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BangumiBase/rakudaikishinocavalry

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Hugging Face2024-03-20 更新2024-03-04 收录
下载链接:
https://hf-mirror.com/datasets/BangumiBase/rakudaikishinocavalry
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资源简介:
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Rakudai Kishi No Cavalry This is the image base of bangumi Rakudai Kishi no Cavalry, we detected 20 characters, 1314 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 305 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 19 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 365 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 41 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 62 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 44 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 47 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 23 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 105 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 9 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 18 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 20 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 9 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 10 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 9 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 9 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 37 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 6 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | N/A | N/A | | 18 | 19 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | noise | 157 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
提供机构:
BangumiBase
原始信息汇总

Bangumi Image Base of Rakudai Kishi No Cavalry

数据集概述

  • 名称: Bangumi Image Base of Rakudai Kishi No Cavalry
  • 标签: art
  • 大小类别: 1K<n<10K
  • 许可证: MIT

数据集详情

  • 总图片数: 1314张
  • 角色数: 20个
  • 完整数据集下载链接: all.zip

角色预览

# 图片数量 下载链接 预览1 预览2 预览3 预览4 预览5 预览6 预览7 预览8
0 305 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
1 19 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
2 365 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
3 41 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
4 62 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
5 44 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
6 47 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
7 23 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
8 105 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
9 9 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
10 18 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
11 20 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
12 9 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
13 10 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
14 9 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
15 9 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
16 37 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
17 6 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 N/A N/A
18 19 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
noise 157 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8

注意事项

  • 数据质量: 这些图片库不保证100%干净,可能存在噪声。
  • 预处理建议: 如果打算手动训练模型,建议对下载的数据集进行必要的预处理,以消除潜在的噪声样本(约1%的概率)。
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