Datasets:
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import json, os
from PIL import Image
import datasets
from datasets.utils.file_utils import xopen # <─ key helper
from datasets.utils.logging import get_logger, tqdm
logger = get_logger(__name__)
logger.setLevel("INFO")
NUM_PARTS = 14
_TAR_URLS = [
f"https://huggingface.co/datasets/artpods56/EcclesialSchematisms/"
f"resolve/main/images/images_part{i}.tar"
for i in range(1, NUM_PARTS + 1)
]
_LABEL_URL = "https://huggingface.co/datasets/artpods56/EcclesialSchematisms/" \
"resolve/main/labels/train.jsonl"
class EcclesiaeSchematisms(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features({
"image_pil": datasets.Image(decode="pil"), # keep memory low
"image": datasets.Value("string"),
"width": datasets.Value("int32"),
"height": datasets.Value("int32"),
"words": datasets.Sequence(datasets.Value("string")),
"bboxes": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))),
"labels": datasets.Sequence(datasets.Value("string")),
"conf": datasets.Sequence(datasets.Value("float32")),
})
)
def _split_generators(self, dl_manager):
images_tars = dl_manager.download(_TAR_URLS)
labels_file = dl_manager.download(_LABEL_URL) # local, small
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"images_tars": images_tars,
"labels": labels_file,
"dl_manager": dl_manager, # pass it forward
},
)
]
# NOTE the extra parameter
def _generate_examples(self, images_tars, labels, dl_manager):
logger.info("Loading label annotations…")
annotations = {}
with xopen(labels, "r") as f: # works in streaming
for line in f:
ann = json.loads(line)
annotations[os.path.basename(ann["image_path"])] = ann
logger.info("Loaded %d annotations.", len(annotations))
example_id = 0
for tar_path in images_tars:
logger.info("Iterating %s", tar_path)
# iter_archive streams members one-by-one
for member_name, fobj in dl_manager.iter_archive(tar_path):
if not member_name.endswith(".jpg"):
continue
img_name = os.path.basename(member_name)
ann = annotations.get(img_name)
if ann is None:
continue
with Image.open(fobj).convert("RGB") as image:
yield example_id, {
"image_pil": image,
"image": ann["image_path"],
"width": ann["width"],
"height": ann["height"],
"words": ann["words"],
"bboxes": ann["bboxes"],
"labels": ann["labels"],
"conf": ann.get("conf", []),
}
example_id += 1
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