Datasets:
The dataset viewer is not available for this dataset.
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Navanjana/image-wallpapers-dataset
Dataset Description
This dataset contains high-quality images paired with descriptive text annotations, designed for computer vision and multimodal machine learning tasks. Each image has been preprocessed to standard dimensions and paired with detailed descriptions extracted from web sources.
Dataset Summary
- Total Images: [NUMBER] images
- Image Format: JPEG (RGB)
- Image Dimensions: 224×224 pixels
- Text Descriptions: Natural language descriptions in English
- Use Cases: Image classification, image captioning, vision-language models, multimodal learning
Dataset Structure
Data Fields
image: A PIL Image object containing a 224×224 RGB imagetext: A string containing the descriptive text for the image
Data Splits
- Train: [42,649] examples
Example Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("Navanjana/image-wallpapers-dataset")
# Access training data
train_data = dataset["train"]
# Get a single example
example = train_data[0]
image = example["image"]
description = example["text"]
# Display image with description
import matplotlib.pyplot as plt
plt.imshow(image)
plt.title(description)
plt.axis("off")
plt.show()
Dataset Creation
Source Data
This dataset was created by collecting images and their associated descriptions from publicly available web sources. All images have been processed to ensure consistency in format and quality.
Data Collection Process
- Web Scraping: Images and descriptions were collected from [specify sources if appropriate]
- Image Processing: All images were resized to 224×224 pixels using high-quality resampling
- Format Standardization: Images converted to RGB JPEG format
- Quality Control: Corrupt or extremely small images were filtered out
- Description Cleaning: Text descriptions were cleaned and standardized
Data Processing Pipeline
- Image resizing with aspect ratio preservation
- Color space normalization to RGB
- File format standardization to JPEG
- Text cleaning and encoding to UTF-8
Intended Use
Primary Use Cases
- Image Classification: Training models to classify images into categories
- Image Captioning: Developing models that generate descriptions for images
- Vision-Language Models: Training multimodal models like CLIP, DALL-E, etc.
- Research: Academic research in computer vision and natural language processing
Out-of-Scope Uses
- Commercial use without proper licensing verification
- Training models for harmful or discriminatory purposes
- Use in high-stakes decision-making without proper validation
Considerations for Users
Limitations
- Images are resized to 224×224, which may result in loss of fine details
- Descriptions are extracted automatically and may contain inaccuracies
- Dataset may reflect biases present in the source material
- Limited to English language descriptions
Biases
Users should be aware that this dataset may contain:
- Geographic biases toward certain regions or cultures
- Demographic biases in the representation of people
- Topical biases based on the source websites
Legal and Ethical Considerations
License
[Specify your license here - common options:]
- CC BY 4.0 (Creative Commons Attribution)
- MIT License
- Apache 2.0
- Custom license
Data Privacy
- No personally identifiable information (PII) is intentionally included
- Images are from publicly available sources
- Users should verify compliance with local regulations
Attribution
If you use this dataset in your research, please cite:
@dataset{Navanjana/image-dataset,
title={[image-dataset]},
author={[Navanjana]},
year={2025},
url={https://huggingface.co/datasets/Navanjana/image-dataset},
note={Downloaded from Hugging Face Datasets}
}
Technical Specifications
System Requirements
- Python 3.7+
- PIL/Pillow for image processing
- datasets library for loading
Version History
Version 1.0 (Current)
- Initial release with [42,649] image-text pairs
- Standard preprocessing pipeline applied
Support and Feedback
For questions, bug reports, or feature requests:
- Email: [malmikanavanjana19@gmail.com]
- Hugging Face Discussion: Use the discussion tab on this dataset page
Acknowledgments
- Data collection and processing tools: BeautifulSoup, Pillow, requests
- Dataset hosting: Hugging Face Hub
- [Any other acknowledgments]
Disclaimer: This dataset is provided as-is for research and educational purposes. Users are responsible for ensuring appropriate use and compliance with all applicable laws and regulations. ```
- Downloads last month
- 23