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---
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.
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