Datasets:

ESmike
/

true_imgs_modalities

dataset_info:
  features:
    - name: caption
      dtype: string
    - name: width
      dtype: int64
    - name: height
      dtype: int64
    - name: filename
      dtype: string
    - name: std512_hash
      dtype: string
    - name: colorboost_hash
      dtype: string
    - name: grayscale_hash
      dtype: string
    - name: edges_hash
      dtype: string
    - name: edges
      dtype: image
    - name: grayscale
      dtype: image
    - name: std512
      dtype: image
    - name: colorboost
      dtype: image
  splits:
    - name: train
      num_bytes: 1482878357.415
      num_examples: 4149
  download_size: 1384883967
  dataset_size: 1482878357.415
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-to-image
  - image-segmentation
  - image-to-text
language:
  - en
size_categories:
  - 1K<n<10K

Dataset Summary

ESmike/true_imgs_modalities is a multimodal dataset containing 4,149 real images at a uniform resolution of 512 × 512, along with multiple derived modalities for each image. This dataset is intended for research and experimentation in computer vision, generative modeling, and multimodal learning.

All images originate from real photographs curated and processed. Each base image is provided alongside additional modality representations (details in the Data Fields section).

If you use this dataset in your research, add the below citation.

Supported Tasks and Use Cases

This dataset can be used for a wide range of tasks, including:

Multimodal image-to-image training
Generative model conditioning
Representation learning
Vision–language / multimodal modeling
Super-resolution or transformation tasks
Benchmarking image encoders

Dataset Structure

Data Fields

image: The original real 512×512 image.
caption: A short text description of the image. filename: Original filename used during dataset creation. width, height: Original image dimensions before standardization. std512: The main 512×512 standardized real image. colorboost: A color-enhanced version of the image. grayscale: A grayscale transformation of the image. edges: Edge-detected version of the image.

Citation

If you use this dataset, please cite:

@dataset{esmike_true_imgs_modalities,
  author = {Eric Saikali},
  title = {true_imgs_modalities},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/ESmike/true_imgs_modalities}
}

How to Use

from datasets import load_dataset

ds = load_dataset("ESmike/true_imgs_modalities")
example = ds["train"][0]

image = example["image"]
modality = example["std512"]