Update artwork_for_sdxl.py

artwork_for_sdxl.py

@@ -1,5 +1,5 @@
 # coding=utf-8
-# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
+# Copyright 2024 The HuggingFace Datasets Authors and the current dataset script contributor.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -12,37 +12,32 @@
 # 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.
-"""ImageNet-Sketch data set for evaluating model's ability in learning (out-of-domain) semantics at ImageNet scale"""
+"""Artwork Images - a dataset of centuries of Images prompt."""
 
 import os
 
 import pandas as pd
 import datasets
-from datasets.tasks import ImageClassification
+from PIL import Image
 
 # from .classes import IMAGENET2012_CLASSES
 
 
-_HOMEPAGE = "https://huggingface.co/datasets/AIPI540/test2/tree/main"
+_HOMEPAGE = "https://huggingface.co/datasets/wintercoming6/artwork_for_sdxl/tree/main"
 
 _CITATION = """\
-@inproceedings{wang2019learning,
-        title={Learning Robust Global Representations by Penalizing Local Predictive Power},
-        author={Wang, Haohan and Ge, Songwei and Lipton, Zachary and Xing, Eric P},
-        booktitle={Advances in Neural Information Processing Systems},
-        pages={10506--10518},
-        year={2019}
+Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 10684-10695).  
 }
 """
 
 _DESCRIPTION = """\
-Artwork Images, to predict the year of the artwork created.
+Artwork Images, to generate the similar artwork using stable diffusion model.
 """
 
 _URL = "https://huggingface.co/datasets/wintercoming6/artwork_for_sdxl/resolve/main/metadata.jsonl"
 
 class Artwork(datasets.GeneratorBasedBuilder):
-    """Artwork Images - a dataset of centuries of Images classes"""
+    """Artwork Images - a dataset of centuries of Images prompt."""
 
     def _info(self):
         return datasets.DatasetInfo(
@@ -53,10 +48,8 @@ class Artwork(datasets.GeneratorBasedBuilder):
                     "image_data": Image,
                 }
             ),
-            supervised_keys=("label","image_data"),
+            supervised_keys=("prompt","image_data"),
             homepage=_HOMEPAGE,
-            citation=_CITATION,
-            task_templates=[ImageClassification(image_column="image_data", label_column="prompt")],
         )
 
     def _split_generators(self, dl_manager):