Dataset Viewer
Prompt
stringlengths 1
389
| Category
stringclasses 12
values | Challenge
stringclasses 11
values | Note
stringclasses 24
values | images
imagewidth (px) 256
256
| model_name
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value | seed
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0
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bond
|
Abstract
|
Basic
|
Biology-inspired concepts with multiple meanings
|
openMUSE/muse-512
| 0 |
|
element
|
Abstract
|
Basic
|
Biology-inspired concepts with multiple meanings
|
openMUSE/muse-512
| 0 |
|
molecule
|
Abstract
|
Basic
|
Biology-inspired concepts with multiple meanings
|
openMUSE/muse-512
| 0 |
|
life
|
Abstract
|
Basic
|
Biology-inspired concepts with multiple meanings
|
openMUSE/muse-512
| 0 |
|
protein
|
Abstract
|
Basic
|
Biology-inspired concepts with multiple meanings
|
openMUSE/muse-512
| 0 |
|
yin-yang
|
Abstract
|
Basic
|
Related to five elements
|
openMUSE/muse-512
| 0 |
|
wood
|
Abstract
|
Basic
|
Related to five elements
|
openMUSE/muse-512
| 0 |
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metal
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Abstract
|
Basic
|
Related to five elements
|
openMUSE/muse-512
| 0 |
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space
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Abstract
|
Basic
|
Related to five elements
|
openMUSE/muse-512
| 0 |
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air
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Abstract
|
Basic
|
Related to five elements
|
openMUSE/muse-512
| 0 |
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fire
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Abstract
|
Basic
|
Related to five elements
|
openMUSE/muse-512
| 0 |
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water
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Abstract
|
Basic
|
Related to five elements
|
openMUSE/muse-512
| 0 |
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earth
|
Abstract
|
Basic
|
Related to five elements
|
openMUSE/muse-512
| 0 |
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force
|
Abstract
|
Basic
|
Physics concepts
|
openMUSE/muse-512
| 0 |
|
motion
|
Abstract
|
Basic
|
Physics concepts
|
openMUSE/muse-512
| 0 |
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inertia
|
Abstract
|
Basic
|
Physics concepts
|
openMUSE/muse-512
| 0 |
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energy
|
Abstract
|
Basic
|
Physics concepts
|
openMUSE/muse-512
| 0 |
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black hole
|
Abstract
|
Basic
|
Physics concepts
|
openMUSE/muse-512
| 0 |
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gravity
|
Abstract
|
Basic
|
Physics concepts
|
openMUSE/muse-512
| 0 |
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peace
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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fairness
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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gender
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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intelligence
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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bias
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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hate
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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anger
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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emotion
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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feeling
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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love
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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artificial intelligence
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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meaning of life
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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42
|
Abstract
|
Basic
|
Simple numbers but challenging
|
openMUSE/muse-512
| 0 |
|
0
|
Abstract
|
Basic
|
Simple numbers but challenging
|
openMUSE/muse-512
| 0 |
|
infinity
|
Abstract
|
Basic
|
Math concepts
|
openMUSE/muse-512
| 0 |
|
imaginary numbers
|
Abstract
|
Basic
|
Math concepts
|
openMUSE/muse-512
| 0 |
|
Fibonacci number
|
Abstract
|
Basic
|
Math concepts
|
openMUSE/muse-512
| 0 |
|
golden ratio
|
Abstract
|
Basic
|
Math concepts
|
openMUSE/muse-512
| 0 |
|
an F1
|
Vehicles
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
parallel lines
|
Illustrations
|
Basic
|
Math concepts
|
openMUSE/muse-512
| 0 |
|
concentric circles
|
Illustrations
|
Basic
|
Math concepts
|
openMUSE/muse-512
| 0 |
|
concurrent lines
|
Illustrations
|
Basic
|
Math concepts
|
openMUSE/muse-512
| 0 |
|
congruent triangles
|
Illustrations
|
Basic
|
Math concepts
|
openMUSE/muse-512
| 0 |
|
a hot air balloon
|
Vehicles
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
The Starry Night
|
Arts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
300
|
Abstract
|
Basic
|
Simple numbers but challenging
|
openMUSE/muse-512
| 0 |
|
101
|
Abstract
|
Basic
|
Simple numbers but challenging
|
openMUSE/muse-512
| 0 |
|
U.S. 101
|
World Knowledge
|
Basic
|
Simple numbers but challenging
|
openMUSE/muse-512
| 0 |
|
commonsense
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
happiness
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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hope
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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insight
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
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inspiration
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
derision
|
Abstract
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
Salvador Dalí
|
People
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a shiba inu
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a handpalm
|
People
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
an espresso machine
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a propaganda poster
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
The Oriental Pearl
|
World Knowledge
|
Basic
|
CogView
|
openMUSE/muse-512
| 0 |
|
Ha Long Bay
|
World Knowledge
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
A Vietnam map
|
World Knowledge
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
A bowl of Pho
|
Food & Beverage
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a snail
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
brain coral
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a walnut
|
Produce & Plants
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a capybara
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a baby penguin
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a cup of boba
|
Food & Beverage
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a photo of san francisco's golden gate bridge
|
World Knowledge
|
Basic
|
DALL-E
|
openMUSE/muse-512
| 0 |
|
A picture of some food in the plate
|
Food & Beverage
|
Basic
|
VQ-Diffusion
|
openMUSE/muse-512
| 0 |
|
a chair
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
the Empire State Building
|
World Knowledge
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
the Sydney Opera House
|
World Knowledge
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a hedgehog
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a corgi
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a robot
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
robots
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a fall landscape
|
Outdoor Scenes
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a sunset
|
Outdoor Scenes
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a boat
|
Vehicles
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a fox
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a red cube
|
Illustrations
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a panda
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a space elevator
|
Artifacts
|
Basic
|
GLIDE
|
openMUSE/muse-512
| 0 |
|
a city
|
Outdoor Scenes
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a fog
|
Outdoor Scenes
|
Basic
| null |
openMUSE/muse-512
| 0 |
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a clock
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a phone
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
food
|
Food & Beverage
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a store front
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Outdoor Scenes
|
Basic
| null |
openMUSE/muse-512
| 0 |
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an armchair
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Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a teapot
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
an illustration of a teapot
|
Artifacts
|
Basic
|
DALL-E
|
openMUSE/muse-512
| 0 |
|
a tiger
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a bench
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
an orange
|
Produce & Plants
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a laptop
|
Artifacts
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
an owl
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a train
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Vehicles
|
Basic
| null |
openMUSE/muse-512
| 0 |
|
a cow
|
Animals
|
Basic
| null |
openMUSE/muse-512
| 0 |
End of preview. Expand
in Data Studio
Dataset Card for "muse_512"
```py
from PIL import Image
import torch
from muse import PipelineMuse, MaskGiTUViT
from datasets import Dataset, Features
from datasets import Image as ImageFeature
from datasets import Value, load_dataset
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = PipelineMuse.from_pretrained(
transformer_path="valhalla/research-run",
text_encoder_path="openMUSE/clip-vit-large-patch14-text-enc",
vae_path="openMUSE/vqgan-f16-8192-laion",
).to(device)
pipe.transformer = MaskGiTUViT.from_pretrained("valhalla/research-run-finetuned-journeydb", revision="06bcd6ab6580a2ed3275ddfc17f463b8574457da", subfolder="ema_model").to(device)
pipe.tokenizer.pad_token_id = 49407
if device == "cuda":
pipe.transformer.enable_xformers_memory_efficient_attention()
pipe.text_encoder.to(torch.float16)
pipe.transformer.to(torch.float16)
import PIL
def main():
print("Loading dataset...")
parti_prompts = load_dataset("nateraw/parti-prompts", split="train")
print("Loading pipeline...")
seed = 0
device = "cuda"
torch.manual_seed(0)
ckpt_id = "openMUSE/muse-512"
scale = 10
print("Running inference...")
main_dict = {}
for i in range(len(parti_prompts)):
sample = parti_prompts[i]
prompt = sample["Prompt"]
image = pipe(
prompt,
timesteps=16,
negative_text=None,
guidance_scale=scale,
temperature=(2, 0),
orig_size=(512, 512),
crop_coords=(0, 0),
aesthetic_score=6,
use_fp16=device == "cuda",
transformer_seq_len=1024,
use_tqdm=False,
)[0]
image = image.resize((256, 256), resample=PIL.Image.Resampling.LANCZOS)
img_path = f"/home/patrick/muse_images/muse_512_{i}.png"
image.save(img_path)
main_dict.update(
{
prompt: {
"img_path": img_path,
"Category": sample["Category"],
"Challenge": sample["Challenge"],
"Note": sample["Note"],
"model_name": ckpt_id,
"seed": seed,
}
}
)
def generation_fn():
for prompt in main_dict:
prompt_entry = main_dict[prompt]
yield {
"Prompt": prompt,
"Category": prompt_entry["Category"],
"Challenge": prompt_entry["Challenge"],
"Note": prompt_entry["Note"],
"images": {"path": prompt_entry["img_path"]},
"model_name": prompt_entry["model_name"],
"seed": prompt_entry["seed"],
}
print("Preparing HF dataset...")
ds = Dataset.from_generator(
generation_fn,
features=Features(
Prompt=Value("string"),
Category=Value("string"),
Challenge=Value("string"),
Note=Value("string"),
images=ImageFeature(),
model_name=Value("string"),
seed=Value("int64"),
),
)
ds_id = "diffusers-parti-prompts/muse512"
ds.push_to_hub(ds_id)
if __name__ == "__main__":
main()
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