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Add: AnimateDiff, LCM

Installation_fix
tin2tin 1 year ago committed by GitHub
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1 changed files with 93 additions and 62 deletions
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  1. 153
      __init__.py

153
__init__.py
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@ -999,7 +999,7 @@ class GeneratorAddonPreferences(AddonPreferences):
"Segmind SSD-1B (1024x1024)",
"segmind/SSD-1B",
),
#("SimianLuo/LCM_Dreamshaper_v7", "LCM Dreamshaper v7 (768 x 768)", "SimianLuo/LCM_Dreamshaper_v7"), Properly needs a torch update?
#("SimianLuo/LCM_Dreamshaper_v7", "LCM Dreamshaper v7 (768 x 768)", "SimianLuo/LCM_Dreamshaper_v7"), #Properly needs a torch update?
("warp-ai/wuerstchen", "Würstchen (1024x1024)", "warp-ai/wuerstchen"),
("DeepFloyd/IF-I-M-v1.0", "DeepFloyd/IF-I-M-v1.0", "DeepFloyd/IF-I-M-v1.0"),
(
@ -1440,8 +1440,6 @@ class LORA_OT_RefreshFiles(Operator):
file_item.name = filename.replace(".safetensors", "")
file_item.enabled = False
file_item.weight_value = 1.0
else:
print(filename)
return {"FINISHED"}
@ -1605,18 +1603,6 @@ class SEQUENCER_PT_pallaidium_panel(Panel): # UI
row.prop(context.scene, "movie_use_random", text="", icon="QUESTION")
sub_row.active = not context.scene.movie_use_random
if type != "audio":
if type == "movie" or (
type == "image"
and image_model_card != "lllyasviel/sd-controlnet-canny"
and image_model_card != "lllyasviel/sd-controlnet-openpose"
and image_model_card != "lllyasviel/control_v11p_sd15_scribble"
and image_model_card != "monster-labs/control_v1p_sd15_qrcode_monster"
and image_model_card != "Salesforce/blipdiffusion"
):
col = col.column(heading="FreeU", align=True)
col.prop(context.scene, "use_freeU", text="")
if type == "movie" and (
movie_model_card == "cerspense/zeroscope_v2_dark_30x448x256"
or movie_model_card == "cerspense/zeroscope_v2_576w"
@ -1626,11 +1612,26 @@ class SEQUENCER_PT_pallaidium_panel(Panel): # UI
col.prop(context.scene, "video_to_video", text="2x")
if type == "image":
col = col.column(heading="Refine", align=True)
col.prop(context.scene, "refine_sd", text="Image")
col = col.column(heading="Enhance", align=True)
col.prop(context.scene, "refine_sd", text="SD Refine")
sub_col = col.row()
sub_col.active = context.scene.refine_sd
if type != "audio":
if type == "movie" or (
type == "image"
and image_model_card != "lllyasviel/sd-controlnet-canny"
and image_model_card != "lllyasviel/sd-controlnet-openpose"
and image_model_card != "lllyasviel/control_v11p_sd15_scribble"
and image_model_card != "monster-labs/control_v1p_sd15_qrcode_monster"
and image_model_card != "Salesforce/blipdiffusion"
):
#col = col.column(heading="FreeU", align=True)
row = col.row()
row.prop(context.scene, "use_freeU", text="FreeU")
if type == "image":
row.prop(context.scene, "use_lcm", text="LCM")
# Output.
layout = self.layout
layout.use_property_split = True
@ -2485,28 +2486,29 @@ class SEQUENCER_OT_generate_image(Operator):
if not seq_editor:
scene.sequence_editor_create()
# try:
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
from diffusers.utils import pt_to_pil
import torch
import requests
from diffusers.utils import load_image
import numpy as np
import PIL
import cv2
from PIL import Image
from .free_lunch_utils import (
register_free_upblock2d,
register_free_crossattn_upblock2d,
)
# from compel import Compel
# except ModuleNotFoundError:
# print("Dependencies needs to be installed in the add-on preferences.")
# self.report(
# {"INFO"},
# "Dependencies needs to be installed in the add-on preferences.",
# )
# return {"CANCELLED"}
try:
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
from diffusers.utils import pt_to_pil
import torch
import requests
from diffusers.utils import load_image
import numpy as np
import PIL
import cv2
from PIL import Image
from .free_lunch_utils import (
register_free_upblock2d,
register_free_crossattn_upblock2d,
)
#from compel import Compel
except ModuleNotFoundError:
print("Dependencies needs to be installed in the add-on preferences.")
self.report(
{"INFO"},
"Dependencies needs to be installed in the add-on preferences.",
)
return {"CANCELLED"}
# clear the VRAM
if torch.cuda.is_available():
torch.cuda.empty_cache()
@ -2649,7 +2651,12 @@ class SEQUENCER_OT_generate_image(Operator):
safety_checker=None,
) # safety_checker=None,
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
if scene.use_lcm:
from diffusers import LCMScheduler
pipe.load_lora_weights("latent-consistency/lcm-lora-sdv1-5")
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
else:
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
if low_vram():
pipe.enable_xformers_memory_efficient_attention()
@ -2706,7 +2713,12 @@ class SEQUENCER_OT_generate_image(Operator):
torch_dtype=torch.float16,
) # safety_checker=None,
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
if scene.use_lcm:
from diffusers import LCMScheduler
pipe.load_lora_weights("latent-consistency/lcm-lora-sdv1-5")
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
else:
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
if low_vram():
pipe.enable_xformers_memory_efficient_attention()
@ -2725,14 +2737,9 @@ class SEQUENCER_OT_generate_image(Operator):
StableDiffusionControlNetPipeline,
UniPCMultistepScheduler,
)
checkpoint = "lllyasviel/control_v11p_sd15_scribble"
processor = HEDdetector.from_pretrained("lllyasviel/Annotators")
controlnet = ControlNetModel.from_pretrained(
checkpoint, torch_dtype=torch.float16
)
checkpoint = "lllyasviel/control_v11p_sd15_scribble"
controlnet = ControlNetModel.from_pretrained(checkpoint, torch_dtype=torch.float16)
pipe = StableDiffusionControlNetPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
@ -2740,7 +2747,12 @@ class SEQUENCER_OT_generate_image(Operator):
torch_dtype=torch.float16,
)
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
if scene.use_lcm:
from diffusers import LCMScheduler
pipe.load_lora_weights("latent-consistency/lcm-lora-sdv1-5")
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
else:
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
if low_vram():
# torch.cuda.set_per_process_memory_fraction(0.95) # 6 GB VRAM
@ -2759,7 +2771,7 @@ class SEQUENCER_OT_generate_image(Operator):
)
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("SimianLuo/LCM_Dreamshaper_v7", custom_pipeline="latent_consistency_txt2img", torch_dtype=torch.float32)
pipe = DiffusionPipeline.from_pretrained("SimianLuo/LCM_Dreamshaper_v7", custom_pipeline="latent_consistency_txt2img", torch_dtype=torch.float16)
# if low_vram():
# # torch.cuda.set_per_process_memory_fraction(0.95) # 6 GB VRAM
@ -2768,7 +2780,7 @@ class SEQUENCER_OT_generate_image(Operator):
# else:
#pipe.to(torch_device="cuda")
#pipe.enable_vae_slicing()
pipe.to(torch_device="cuda")
pipe.to(torch_device="cuda", torch_dtype=torch.float16)
# if low_vram():
# # torch.cuda.set_per_process_memory_fraction(0.95) # 6 GB VRAM
# #pipe.enable_model_cpu_offload()
@ -2896,7 +2908,6 @@ class SEQUENCER_OT_generate_image(Operator):
enabled_items = None
if image_model_card == "stabilityai/stable-diffusion-xl-base-1.0":
#from diffusers import LCMScheduler
vae = AutoencoderKL.from_pretrained(
"madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
)
@ -2906,17 +2917,30 @@ class SEQUENCER_OT_generate_image(Operator):
torch_dtype=torch.float16,
variant="fp16",
)
#pipe.load_lora_weights("latent-consistency/lcm-lora-sdxl")
#pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
else:
pipe = DiffusionPipeline.from_pretrained(
image_model_card,
torch_dtype=torch.float16,
variant="fp16",
)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(
pipe.scheduler.config
)
if scene.use_lcm:
print("Use LCM: True")
from diffusers import LCMScheduler
if image_model_card == "stabilityai/stable-diffusion-xl-base-1.0":
pipe.load_lora_weights("latent-consistency/lcm-lora-sdxl")
elif image_model_card == "segmind/SSD-1B":
pipe.load_lora_weights("latent-consistency/lcm-lora-ssd-1b")
pipe.fuse_lora()
else:
pipe.load_lora_weights("latent-consistency/lcm-lora-sdv1-5")
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
else:
print("Use LCM: False")
pipe.scheduler = DPMSolverMultistepScheduler.from_config(
pipe.scheduler.config
)
pipe.watermark = NoWatermark()
@ -3132,11 +3156,13 @@ class SEQUENCER_OT_generate_image(Operator):
#negative_prompt=negative_prompt,
num_inference_steps=image_num_inference_steps,
guidance_scale=image_num_guidance,
#lcm_origin_steps=50,
height=y,
width=x,
lcm_origin_steps=50,
#height=y,
#width=x,
#generator=generator,
).images[0]
output_type="pil",
).images
# OpenPose
elif image_model_card == "lllyasviel/sd-controlnet-openpose":
@ -3913,6 +3939,11 @@ def register():
default=0,
)
bpy.types.Scene.use_lcm = bpy.props.BoolProperty(
name="use_lcm",
default=0,
)
for cls in classes:
bpy.utils.register_class(cls)
# LoRA

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