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BangumiBase/anohimitahananonamaewobokutachiwamadashiranai

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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/anohimitahananonamaewobokutachiwamadashiranai
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资源简介:
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Ano Hi Mita Hana No Namae Wo Bokutachi Wa Mada Shiranai. This is the image base of bangumi Ano Hi Mita Hana no Namae wo Bokutachi wa Mada Shiranai., we detected 19 characters, 1523 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 | 183 | [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 | 29 | [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 | 121 | [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 | 40 | [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 | 22 | [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 | 20 | [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 | 462 | [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 | 21 | [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 | 154 | [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 | 10 | [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 | 131 | [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 | 12 | [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 | 8 | [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 | 14 | [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 | 221 | [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 | 15 | [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 | 14 | [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 | 11 | [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) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | noise | 35 | [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

数据集概述

数据集名称

Bangumi Image Base of Ano Hi Mita Hana No Namae Wo Bokutachi Wa Mada Shiranai.

数据集描述

该数据集包含19个角色和1523张图片。数据集的完整下载链接为all.zip

数据质量

请注意,这些图像数据集并不保证100%清洗干净,可能存在噪声。如果计划手动训练模型,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)。

角色预览

以下是各个角色的图片数量和下载链接:

# 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
0 183 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
1 29 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
2 121 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
3 40 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
4 22 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
5 20 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
6 462 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
7 21 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
8 154 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
9 10 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
10 131 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
11 12 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
12 8 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
13 14 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
14 221 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
15 15 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
16 14 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
17 11 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
noise 35 Download preview 1 preview 2 preview 3 preview 4 preview 5 preview 6 preview 7 preview 8
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