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  This dataset includes ~2500 images of fantasy RPG character art. This dataset has a distribution of races and classes, though only races are annotated right now.
 
 
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  Additionally, BLIP captions were generated for all examples.
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  Thus, there are two datasets- one with the human generated race annotation formatted as 'D&D Character, {race}'
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  BLIP captions are formatted as 'D&D Character, {race} {caption}' for example: 'D&D Character, drow a woman with horns and horns'
 
 
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  Distribution of races:
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  ({'kenku': 31,
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  'drow': 162,
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  'tiefling': 285,
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- 'dwarf': 116,
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- 'dragonborn': 110,
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- 'gnome': 72,
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- 'orc': 184,
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- 'aasimar': 74,
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- 'kobold': 61,
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- 'aarakocra': 24,
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- 'tabaxi': 123,
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- 'genasi': 126,
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- 'human': 652,
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  'elf': 190,
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  'goblin': 80,
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  'halfling': 52,
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  'centaur': 22,
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  'firbolg': 76,
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  'goliath': 35})
 
 
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  There is a high chance some images are mislabelled! Please feel free to enrich this dataset with whatever attributes you think might be useful!
 
1
  This dataset includes ~2500 images of fantasy RPG character art. This dataset has a distribution of races and classes, though only races are annotated right now.
2
+
3
+
4
  Additionally, BLIP captions were generated for all examples.
5
  Thus, there are two datasets- one with the human generated race annotation formatted as 'D&D Character, {race}'
6
  BLIP captions are formatted as 'D&D Character, {race} {caption}' for example: 'D&D Character, drow a woman with horns and horns'
7
+
8
+
9
  Distribution of races:
10
  ({'kenku': 31,
11
  'drow': 162,
12
  'tiefling': 285,
13
+ 'dwarf': 116,
14
+ 'dragonborn': 110,
15
+ 'gnome': 72,
16
+ 'orc': 184,
17
+ 'aasimar': 74,
18
+ 'kobold': 61,
19
+ 'aarakocra': 24,
20
+ 'tabaxi': 123,
21
+ 'genasi': 126,
22
+ 'human': 652,
23
  'elf': 190,
24
  'goblin': 80,
25
  'halfling': 52,
26
  'centaur': 22,
27
  'firbolg': 76,
28
  'goliath': 35})
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+
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+
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  There is a high chance some images are mislabelled! Please feel free to enrich this dataset with whatever attributes you think might be useful!