stanford_cars

# Stanford Cars Dataset

## Dataset Overview

- **Splits**:
- **Training**: 8144 images used for model training.
- **Test**: 8041 images used for evaluation.
- **Contrast**: 8041 images with high contrast for robustness testing.
- **Gaussian Noise**: 8041 images corrupted by Gaussian noise for robustness testing.
- **Impulse Noise**: 8041 images corrupted by impulse noise for robustness testing.
- **JPEG Compression**: 8041 compressed images for robustness testing.
- **Motion Blur**: 8041 images with motion blur for robustness testing.
- **Pixelate**: 8041 pixelated images for robustness testing.
- **Spatter**: 8041 images corrupted by spatter for robustness testing.

## Usage Examples

```python
from datasets import load_dataset

# Load the dataset in a tabular format with image URLs and metadata
dataset = load_dataset("tanganke/stanford_cars")

# Access the training set directly
train_set = dataset["train"]
```

# 斯坦福汽车数据集（Stanford Cars Dataset）

## 数据集概览

- **数据集划分**：
- **训练集**：8144张图像用于模型训练。
- **测试集**：8041张图像用于模型评估。
- **高对比度子集**：8041张高对比度图像，用于鲁棒性测试。
- **高斯噪声（Gaussian Noise）子集**：8041张被高斯噪声污染的图像，用于鲁棒性测试。
- **脉冲噪声（Impulse Noise）子集**：8041张被脉冲噪声污染的图像，用于鲁棒性测试。
- **JPEG压缩（JPEG Compression）子集**：8041张经过JPEG压缩的图像，用于鲁棒性测试。
- **运动模糊（Motion Blur）子集**：8041张带有运动模糊的图像，用于鲁棒性测试。
- **像素化（Pixelate）子集**：8041张像素化图像，用于鲁棒性测试。
- **溅污（Spatter）子集**：8041张被溅污污染的图像，用于鲁棒性测试。

## 使用示例

python
from datasets import load_dataset

# 以表格格式加载包含图像URL与元数据的数据集
dataset = load_dataset("tanganke/stanford_cars")

# 直接访问训练集
train_set = dataset["train"]