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imagereward-evaluation.py

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+import datasets
+import json
+
+import json
+import os
+
+import datasets
+
+_DESCRIPTION = """\
+Dataset to perform Aesthetic evaluation from Table 2 in ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation.
+
+@misc{xu2023imagereward,
+      title={ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation}, 
+      author={Jiazheng Xu and Xiao Liu and Yuchen Wu and Yuxuan Tong and Qinkai Li and Ming Ding and Jie Tang and Yuxiao Dong},
+      year={2023},
+      eprint={2304.05977},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+"""
+
+class ImagerewardEvaluation(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("string"),
+                "prompt": datasets.Value("string"),
+                "generations": datasets.Sequence(datasets.Image()),
+                "ranking": datasets.Sequence(datasets.Value("int32")),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract("./test.json")
+        images = dl_manager.download_and_extract("./images.zip")
+        print(downloaded_files, images)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"metadata_path": downloaded_files, "images_path": os.path.join(images, "test_images")}),
+        ]
+
+    def _generate_examples(self, metadata_path, images_path):
+        with open(metadata_path, encoding="utf-8") as f:
+            data = json.load(f)
+            for item in data:
+                yield item["id"], {
+                    "id": item["id"],
+                    "prompt": item["prompt"],
+                    "generations": [os.path.join(images_path, x) for x in item["generations"]],
+                    "ranking": item["ranking"],
+                }

images.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e74d1b0d3017cc2ad58ba355a230ad9cede32841c655d5357aa6adc47a35e011
+size 1183893396