Change Log for SD.Next
Update for 2023-12-29
- Control
- native implementation of all image control methods:
ControlNet, ControlNet XS, Control LLLite, T2I Adapters and IP Adapters - top-level Control next to Text and Image generate
- supports all variations of SD15 and SD-XL models
- supports Text, Image, Batch and Video processing
- for details and list of supported models and workflows, see Wiki documentation:
https://github.com/vladmandic/automatic/wiki/Control
- native implementation of all image control methods:
- Diffusers
- Segmind Vega model support
- small and fast version of SDXL, only 3.1GB in size!
- select from networks -> reference
- aMUSEd 256 and aMUSEd 512 model support
- lightweigt models that excel at fast image generation
- note: must select: settings -> diffusers -> generator device: unset
- select from networks -> reference
- Playground v1, Playground v2 256, Playground v2 512, Playground v2 1024 model support
- comparable to SD15 and SD-XL, trained from scratch for highly aesthetic images
- simply select from networks -> reference and use as usual
- BLIP-Diffusion
- img2img model that can replace subjects in images using prompt keywords
- download and load by selecting from networks -> reference -> blip diffusion
- in image tab, select
blip diffusion
script
- DemoFusion run your SDXL generations at any resolution!
- in Text tab select script -> demofusion
- note: GPU VRAM limits do not automatically go away so be careful when using it with large resolutions
in the future, expect more optimizations, especially related to offloading/slicing/tiling,
but at the moment this is pretty much experimental-only
- AnimateDiff
- overall improved quality
- can now be used with second pass - enhance, upscale and hires your videos!
- IP Adapter
- add support for ip-adapter-plus_sd15, ip-adapter-plus-face_sd15 and ip-adapter-full-face_sd15
- can now be used in xyz-grid
- Text-to-Video
- in text tab, select
text-to-video
script - supported models: ModelScope v1.7b, ZeroScope v1, ZeroScope v1.1, ZeroScope v2, ZeroScope v2 Dark, Potat v1
if you know of any other t2v models youd like to see supported, let me know! - models are auto-downloaded on first use
- note: current base model will be unloaded to free up resources
- in text tab, select
- Prompt scheduling now implemented for Diffusers backend, thanks @AI-Casanova
- Custom pipelines contribute by adding your own custom pipelines!
- for details, see fully documented example:
https://github.com/vladmandic/automatic/blob/dev/scripts/example.py
- for details, see fully documented example:
- Schedulers
- add timesteps range, changing it will make scheduler to be over-complete or under-complete
- add rescale betas with zero SNR option (applicable to Euler, Euler a and DDIM, allows for higher dynamic range)
- Inpaint
- improved quality when using mask blur and padding
- UI
- 3 new native UI themes: orchid-dreams, emerald-paradise and timeless-beige, thanks @illu_Zn
- more dynamic controls depending on the backend (original or diffusers)
controls that are not applicable in current mode are now hidden - allow setting of resize method directly in image tab
(previously via settings -> upscaler_for_img2img)
- Segmind Vega model support
- Optional
- FaceID face guidance during generation
- also based on IP adapters, but with additional face detection and external embeddings calculation
- calculates face embeds based on input image and uses it to guide generation
- simply select from scripts -> faceid
- experimental module: requirements must be installed manually:
pip install insightface ip_adapter
- Depth 3D image to 3D scene
- delivered as an extension, install from extensions tab
https://github.com/vladmandic/sd-extension-depth3d - creates fully compatible 3D scene from any image by using depth estimation
and creating a fully populated mesh - scene can be freely viewed in 3D in the UI itself or downloaded for use in other applications
- delivered as an extension, install from extensions tab
- ONNX/Olive
- major work continues in olive branch, see wiki for details, thanks @lshqqytiger
as a highlight, 4-5 it/s using DirectML on AMD GPU translates to 23-25 it/s using ONNX/Olive!
- major work continues in olive branch, see wiki for details, thanks @lshqqytiger
- FaceID face guidance during generation
- General
- new onboarding
- if no models are found during startup, app will no longer ask to download default checkpoint
instead, it will show message in UI with options to change model path or download any of the reference checkpoints - extra networks -> models -> reference section is now enabled for both original and diffusers backend
- if no models are found during startup, app will no longer ask to download default checkpoint
- support for Torch 2.1.2 (release) and Torch 2.3 (dev)
- Process create videos from batch or folder processing
supports GIF, PNG and MP4 with full interpolation, scene change detection, etc. - LoRA
- add support for block weights, thanks @AI-Casanova
example<lora:SDXL_LCM_LoRA:1.0:in=0:mid=1:out=0>
- add support for LyCORIS GLora networks
- add support for LoRA PEFT (Diffusers) networks
- add support for Lora-OFT (Kohya) and Lyco-OFT (Kohaku) networks
- reintroduce alternative loading method in settings:
lora_force_diffusers
- add support for
lora_fuse_diffusers
if using alternative method
use if you have multiple complex loras that may be causing performance degradation
as it fuses lora with model during load instead of interpreting lora on-the-fly
- add support for block weights, thanks @AI-Casanova
- CivitAI downloader allow usage of access tokens for download of gated or private models
- Extra networks new settting -> extra networks -> build info on first access
indexes all networks on first access instead of server startup - IPEX, thanks @disty0
- update to Torch 2.1
if you get file not found errors, setDISABLE_IPEXRUN=1
and run the webui with--reinstall
- built-in MKL and DPCPP for IPEX, no need to install OneAPI anymore
- StableVideoDiffusion is now supported with IPEX
- 8 bit support with NNCF on Diffusers backend
- fix IPEX Optimize not applying with Diffusers backend
- disable 32bit workarounds if the GPU supports 64bit
- add
DISABLE_IPEXRUN
andDISABLE_IPEX_1024_WA
environment variables - performance and compatibility improvements
- update to Torch 2.1
- OpenVINO, thanks @disty0
- 8 bit support for CPUs
- reduce System RAM usage
- update to Torch 2.1.2
- add Directory for OpenVINO cache option to System Paths
- remove Intel ARC specific 1024x1024 workaround
- HDR controls
- batch-aware for enhancement of multiple images or video frames
- available in image tab
- Logging
- additional TRACE logging enabled via specific env variables
see https://github.com/vladmandic/automatic/wiki/Debug for details - improved profiling
use with--debug --profile
- log output file sizes
- additional TRACE logging enabled via specific env variables
- Other
- API several minor but breaking changes to API behavior to better align response fields, thanks @Trojaner
- Inpaint add option
apply_overlay
to control if inpaint result should be applied as overlay or as-is
can remove artifacts and hard edges of inpaint area but also remove some details from original - chaiNNer fix
NaN
issues due to autocast - Upscale increase limit from 4x to 8x given the quality of some upscalers
- Extra Networks fix sort
- reduced default CFG scale from 6 to 4 to be more out-of-the-box compatibile with LCM/Turbo models
- disable google fonts check on server startup
- fix torchvision/basicsr compatibility
- fix styles quick save
- add hdr settings to metadata
- improve handling of long filenames and filenames during batch processing
- do not set preview samples when using via api
- avoid unnecessary resizes in img2img and inpaint
- safe handling of config updates avoid file corruption on I/O errors
- updated
cli/simple-txt2img.py
andcli/simple-img2img.py
scripts - save
params.txt
regardless of image save status - update built-in log monitor in ui, thanks @midcoastal
- major CHANGELOG doc cleanup, thanks @JetVarimax
- major INSTALL doc cleanup, thanks JetVarimax
- new onboarding
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