---
license: cc-by-nc-4.0
language:
- en
size_categories:
- 10K<n<100K
---

# 📚 HistVis Dataset

**HistVis** is a dataset designed to evaluate how text-to-image models represent cultural and historical variations in human activities. It contains images generated by multiple models across temporal prompts and activity categories.

## 📋 Dataset Structure

The main metadata is stored in [`dataset.csv`](./dataset.csv), with one row per image. Below is a description of each column:

| Column | Description |
|--------|-------------|
| `image_path` | **Relative path** to the image file within the repository. These correspond to generations by different models under specific historical prompts. |
| `model` | The name of the text-to-image model used to generate the image (e.g., `Flux_Schnell`, `SD_3`, `SD_XL`). |
| `historical_period` | The historical era or century the prompt refers to (e.g., `19th_century`, `1920s`). This is the temporal condition imposed in the prompt. |
| `universal_human_activity` | The prompt used to describe the universal human activity, such as "a person listening to music" or "a person laughing with a friend". |
| `category` | The broader conceptual category of the human activity (e.g., `Health and Well-being`, `Art`, "Music"). This groups related prompts under common cultural dimensions. |

## 🧾 Prompt Format

Each image in the dataset was generated using the following prompt template:

> **"a [universal_human_activity] in the [historical_period]"**

For example:
- "a person listening to music in the 1950s"
- "a person laughing with a friend in the 19th century"

## 💻 Using the Dataset

You can access the HistVis dataset using the Hugging Face Datasets library. Below are examples showing how to load and explore the dataset.

### Basic Usage

```python
from datasets import load_dataset
import pandas as pd

# Load the dataset metadata (CSV only)
dataset = load_dataset('csv', data_files='https://huggingface.co/datasets/latentcanon/HistVis/resolve/main/dataset.csv')

# Convert to pandas DataFrame for easier manipulation
df = pd.DataFrame(dataset['train'])
print(f"Dataset contains {len(df)} entries")

# View first few entries
print(df.head())