Datasetpublic

Anyuhhh/2025-24679-image-dataset

Car Classification Dataset - Original Dataset Description This dataset contains 31 original car images collected for binary classification tasks. Images are captured from various angles and in different lighting conditions. Dataset Summary Images: 31 high-quality car photographs Resolution: 224x224 pixels Format: RGB images (converted from HEIC/PNG) Labels: Binary classification (sedan vs SUV) Usage This dataset is designed for:… See the full description on the dataset page: https://huggingface.co/datasets/Anyuhhh/2025-24679-image-dataset.

sourceHugging Facemitupdated 1y agoView on Hugging Face

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Dataset Card

Car Classification Dataset - Original

Dataset Description

This dataset contains 31 original car images collected for binary classification tasks. Images are captured from various angles and in different lighting conditions.

Dataset Summary

—Images: 31 high-quality car photographs
—Resolution: 224x224 pixels
—Format: RGB images (converted from HEIC/PNG)
—Labels: Binary classification (sedan vs SUV)

Usage

This dataset is designed for:

—Image classification model training
—Computer vision experiments
—Data augmentation testing

Collection Process

Images were personally captured and manually labeled to ensure quality and accuracy.

Dataset Card for Augmented Car Images

yaml

---
language:
- en
license: mit
tags:
- image-classification
- computer-vision
- cars
- vehicles
- augmented-data
annotations_creators:
- machine-generated
pretty_name: Car Classification Dataset - Augmented
size_categories:
- n<1K
task_categories:
- image-classification
task_ids:
- multi-class-image-classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype: 
        class_label:
          names:
            '0': sedan
            '1': suv
  splits:
    - name: original
      num_examples: 31
    - name: augmented
      num_examples: 341
  dataset_size: 372
---

# Car Classification Dataset - Augmented

## Dataset Description

This dataset contains both original and augmented car images for robust binary classification training. The augmentation pipeline ensures model generalization.

### Dataset Summary

- **Original Images**: 31 car photographs
- **Augmented Images**: 341 images (31 original + 310 augmented variations)
- **Resolution**: 224x224 pixels
- **Augmentation Techniques Applied**:
  - Random resized crops (0.7-1.0 scale)
  - Horizontal/vertical flips
  - Rotation (±15 degrees)
  - Color jittering
  - Random erasing
  - RandAugment transformations

### Splits

- `original`: 31 unmodified images
- `augmented`: 341 images including originals and augmented versions

### Usage

from datasets import load_dataset

dataset = load_dataset("your-username/2025-24679-image-dataset")

Access original images

original_data = dataset['original']

Access augmented dataset

augmented_data = dataset['augmented']