init

README.md

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+---
+license: other
+task_categories:
+- text-to-image
+language:
+- en
+tags:
+- stable-diffusion
+- realms
+pretty_name: Realms Adventurers Dataset
+size_categories:
+- n<1K
+---
+
+# Realms Adventurer Dataset for Text-to-Image
+
+This dataset contains annotated image-caption pairs with a specific structure.
+
+## Example
+
+```json
+{
+    "file_name": "91200682-07_giants.png",
+    "sex": "male",
+    "race": "giant",
+    "class": "mage",
+    "inherent_features": "red flowers growing on his skin",
+    "clothing": "brown leather pants",
+    "accessories": null,
+    "background": "between tall red trees",
+    "shot": "full",
+    "view": "frontal",
+    "caption": "a male giant mage with red flowers growing on his skin, wearing brown leather pants, between tall red trees, full, frontal"
+}
+```
+
+## Usage
+
+```python
+import datasets
+
+dataset = datasets.load_dataset("rvorias/realms_adventurers")
+
+dataset["train"][0]
+```
+
+## Annotation tooling
+
+Label-studio was used to organize and create annotations.

data/images_001.zip

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+oid sha256:b96fdea763d54939fbd8de3936ababd9fada7569a735f5b39b6dbbdbb27f98b5
+size 177930282

metadata.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c5f4130f05744481cdf6a52a835413cdd6c3a469c5c489f6a2ab03875800b047
+size 89974

realms_adventurers.py

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+# Copyright 2020 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.
+# 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.
+
+import json
+import os
+
+import datasets
+from huggingface_hub import hf_hub_url
+
+
+_CITATION = ""
+_DESCRIPTION = """This is the public dataset for the realms adventurer generator.
+It contains images of characters and annotations to form structured captions."""
+
+_HOMEPAGE = ""
+
+_LICENSE = "https://docs.midjourney.com/docs/terms-of-service"
+
+_URLS = {
+    "images": hf_hub_url(
+        "rvorias/realms_adventurers",
+        filename="images_001.zip",
+        subfolder="images",
+        repo_type="dataset",
+    ),
+    "metadata": hf_hub_url(
+        "rvorias/realms_adventurers",
+        filename=f"metadata.json",
+        repo_type="dataset",
+    ),
+}
+
+
+class RealmsAdventurersDataset(datasets.GeneratorBasedBuilder):
+    """Public dataset for the realms adventurer generator.
+    Containts images + structured captions."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "image": datasets.Image(),
+                "caption": datasets.Value("string"),
+                "components": {                
+                    "sex": datasets.Value("string"),
+                    "race": datasets.Value("string"),
+                    "class": datasets.Value("string"),
+                    "inherent_features": datasets.Value("string"),
+                    "clothing": datasets.Value("string"),
+                    "accessories": datasets.Value("string"),
+                    "background": datasets.Value("string"),
+                    "shot": datasets.Value("string"),
+                    "view": datasets.Value("string"),
+                }
+            }
+        )
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            supervised_keys=("image", "caption"),
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        images_url = _URLS["images"]
+        images_dir = dl_manager.download_and_extract(images_url)
+
+        print("AA")
+        
+        annotations_url = _URLS["annotations"]
+        annotations_path = dl_manager.download(annotations_url)
+
+        print(images_dir)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "root_dir": images_dir,
+                    "metadata_path": annotations_path,
+                },
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, root_dir, metadata_path):
+        with open(metadata_path, encoding="utf-8") as f:
+            data = json.load(f)
+        # for sample in data:
+        #     image_path = os.path.join(root_dir, sample["file_name"])
+        #     with open(image_path, "rb") as file_obj:
+        #         yield image_path, {
+        #             "image": {"path": image_path, "bytes": file_obj.read()},
+        #             "caption": sample["caption"],
+        #             "components": {                
+        #                 "sex": sample.get("sex"),
+        #                 "race": sample.get("race"),
+        #                 "class": sample.get("class"),
+        #                 "inherent_features": sample.get("inherent_features"),
+        #                 "clothing": sample.get("clothing"),
+        #                 "accessories": sample.get("accessories"),
+        #                 "background": sample.get("background"),
+        #                 "shot": sample.get("shot"),
+        #                 "view": sample.get("view"),
+        #             },
+        #         }