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Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the modelAddress questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the modelAddress questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the modelAddress questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the modelAddress questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model
Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model
metadata
license: Apache License 2.0
image:
image-classification:
size_scale:
- 100-10k
tags:
- classification
数据集描述
数据集简介
本数据集是简单的猫狗二分类数据集，共2个类别，其中训练集包含275张带注释的图像，验证集包含70张带注释的图像。整个数据集共10.3MB，可用于快速模型验证、性能评估、小数据集训练等。
数据集支持的任务
可用于快速模型验证、性能评估、小数据集训练等。
数据集的格式和结构
数据格式
数据集包括训练集train和验证集val，train和val文件夹之下按文件夹进行分类，共有2个子文件夹，同类别标签的图片在同一个文件夹下，图片格式为JPG。同时包含与标注文件中label id相对应的类名文件classname.txt。
数据集加载方式
from modelscope.msdatasets import MsDataset
from modelscope.utils.constant import DownloadMode
ms_train_dataset = MsDataset.load(
'cats_and_dogs', namespace='tany0699',
subset_name='default', split='train') # 加载训练集
print(next(iter(ms_train_dataset)))
ms_val_dataset = MsDataset.load(
'cats_and_dogs', namespace='tany0699',
subset_name='default', split='validation') # 加载验证集
print(next(iter(ms_val_dataset)))
数据分片
本数据集包含train和val数据集。
| 子数据集 | train | val | test |
|---|---|---|---|
| default | 训练集 | 验证集 | / |
Clone with HTTP
git clone https://www.modelscope.cn/datasets/tany0699/cats_and_dogs.git