| --- |
| license: cc-by-nc-4.0 |
| language: |
| - en |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # 📚 HistVis Dataset |
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|
| **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. |
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| ## 📋 Dataset Structure |
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| The main metadata is stored in [`dataset.csv`](./dataset.csv), with one row per image. Below is a description of each column: |
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| | 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 |
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| Each image in the dataset was generated using the following prompt template: |
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| > **"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()) |
