---
license: mit
dataset_info:
  features:
  - name: image
    dtype: image
  - name: commands
    list:
    - name: shape
      dtype: string
    - name: class
      dtype: string
    - name: position_x
      dtype: float64
    - name: position_y
      dtype: float64
    - name: position_z
      dtype: int64
    - name: width
      dtype: float64
    - name: height
      dtype: float64
    - name: color
      sequence: int64
  splits:
  - name: train
    num_bytes: 1838065
    num_examples: 1000
  download_size: 789830
  dataset_size: 1838065
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
language:
- en
tags:
- synthetic
size_categories:
- 1K<n<10K
task_categories:
- text-to-image
- text-generation
pretty_name: Houses
---

# Houses

This synthetic dataset contains images of simple houses and their corresponding drawing instructions. It is designed for training models to predict missing elements in visual sequences to facilitate systems such as Copilot. 

## Features
- **Images**: 256x256 images representing house drawings.
- **Commands**: structured commands in JSON format describing the components of the house (e.g., body, roof, windows).

## Usage
This dataset can be used to train machine learning models for tasks such as:
- sequence completion;
- image generation from structured commands;
- commands generation from visual inputs.

You can also use code from this [repository](https://github.com/vvmatorin/houses) to generate a dataset of the same format according to your own requirements.