SPIDER-skin
SPIDER-skin是皮肤病理图像分类数据集,含159,854张中心图像块,覆盖24类皮肤疾病和组织结构,用于监督学习。
基本信息
资源简介
SPIDER-skin是面向皮肤器官的有监督病理图像数据集,包含159,854张中心图像块(224×224像素)及24种类别,涵盖光化性角化病、基底细胞癌、侵袭性黑色素瘤等皮肤疾病和组织学结构。图像块从3,784张全视野数字切片以20倍放大倍率提取,并附带24张上下文图像块形成1120×1120复合区域。数据集提供训练-测试划分,可用于皮肤病理图像分类任务的模型训练和基准测试。
下载信息
注册下载
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暂未开放千方医数集,医疗数据集部分,是为社区服务的公开医疗数据集搜索引擎,并不存储或者下载原始的任何数据。 如果您有其他医疗数据需求,可以和客服联系,或者下工单。我们有强大的三甲医疗机构帮助您提供个性化的医疗数据定制、采集、标注服务。
使用方式
数据集获取(ModelScope)
方式一:MsDataset(Python)
# 前置依赖: pip install modelscope
from modelscope.msdatasets import MsDataset
ds = MsDataset.load("histai/SPIDER-skin", subset_name="default", split="train")
print(ds)
方式二:CLI(命令行)
pip install modelscope
modelscope download dataset histai/SPIDER-skin
数据集卡片摘录(源站)
SPIDER-SKIN Dataset
SPIDER is a collection of supervised pathological datasets covering multiple organs, each with comprehensive class coverage. These datasets are professionally annotated by pathologists.
If you would like to support, sponsor, or obtain a commercial license for the SPIDER data and models, please contact us at models@hist.ai.
For a detailed description of SPIDER, methodology, and benchmark results, refer to our research paper:
SPIDER: A Comprehensive Multi-Organ Supervised Pathology Dataset and Baseline Models
View on arXiv
This repository contains the SPIDER-skin dataset. To explore datasets for other organs, visit the Hugging Face HistAI page or GitHub. SPIDER is regularly updated with new organs and data, so follow us on Hugging Face to stay updated.
Overview
SPIDER-skin is a supervised dataset of image-class pairs for the skin organ. Each data point consists of:
- A central 224×224 patch with a class label
- 24 surrounding context patches of the same size, forming a composite 1120×1120 region
- Patches are extracted at 20X magnification
We provide a train-test split for consistent benchmarking. The split is done at the slide level, ensuring that patches from the same whole slide image (WSI) do not appear in both training and test sets. Users can also merge and re-split the data as needed.
How to Use
Downloading the Dataset
Option 1: Using huggingface_hub
from huggingface_hub import snapshot_download
snapshot_download(repo_id="histai/SPIDER-skin", repo_type="dataset", local_dir="/local_path")
Option 2: Using git
# Ensure you have Git LFS installed (https://git-lfs.com)
git lfs install
git clone https://huggingface.co/datasets/histai/SPIDER-skin
Extracting the Dataset
The dataset is provided in multiple tar archives. Unpack them using:
cat spider-skin.tar.* | tar -xvf -
Using the Dataset
Once extracted, you will find:
- An
images/folder - A
metadata.jsonfile
You can process and use the dataset in two ways:
1. Directly in Code (Recommended for PyTorch Training)
Use the dataset class provided in scripts/spider_dataset.py. This class takes:
- Path to the dataset (folder containing
metadata.jsonand
许可
Apache License 2.0
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。
精度瓶颈?数据缺失?
当前公开数据无法满足您的算法精度?千方提供针对 皮肤癌 的高质量、多模态真实临床数据定制解决方案。




