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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**
```python
from datasets import load_dataset
ds = load_dataset("ESmike/true_imgs_modalities")
example = ds["train"][0]
image = example["image"]
modality = example["std512"]
```
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