "citation": "@TECHREPORT{Krizhevsky09learningmultiple,\n    author = {Alex Krizhevsky},\n    title = {Learning multiple layers of features from tiny images},\n    institution = {},\n    year = {2009}\n}\n",
+        "homepage": "https://www.cs.toronto.edu/~kriz/cifar.html",
+        "license": "",
+        "features": {
+            "img": {
+                "id": null,
+                "_type": "Image"
+            }
+        },
+        "post_processed": null,
+        "supervised_keys": {
+            "input": "img",
+            "output": "label"
+        },
+        "builder_name": "cifar10",
+        "version": {
+            "version_str": "1.0.0",
+            "description": "",
+            "major": 1,
+            "minor": 0,
+            "patch": 0
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 476635078,
+                "num_examples": 20000,
+                "dataset_name": "cifar10"
+            }
+        },
+        "download_size": 476635078,
+        "post_processing_size": null,
+        "dataset_size": 136627438,
+        "size_in_bytes": 307125509
+    }
+}

pyproject.toml

@@ -0,0 +1,18 @@
+[tool.poetry]
+name = "cartoonset10k"
+version = "0.1.0"
+description = ""
+authors = ["Cristian Garcia <[email protected]>"]
+
+[tool.poetry.dependencies]
+python = "^3.8"
+datasets = "^1.18.4"
+numpy = "^1.22.3"
+Pillow = "^9.0.1"
+
+[tool.poetry.dev-dependencies]
+black = {version = "^22.1.0", allow-prereleases = true}
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"