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Update __init__.py

Pallaidium_MacOS
tin2tin 12 months ago committed by GitHub
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1 changed files with 41 additions and 20 deletions
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  1. 61
      __init__.py

61
__init__.py
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@ -937,6 +937,16 @@ def input_strips_updated(self, context):
bpy.ops.lora.refresh_files()
if type == "text":
scene.input_strips = "input_strips"
if (
type == "movie"
and movie_model_card
== "stabilityai/stable-video-diffusion-img2vid"
) or (
type == "movie"
and movie_model_card
== "stabilityai/stable-video-diffusion-img2vid-xt"
):
scene.input_strips = "input_strips"
def output_strips_updated(self, context):
@ -967,6 +977,16 @@ def output_strips_updated(self, context):
scene.input_strips = "input_strips"
if type == "text":
scene.input_strips = "input_strips"
if (
type == "movie"
and movie_model_card
== "stabilityai/stable-video-diffusion-img2vid"
) or (
type == "movie"
and movie_model_card
== "stabilityai/stable-video-diffusion-img2vid-xt"
):
scene.input_strips = "input_strips"
class GeneratorAddonPreferences(AddonPreferences):
@ -2041,7 +2061,7 @@ class SEQUENCER_OT_generate_movie(Operator):
upscale.enable_model_cpu_offload()
# upscale.enable_vae_tiling()
# upscale.enable_vae_slicing()
upscale.unet.enable_forward_chunking(chunk_size=1, dim=1) # heavy:
#upscale.unet.enable_forward_chunking(chunk_size=1, dim=1) # heavy:
else:
upscale.to("cuda")
# Models for movie generation
@ -2139,7 +2159,7 @@ class SEQUENCER_OT_generate_movie(Operator):
if low_vram():
upscale.enable_model_cpu_offload()
upscale.unet.enable_forward_chunking(chunk_size=1, dim=1) # Heavy
#upscale.unet.enable_forward_chunking(chunk_size=1, dim=1) # Heavy
# upscale.enable_vae_slicing()
else:
upscale.to("cuda")
@ -2491,7 +2511,7 @@ class SEQUENCER_OT_generate_audio(Operator):
"Dependencies needs to be installed in the add-on preferences.",
)
return {"CANCELLED"}
show_system_console(True)
set_system_console_topmost(True)
@ -2517,7 +2537,7 @@ class SEQUENCER_OT_generate_audio(Operator):
# pipe.enable_vae_slicing()
else:
pipe.to("cuda")
# Musicgen
elif addon_prefs.audio_model_card == "facebook/musicgen-stereo-small":
from transformers import pipeline
@ -2531,7 +2551,7 @@ class SEQUENCER_OT_generate_audio(Operator):
)
if int(audio_length_in_s * 50) > 1503:
self.report({"INFO"}, "Maximum output duration is 30 sec.")
# Bark
elif addon_prefs.audio_model_card == "bark":
preload_models(
@ -2540,7 +2560,7 @@ class SEQUENCER_OT_generate_audio(Operator):
fine_use_gpu=True,
fine_use_small=True,
)
# Mustango
elif addon_prefs.audio_model_card == "declare-lab/mustango":
import IPython
@ -2553,13 +2573,13 @@ class SEQUENCER_OT_generate_audio(Operator):
model = DiffusionPipeline.from_pretrained(
"declare-lab/mustango"
) # , device="cuda:0", torch_dtype=torch.float16)
# Deadend
else:
print("Audio model not found.")
self.report({"INFO"}, "Audio model not found.")
return {"CANCELLED"}
# Main loop
for i in range(scene.movie_num_batch):
if i > 0:
@ -2610,7 +2630,7 @@ class SEQUENCER_OT_generate_audio(Operator):
# Write the combined audio to a file
write_wav(filename, rate, audio.transpose())
# Musicgen
elif addon_prefs.audio_model_card == "facebook/musicgen-stereo-small":
print("Generate: MusicGen Stereo")
@ -2837,7 +2857,7 @@ class SEQUENCER_OT_generate_image(Operator):
"None of the selected strips are movie, image, text or scene types.",
)
return {"CANCELLED"}
# LOADING MODELS
# models for inpaint
@ -2871,7 +2891,7 @@ class SEQUENCER_OT_generate_image(Operator):
pipe.enable_model_cpu_offload()
else:
pipe.to("cuda")
# Conversion img2img/vid2img.
elif (
do_convert
@ -2908,7 +2928,7 @@ class SEQUENCER_OT_generate_image(Operator):
# converter.enable_vae_slicing()
else:
converter.to("cuda")
# ControlNet & Illusion
elif (
image_model_card == "lllyasviel/sd-controlnet-canny"
@ -2949,7 +2969,7 @@ class SEQUENCER_OT_generate_image(Operator):
# pipe.enable_vae_slicing()
else:
pipe.to("cuda")
# Blip
elif image_model_card == "Salesforce/blipdiffusion":
print("Load: Blip Model")
@ -2970,7 +2990,7 @@ class SEQUENCER_OT_generate_image(Operator):
pipe = BlipDiffusionControlNetPipeline.from_pretrained(
"Salesforce/blipdiffusion-controlnet", torch_dtype=torch.float16
).to("cuda")
# OpenPose
elif image_model_card == "lllyasviel/sd-controlnet-openpose":
print("Load: OpenPose Model")
@ -3015,7 +3035,7 @@ class SEQUENCER_OT_generate_image(Operator):
# pipe.enable_vae_slicing()
else:
pipe.to("cuda")
# Scribble
elif image_model_card == "lllyasviel/control_v11p_sd15_scribble":
print("Load: Scribble Model")
@ -3057,7 +3077,7 @@ class SEQUENCER_OT_generate_image(Operator):
# pipe.enable_forward_chunking(chunk_size=1, dim=1)
else:
pipe.to("cuda")
# Dreamshaper
elif image_model_card == "Lykon/dreamshaper-7":
if do_convert:
@ -3072,7 +3092,7 @@ class SEQUENCER_OT_generate_image(Operator):
) # , custom_pipeline="latent_consistency_txt2img"
pipe.to(torch_device="cuda", torch_dtype=torch.float16)
# Wuerstchen
elif image_model_card == "warp-ai/wuerstchen":
print("Load: Würstchen Model")
@ -3095,7 +3115,7 @@ class SEQUENCER_OT_generate_image(Operator):
pipe.enable_model_cpu_offload()
else:
pipe.to("cuda")
# DeepFloyd
elif image_model_card == "DeepFloyd/IF-I-M-v1.0":
print("Load: DeepFloyd Model")
@ -3116,7 +3136,7 @@ class SEQUENCER_OT_generate_image(Operator):
stage_1.enable_model_cpu_offload()
else:
stage_1.to("cuda")
# stage 2
stage_2 = DiffusionPipeline.from_pretrained(
"DeepFloyd/IF-II-M-v1.0",
@ -3128,7 +3148,7 @@ class SEQUENCER_OT_generate_image(Operator):
stage_2.enable_model_cpu_offload()
else:
stage_2.to("cuda")
# stage 3
safety_modules = {
"feature_extractor": stage_1.feature_extractor,
@ -3239,6 +3259,7 @@ class SEQUENCER_OT_generate_image(Operator):
)
pipe.set_adapters(enabled_names, adapter_weights=enabled_weights)
print("Load LoRAs: " + " ".join(enabled_names))
# load refiner model if chosen.
if do_refine:
print(

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