File size: 6,773 Bytes
7791147 9c2ebfa 88a6572 7791147 bd5c559 f735690 486819e 26e15e7 f735690 486819e f735690 051814d 106209a aeaf650 fa917d3 1c17828 fb15d50 051814d bd5c559 12b4354 bd5c559 5bda548 61ab4dd 98ed851 bd5c559 1c17828 fb15d50 1c17828 e26956b 7d6b06b 61ab4dd a662231 61ab4dd a662231 61ab4dd a662231 61ab4dd f729977 98ed851 f729977 98ed851 f729977 98ed851 f729977 98ed851 f729977 98ed851 f729977 98ed851 c582e3d aec695a 0fd54be c582e3d aec695a c582e3d aec695a c582e3d aec695a 9d864f8 9a01103 be7dd21 9a01103 42a30c9 0154828 50e4188 0154828 50e4188 0154828 044a8f1 278e56a ea80b80 278e56a ac0aee6 278e56a ac0aee6 164b35a ac0aee6 164b35a ac0aee6 164b35a e4f1546 c0eab4a e4f1546 1c17828 e4f1546 2aaba44 9d17708 2aaba44 9d17708 88a6572 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 |
---
license: cc-by-nc-sa-4.0
library_name: diffusers
---
Thank you for support my work.
<a href="https://www.buymeacoffee.com/bdsqlsz"><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a new graphics card&emoji=😋&slug=bdsqlsz&button_colour=40DCA5&font_colour=ffffff&font_family=Cookie&outline_colour=000000&coffee_colour=FFDD00" /></a>
https://www.buymeacoffee.com/bdsqlsz
Support list will show in main page.
# Support List
```
DiamondShark
Yashamon
t4ggno
Someone
kgmkm_mkgm
yacong
```
Pre-trained models and output samples of ControlNet-LLLite form bdsqlsz
# Inference with ComfyUI: https://github.com/kohya-ss/ControlNet-LLLite-ComfyUI Not Controlnet Nodes!
For 1111's Web UI, [sd-webui-controlnet](https://github.com/Mikubill/sd-webui-controlnet) extension supports ControlNet-LLLite.
Training: https://github.com/kohya-ss/sd-scripts/blob/sdxl/docs/train_lllite_README.md
The recommended preprocessing for the animeface model is [Anime-Face-Segmentation](https://github.com/siyeong0/Anime-Face-Segmentation)
# Models
## Trained on anime model
AnimeFaceSegment、Normal、T2i-Color/Shuffle、lineart_anime_denoise、recolor_luminance
Base Model use[Kohaku-XL](https://civitai.com/models/136389?modelVersionId=150441)
MLSD
Base Model use[ProtoVision XL - High Fidelity 3D](https://civitai.com/models/125703?modelVersionId=144229)
# Japanese Introduction
https://note.com/kagami_kami/n/nf71099b6abe3
Thank kgmkm_mkgm for introducing these controlllite models and testing.
# Samples
## AnimeFaceSegmentV2
![source 1](./sample/00015-882327104.png)
![sample 1](./sample/grid-0000-656896882.png)
![source 2](./sample/00081-882327170.png)
![sample 2](./sample/grid-0000-2857388239.png)
## MLSDV2
![source 1](./sample/0-73.png)
![preprocess 1](./sample/mlsd-0000.png)
![sample 1](./sample/grid-0001-496872924.png)
![source 2](./sample/0-151.png)
![preprocess 2](./sample/mlsd-0001.png)
![sample 2](./sample/grid-0002-906633402.png)
## Normal_Dsine
![source](./sample/f49e5ae5b9c86ffab78f48e71d72f2f151248e33f10c54c498c7ca4be0dc5025.jpg)
![preprocess 1](./sample/normal_dsine-0022.png)
![sample 1](./sample/grid-0018-3079334279.png)
![sample 2](./sample/grid-0002-1006844163.png)
## T2i-Color/Shuffle
![source 1](./sample/sample_0_525_c9a3a20fa609fe4bbf04.png)
![preprocess 1](./sample/color-0008.png)
![sample 1](./sample/grid-0017-751452001.jpg)
![source 2](./sample/F8LQ75WXoAETQg3.jpg)
![preprocess 2](./sample/color-0009.png)
![sample 2](./sample/grid-0018-2976518185.jpg)
## Lineart_Anime_Denoise
![source 1](./sample/20230826131545.png)
![preprocess 1](./sample/lineart_anime_denoise-1308.png)
![sample 1](./sample/grid-0028-1461058306.png)
![source 2](./sample/Snipaste_2023-08-10_23-33-53.png)
![preprocess 2](./sample/lineart_anime_denoise-1309.png)
![sample 2](./sample/grid-0030-1612754720.png)
## Recolor_Luminance
![source 1](./sample/F8LQ75WXoAETQg3.jpg)
![preprocess 1](./sample/recolor_luminance-0014.png)
![sample 1](./sample/grid-0060-2359545755.png)
![source 2](./sample/Snipaste_2023-08-15_02-38-05.png)
![preprocess 2](./sample/recolor_luminance-0016.png)
![sample 2](./sample/grid-0061-448628292.png)
## Canny
![source 1](./sample/Snipaste_2023-08-10_23-33-53.png)
![preprocess 1](./sample/canny-0034.png)
![sample 1](./sample/grid-0100-2599077425.png)
![source 2](./sample/00021-210474367.jpeg)
![preprocess 2](./sample/canny-0021.png)
![sample 2](./sample/grid-0084-938772089.png)
## DW_OpenPose
![preprocess 1](./sample/dw_openpose_full-0015.png)
![sample 1](./sample/grid-0015-4163265662.png)
![preprocess 2](./sample/dw_openpose_full-0030.png)
![sample 2](./sample/grid-0030-2839828192.png)
## Tile_Anime
![source 1](./sample/03476-424776255.png)
![sample 1](./sample/grid-0008-3461355229.png)
![sample 2](./sample/grid-0016-1162724588.png)
![sample 3](./sample/00094-188618111.png)
和其他模型不同,我需要简单解释一下tile模型的用法。
总的来说,tile模型有三个用法,
1、不输入任何提示词,它可以直接还原参考图的大致效果,然后略微重新修改局部细节,可以用于V2V。(图2)
2、权重设定为0.55~0.75,它可以保持原本构图和姿势的基础上,接受提示词和LoRA的修改。(图3)
3、使用配合放大效果,对每个tiling进行细节增加的同时保持一致性。(图4)
因为训练时使用的数据集为动漫2D/2.5D模型,所以目前对真实摄影风格的重绘效果并不好,需要等待完成最终版本。
Unlike other models, I need to briefly explain the usage of the tile model.
In general, there are three uses for the tile model,
1. Without entering any prompt words, it can directly restore the approximate effect of the reference image and then slightly modify local details. It can be used for V2V (Figure 2).
2. With a weight setting of 0.55~0.75, it can maintain the original composition and pose while accepting modifications from prompt words and LoRA (Figure 3).
3. Use in conjunction with magnification effects to increase detail for each tiling while maintaining consistency (Figure 4).
Since the dataset used during training is an anime 2D/2.5D model, currently, its repainting effect on real photography styles is not good; we will have to wait until completing its final version.
![xyz](./sample/xyz_grid-0001-3957894094.png)
目前释放出了α和β两个版本,分别对应1、2以及1、3的用法。
其中α用于姿势、构图迁移,它的泛化性很强,可以和其他LoRA结合使用。
而β用于保持一致性和高清放大,它对条件图片更敏感。
好吧,α是prompt更重要的版本,而β是controlnet更重要的版本。
Currently, two versions, α and β, have been released, corresponding to the usage of 1、2 and 1、3 respectively.
The α version is used for pose and composition transfer, with strong generalization capabilities that can be combined with other LoRA systems.
On the other hand, the β version is used for maintaining consistency and high-definition magnification; it is more sensitive to conditional images.
In summary, α is a more important version for prompts while β is a more important version for controlnet.
## Tile_Realistic
Thank for all my supporter.
```
DiamondShark
Yashamon
t4ggno
Someone
kgmkm_mkgm
```
Even though I broke my foot last week, I still insisted on training the realistic version out.
![source 1](./sample/OIP.jpg)
![sample 1](./sample/grid-0000.png)
You can compared with SD1.5 tile below here↓
![sample 2](./sample/grid-0002.png)
For base model using juggernautXL series,so i recommend use their model or merge with it.
Here is comparing with other SDXL model.
![sample 2](./sample/xyz_grid-0000-948596933.png) |