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---
language:
- en
license: mit
task_categories:
- text-to-image
- unconditional-image-generation
pretty_name: Housey Home v2
dataset_info:
features:
- name: image
dtype: image
- name: prompt
dtype: string
- name: hash
dtype: string
- name: generated_by
dtype: string
- name: quantity
dtype: string
- name: plain_background
dtype: string
- name: has_neighbors
dtype: string
- name: style
sequence: string
- name: size
sequence:
sequence: string
splits:
- name: train
num_bytes: 873060466.6
num_examples: 3032
download_size: 872503009
dataset_size: 873060466.6
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- art
---
# Housey Home v2 - Like v1 never happened
I was in the process of producing a fully synthetic dataset for ungrounded image generation using an unconventional combination of layers. As such, I needed a dataset of highly similar objects with 'themes'. In order to produce `log(x, y)` combinations of options in the final model. This is that dataset.
The initial ( 07/15/2024 ) release includes ~2k unique houses, each processed using a VQA, [ybelkada/blip-vqa-base](https://huggingface.co/Salesforce/blip-vqa-base), to be precise.
Release 2 includes ~3k unique houses, each processed more efficiently and using a more powerful GPU via parallel model loading followed by sequential but accelerated inference and diffusion with each.
```
# This code procedurally generates a simple description based upon the input lists of string selections. Feel free to expand or use as MIT.
word_salad = [
["cartoon", "happy", "goofy", "virant", "whymsical"],
["realistic", "ultra hd", "best quality", "high quality", "masterpiece"],
["horrifying", "nightmare", "wicked", "evil", "dark", "creepy", "scary"]
]
sizes = [
["large mansion", "mansion", "manor", "estate", "enournmous house", "palace"],
["medium house", "home", "residence", "big house", "large house"],
["tiny shack", "cottage", "small house", "miniature house", "dinimutive house", "shack"]
]
post_prompt = ", ".join(chosen_salad := random.choice(word_salad)) + ", " + ", ".join(chosen_sizes := random.choice(sizes))
description = "A " + chosen_sizes[0].split(" ")[0] + ", " + chosen_salad[0] + " " + chosen_sizes[0].split(" ")[1]
``` |