|
import os |
|
import random |
|
import datasets |
|
from datasets.tasks import ImageClassification |
|
|
|
|
|
_HOMEPAGE = ( |
|
f"https://www.modelscope.cn/datasets/MuGemSt/{os.path.basename(__file__)[:-3]}" |
|
) |
|
|
|
_URL = f"{_HOMEPAGE}/resolve/master/images.zip" |
|
|
|
_NAMES = ["Centromere", "Golgi", "Homogeneous", "NuMem", "Nucleolar", "Speckled"] |
|
|
|
|
|
class HEp2(datasets.GeneratorBasedBuilder): |
|
def _info(self): |
|
return datasets.DatasetInfo( |
|
features=datasets.Features( |
|
{ |
|
"image": datasets.Image(), |
|
"label": datasets.features.ClassLabel(names=_NAMES), |
|
} |
|
), |
|
supervised_keys=("image", "label"), |
|
homepage=_HOMEPAGE, |
|
license="mit", |
|
version="0.0.1", |
|
task_templates=[ |
|
ImageClassification( |
|
task="image-classification", |
|
image_column="image", |
|
label_column="label", |
|
) |
|
], |
|
) |
|
|
|
def _ground_truth(self, id): |
|
if id < 2495: |
|
return "Homogeneous" |
|
|
|
elif id < 5326: |
|
return "Speckled" |
|
|
|
elif id < 7924: |
|
return "Nucleolar" |
|
|
|
elif id < 10665: |
|
return "Centromere" |
|
|
|
elif id < 12873: |
|
return "NuMem" |
|
|
|
else: |
|
return "Golgi" |
|
|
|
def _split_generators(self, dl_manager): |
|
data_files = dl_manager.download_and_extract(_URL) |
|
files = dl_manager.iter_files([data_files]) |
|
dataset = [] |
|
for path in files: |
|
file_name = os.path.basename(path) |
|
if file_name.endswith(".png"): |
|
dataset.append( |
|
{ |
|
"image": path, |
|
"label": self._ground_truth(int(file_name.split(".")[0])), |
|
} |
|
) |
|
|
|
random.shuffle(dataset) |
|
data_count = len(dataset) |
|
p80 = int(data_count * 0.8) |
|
p90 = int(data_count * 0.9) |
|
|
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, |
|
gen_kwargs={ |
|
"files": dataset[:p80], |
|
}, |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.VALIDATION, |
|
gen_kwargs={ |
|
"files": dataset[p80:p90], |
|
}, |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TEST, |
|
gen_kwargs={ |
|
"files": dataset[p90:], |
|
}, |
|
), |
|
] |
|
|
|
def _generate_examples(self, files): |
|
for i, path in enumerate(files): |
|
yield i, path |
|
|
