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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.
"""Dataset for filtered Kvasir-instrument and Hyper-Kvasir with bounding boxes."""
import os
import json
from PIL import Image
import datasets
import os
import json
import pandas as pd
import hashlib
cal_mid = lambda bx: [[[float(box['xmin'] + box['xmax']) / 2, float(box['ymin'] + box['ymax']) / 2] for box in bx]]
def cal_sha256(file_path): return hashlib.sha256(
open(file_path, 'rb').read()).hexdigest()
hyper_label_img_path = '/global/D1/projects/HOST/Datasets/hyper-kvasir/labeled-images/image-labels.csv'
hyper_df = pd.read_csv(hyper_label_img_path)
hyper_seg_img_path = '/global/D1/projects/HOST/Datasets/hyper-kvasir/segmented-images/bounding-boxes.json'
hyper_seg_img_base_path = "/global/D1/projects/HOST/Datasets/hyper-kvasir/segmented-images/images"
instr_seg_img_path = '/global/D1/projects/HOST/Datasets/kvasir-instrument/bboxes.json'
instr_seg_img_base_path = '/global/D1/projects/HOST/Datasets/kvasir-instrument/images/'
hyper_seg_imgs = json.load(open(hyper_seg_img_path))
instr_seg_imgs = json.load(open(instr_seg_img_path))
_CITATION = """\
@article{kvasir,
title={Kvasir-instrument and Hyper-Kvasir datasets for bounding box annotations},
author={Sushant Gautam and collaborators},
year={2024}
}
"""
_DESCRIPTION = """
Filtered Kvasir-instrument and Hyper-Kvasir datasets with bounding boxes for medical imaging tasks.
Each entry contains images, bounding box coordinates, and additional metadata.
"""
_HOMEPAGE = "https://example.com/kvasir-hyper-bbox"
_LICENSE = "CC BY-NC 4.0"
_URLS = {
"filtered_data": "https://example.com/kvasir-hyper-bbox-dataset.zip"
}
class KvasirHyperBBox(datasets.GeneratorBasedBuilder):
"""Dataset for Kvasir-instrument and Hyper-Kvasir with bounding boxes."""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="bbox_dataset",
version=VERSION,
description="Dataset with bounding box annotations."
)
]
DEFAULT_CONFIG_NAME = "bbox_dataset"
def _info(self):
features = datasets.Features({
"image_data": datasets.Image(),
"image_sha256": datasets.Value("string"),
"points": datasets.Sequence(datasets.Sequence(datasets.Sequence(datasets.Value("float32")))),
"count": datasets.Value("int64"),
"label": datasets.Value("string"),
"collection_method": datasets.Value("string"),
"classification": datasets.Value("string"),
"organ": datasets.Value("string")
})
return datasets.DatasetInfo(
description=_DESCRIPTION,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
features=features
)
def _split_generators(self, dl_manager):
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={},
)
]
def _generate_examples(self):
for key, entry in hyper_seg_imgs.items():
img_path = os.path.join(hyper_seg_img_base_path, f"{key}.jpg")
hyper_entry = hyper_df.loc[hyper_df['Video file'] == key].iloc[0]
yield key, {
"image_data": open(img_path, 'rb').read(),
"image_sha256": cal_sha256(img_path),
"points": cal_mid(entry['bbox']),
"count": len(entry['bbox']),
"label": hyper_entry.Finding,
"collection_method": 'counting',
"classification": hyper_entry.Classification,
"organ": hyper_entry.Organ
}
for key, entry in instr_seg_imgs.items():
img_path = os.path.join(instr_seg_img_base_path, f"{key}.jpg")
assert len(cal_mid(entry['bbox'])) > 0
yield key, {
"image_data": open(img_path, 'rb').read(),
"image_sha256": cal_sha256(img_path),
"points": cal_mid(entry['bbox']),
"count": len(entry['bbox']),
"label": "instrument",
"collection_method": "counting",
"classification": "instrument",
"organ": "instrument"
}
#datasets-cli test /global/D1/projects/HOST/Datasets/hyper-kvasir/sushant-experiments/kvasir-points_datasets_script.py --save_info --all_configs --trust_remote_code
# huggingface-cli upload kvasir-points . . --repo-type dataset
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