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wikiart_captions / create_wikiart.py

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	from datasets import load_dataset
	from torchvision.transforms import InterpolationMode
	from torchvision.transforms import functional as F


	def art2prompt(example):
	image = example["image"]
	image = F.resize(image, 512, InterpolationMode.LANCZOS)

	artist = example["artist_str"].replace("-", " ").title()
	if example["genre_str"] == "Unknown Genre":
	genre = "painting"
	else:
	genre = example["genre_str"].replace("_", " ")

	style = example["style_str"].replace("_", " ").lower()

	captions = [
	# a landscape in the style of Vincent Van Gogh
	f"a {genre} in the style of {artist}",
	# a landscape in the style of realism
	f"a {genre} in the style of {style}",
	# a realism painting by Vincent Van Gogh
	f"a {style} painting by {artist}",
	# a landscape by Vincent Van Gogh
	f"a {genre} by {artist}",
	]

	return {"text": captions, "image": image}


	dataset = load_dataset("huggan/wikiart", split="train")

	# map the integer labels to their strings
	dataset = dataset.map(
	lambda ex: {
	"artist_str": dataset.features["artist"].int2str(ex["artist"]),
	"genre_str": dataset.features["genre"].int2str(ex["genre"]),
	"style_str": dataset.features["style"].int2str(ex["style"]),
	},
	remove_columns=["artist", "genre", "style"],
	)

	# generate prompts from attributes
	dataset = dataset.map(
	art2prompt, remove_columns=["artist_str", "genre_str", "style_str"], num_proc=8, writer_batch_size=100
	)

	dataset.push_to_hub("fusing/wikiart_captions", split="train")