Datasets:
File size: 4,911 Bytes
766f54f f98e06e 766f54f d33c309 766f54f d33c309 07fcfbe f246a33 07fcfbe f246a33 d33c309 07fcfbe d33c309 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 |
# 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="data",
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)
annotations_url = _URLS["metadata"]
annotations_path = dl_manager.download(annotations_url)
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"])
if "caption" in sample:
caption = sample["caption"]
elif "discord_prompt" in sample:
caption = sample["discord_prompt"]
else:
continue
with open(image_path, "rb") as file_obj:
yield image_path, {
"image": {"path": image_path, "bytes": file_obj.read()},
"caption": 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"),
},
}
|