Derp Learning

Derp Learning 

использую ИИ не по назначению

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Stable WarpFusion v0.24 - FreeU, inpaint-softedge, temporal-depth experimental controlnets

Changelog:
- add FreeU Hack from https://huggingface.co/papers/2309.11497
- add option to apply FreeU before or after controlnet outputs
- add inpaint-softedge and temporal-depth controlnet models
- auto-download inpaint-softedge and temporal-depth checkpoints
- fix sd21 lineart model not working
- refactor get_controlnet_annotations a bit
- add inpaint-softedge and temporal-depth controlnet preprocessors
- fix controlnet preview (next_frame error)
- fix dwpose 'final_boxes' error for frames with no people
- move width_height to video init cell to avoid people forgetting to run it to - update width_height
- fix xformers version
- fix flow preview error for fewer than 10 frames
- fix pillow errors (UnidentifiedImageError: cannot identify image file)
- fix timm import error (isDirectory error)
- deprecate v2_depth model (use depth controlnet instead)
- fix pytorch dependencies error
- fix zoe depth error
- move installers to github repo
FreeU
GUI - misc - apply_freeu_after_control, do_freeunet
This hack lowers the effect of stablediffusion unet residual skip-connections, prioritizing the core concepts in the image over low-frequency details. As you can see in the video, with FreeU on the image seems less cluttered, but still has enough high-frequency details. apply_freeu_after_control applies the hack after getting input from controlnets, which for me was producing a bit worse results.
Inpaint-softedge controlnet
I've experimented with mixed-input controlnets. This works the same way inpaint controlnet does + it uses softedge input for the inpainted area, so it relies not only on the masked area surroundings, but also on softedge filter output for the masked area, which gives a little more control.
Temporal-depth controlnet
This one takes previous frame + current frame depth + next frame depth as its inputs
Those controlnets are experimental, and you can try replacing some controlnet pairs with them, like replace depth with temporal-depth, or replace inpaint with inpaint-softedge
Local install guide:
https://github.com/Sxela/WarpFusion/blob/main/README.md
Guides made by users:
05.05.2023, v0.10 Video to AI Animation Tutorial For Beginners: Stable WarpFusion + Controlnet | MDMZ
11.05.2023, v0.11 How to use Stable Warp Fusion13.05.2023, v0.8 Warp Fusion Local Install Guide (v0.8.6) with Diffusion Demonstration
14.05.2023, v0.12 Warp Fusion Alpha Masking Tutorial | Covers Both Auto-Masking and Custom Masking23.05.2023, v0.12 STABLE WARPFUSION TUTORIAL - Colab Pro & Local Install
15.06.2023, v0.13 AI Animation out of Your Video: Stable Warpfusion Guide (Google Colab & Local Intallation)17.06.2023, v0.14 Stable Warpfusion Tutorial: Turn Your Video to an AI Animation
21.06.2023, v0.14 Avoiding Common Problems with Stable Warpfusion21.06.2023, v0.15 Warp Fusion: Step by Step Tutorial
04.07.2023, v0.15 Intense AI Video Maker (Stable WarpFusion Tutorial)15.08.2023, v0.17 BEST Laptop for AI ( SDXL & Stable Warpfusion ) ft. RTX 4090 - Make AI Art FREE and FAST!
YouTube playlist with settings:
https://www.youtube.com/watch?v=wvvcWm4Snmc&list=PL2cEnissQhlCUgjnGrdvYMwUaDkGemLGq
ipynb
stable_warpfusion_v0_24_6.ipynb757.19 Kb
How to use SDXL Model?
Dev Brat, in load model cell select control_multi_sdxl model version, and provide an sdxl checkpoint. Make sure to use no_half_vae or use a specific fixed vae for sdxl
Hi Alex, I have a 3080 16 GB GPU (Laptop), I tried as per your advice, but the cell keeps on running without any error for a very long time. Can I get any tutorial on the SDXL checkpoint, along with Lora XL?
Dev Brat, you mean the render takes too long? try lowering resolution and number of controlnets
Подскажите пожалуйста у меня RXT 3090 24GB + 5900x + 64 GB Ram 3200. Видео делается крайне долго, есть ли возможность ускорить процесс? GPU грузится максимум на 20% CPU на 10-15%. Спасибо большое.
Илья Пискурёв, 
Gui - misc -> offload model
Gui -> controlnet -> save controlnet annotations
Tiled vae - ячейка в разделе extra featur
Derp Learning, Спасибо сделал. 5 Секунд обрабатывается около 30-35 минут. Было примерно в такой же скорости около 45 минут.
у меня вопрос, а где можно качнуть актуальные ControlNet?, я загрузила ваш блокнот на colab, ссылку директории с моделями ControlNet указала на своем гугл диске и, в итоге, вылезает такая ошибка
Derp Learning, stable_warpfusion_v0_25_6_animatediff
Derp Learning, 
Мне скинули актуальный архив ControlNet, ошибка та же самая, значит я что-то делаю не так
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