非洲合成糖尿病数据集（T2DM与GDM）

数据集获取与加载（Hugging Face datasets）

# 前置依赖: pip install datasets
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-synth-diabetes-diabetes-dataset-all")
print(ds)  # 查看 splits 与字段结构
# 国内网络可先设镜像: import os; os.environ["HF_ENDPOINT"]="https://hf-mirror.com"

git lfs install && git clone https://hf-mirror.com/datasets/electricsheepafrica/africa-synth-diabetes-diabetes-dataset-all

数据集大小约 77.4 KB。

仓库文件结构

• .gitattributes
• README.md
• diabetes_gdm_africa_antenatal_2000.csv
• diabetes_gdm_africa_large_5000.csv
• diabetes_generator.py
• diabetes_t2dm_africa_baseline_1000.csv
• diabetes_t2dm_africa_extra_large_10000.csv
• diabetes_t2dm_africa_large_5000.csv
• diabetes_t2dm_africa_test_2000.csv
• diabetes_t2dm_africa_urban_high_risk_2000.csv
• generate_datasets.py

数据说明

Electric Sheep Africa, africa-synth-diabetes-diabetes-dataset-all [Dataset]. https://huggingface.co/datasets/electricsheepafrica/africa-synth-diabetes-diabetes-dataset-all

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

完整数据卡：huggingface.co/datasets/electricsheepafrica/africa-synth-diabetes-diabetes-dataset-all