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:

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

Collection Process

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

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Dataset Card for Augmented Car Images

---
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
```python
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']