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 image
• text: 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

1. Web Scraping: Images and descriptions were collected from [specify sources if appropriate]
2. Image Processing: All images were resized to 224×224 pixels using high-quality resampling
3. Format Standardization: Images converted to RGB JPEG format
4. Quality Control: Corrupt or extremely small images were filtered out
5. 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: [[email protected]]
• 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]

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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. ```