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tanganke/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… See the full description on the dataset page: https://huggingface.co/datasets/tanganke/stanford_cars.

sourceHugging Faceupdated 2y agoView on Hugging Face
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Dataset Card

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"]