Public/automatic
1
0
Fork 0
mirror of https://github.com/vladmandic/automatic synced 2026-09-19 09:14:35 +02:00
Code Issues Packages Projects Releases Wiki Activity

flux extra controlnets and differential diffusion

Browse Source 
Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2024-10-16 10:10:58 -04:00
parent 18c0ab7297
commit e746871962
7 changed files with 35 additions and 31 deletions
Download Patch File Download Diff File Expand all files Collapse all files
scripts/differential_diffusion.py
+13 -20
View File
@@ -9,32 +9,20 @@ sdnext implementation follows after pipeline-end
import inspect
import hashlib
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
from packaging import version
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
import torchvision
import PIL.Image
import numpy as np
import torch
import torchvision
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers.image_processor import VaeImageProcessor
from diffusers.loaders import FromSingleFileMixin, LoraLoaderMixin, TextualInversionLoaderMixin
from diffusers.models import AutoencoderKL, UNet2DConditionModel
from diffusers.models.attention_processor import (
AttnProcessor2_0,
FusedAttnProcessor2_0,
XFormersAttnProcessor,
)
from diffusers.models.attention_processor import AttnProcessor2_0, FusedAttnProcessor2_0, XFormersAttnProcessor
from diffusers.configuration_utils import FrozenDict
from diffusers.schedulers import KarrasDiffusionSchedulers
from diffusers.utils import (
PIL_INTERPOLATION,
logging,
deprecate,
is_accelerate_available,
is_accelerate_version,
replace_example_docstring,
)
from diffusers.utils import PIL_INTERPOLATION, logging, deprecate, is_accelerate_available, is_accelerate_version, replace_example_docstring
from diffusers.utils.torch_utils import randn_tensor
from diffusers.pipelines.pipeline_utils import DiffusionPipeline
from diffusers.pipelines.stable_diffusion_xl.pipeline_output import StableDiffusionXLPipelineOutput
@@ -1921,7 +1909,7 @@ class Script(scripts.Script):
def run(self, p: processing.StableDiffusionProcessingImg2Img, enabled, strength, invert, model, image): # pylint: disable=arguments-differ
if not enabled:
return
if shared.sd_model_type != 'sdxl' and shared.sd_model_type != 'sd':
if shared.sd_model_type not in ['sdxl', 'sd', 'f1']:
shared.log.error(f'Differential-diffusion: incorrect base model: {shared.sd_model.__class__.__name__}')
return
if not hasattr(p, 'init_images') or len(p.init_images) == 0:
@@ -1936,6 +1924,8 @@ class Script(scripts.Script):
orig_pipeline = shared.sd_model
pipe = None
try:
# shared.sd_model = diffusers.StableDiffusionPipeline.from_pipe(shared.sd_model, **{ 'custom_pipeline': 'kohya_hires_fix', 'high_res_fix': high_res_fix })
# from examples.community.pipeline_stable_diffusion_xl_differential_img2img import StableDiffusionXLDifferentialImg2ImgPipeline
diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING["StableDiffusionXLDiffImg2ImgPipeline"] = StableDiffusionXLDiffImg2ImgPipeline
diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING["StableDiffusionDiffImg2ImgPipeline"] = StableDiffusionDiffImg2ImgPipeline
if shared.sd_model_type == 'sdxl':
@@ -1959,6 +1949,9 @@ class Script(scripts.Script):
safety_checker=None,
requires_safety_checker=False,
)
elif shared.sd_model_type == 'f1':
pipe = diffusers.StableDiffusionPipeline.from_pipe(shared.sd_model, **{ 'custom_pipeline': 'pipeline_flux_differential_img2img' })
diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING["FluxDifferentialImg2ImgPipeline"] = pipe.__class__
sd_models.copy_diffuser_options(pipe, shared.sd_model)
sd_models.set_diffuser_options(pipe)
p.task_args['image'] = image_init