# https://modelscope.cn/models/damo/text-to-video-synthesis/summary
bl_info = {
" name " : " Generative AI " ,
" author " : " tintwotin " ,
" version " : ( 1 , 0 ) ,
" blender " : ( 3 , 4 , 0 ) ,
" location " : " Video Sequence Editor > Sidebar > Generative AI " ,
" description " : " Generate media in the VSE " ,
" category " : " Sequencer " ,
}
import bpy , ctypes , random
from bpy . types import Operator , Panel , AddonPreferences
from bpy . props import StringProperty , BoolProperty , EnumProperty , IntProperty
import site , platform
import subprocess
import sys , os , aud
import string
from os . path import dirname , realpath , isfile
import shutil
os_platform = platform . system ( ) # 'Linux', 'Darwin', 'Java', 'Windows'
def show_system_console ( show ) :
if os_platform == " Windows " :
# https://docs.microsoft.com/en-us/windows/win32/api/winuser/nf-winuser-showwindow
SW_HIDE = 0
SW_SHOW = 5
ctypes . windll . user32 . ShowWindow (
ctypes . windll . kernel32 . GetConsoleWindow ( ) , SW_SHOW #if show else SW_HIDE
)
def set_system_console_topmost ( top ) :
if os_platform == " Windows " :
# https://docs.microsoft.com/en-us/windows/win32/api/winuser/nf-winuser-setwindowpos
HWND_NOTOPMOST = - 2
HWND_TOPMOST = - 1
HWND_TOP = 0
SWP_NOMOVE = 0x0002
SWP_NOSIZE = 0x0001
SWP_NOZORDER = 0x0004
ctypes . windll . user32 . SetWindowPos (
ctypes . windll . kernel32 . GetConsoleWindow ( ) ,
HWND_TOP if top else HWND_NOTOPMOST ,
0 ,
0 ,
0 ,
0 ,
SWP_NOMOVE | SWP_NOSIZE | SWP_NOZORDER ,
)
def closest_divisible_64 ( num ) :
# Determine the remainder when num is divided by 64
remainder = num % 64
# If the remainder is less than or equal to 32, return num - remainder,
# but ensure the result is not less than 64
if remainder < = 32 :
result = num - remainder
return max ( result , 192 )
# Otherwise, return num + (64 - remainder)
else :
return num + ( 64 - remainder )
def find_first_empty_channel ( start_frame , end_frame ) :
for ch in range ( 1 , len ( bpy . context . scene . sequence_editor . sequences_all ) + 1 ) :
for seq in bpy . context . scene . sequence_editor . sequences_all :
if (
seq . channel == ch
and seq . frame_final_start < end_frame
and ( seq . frame_final_start + seq . frame_final_duration ) > start_frame
) :
break
else :
return ch
return 1
def clean_filename ( filename ) :
valid_chars = " -_.() %s %s " % ( string . ascii_letters , string . digits )
clean_filename = " " . join ( c if c in valid_chars else " _ " for c in filename )
return clean_filename
def clean_path ( full_path ) :
max_chars = 250
full_path = full_path [ : max_chars ]
dir_path , filename = os . path . split ( full_path )
cleaned_filename = clean_filename ( filename )
new_filename = cleaned_filename
i = 1
while os . path . exists ( os . path . join ( dir_path , new_filename ) ) :
name , ext = os . path . splitext ( cleaned_filename )
new_filename = f " { name } ( { i } ) { ext } "
i + = 1
return os . path . join ( dir_path , new_filename )
def import_module ( self , module , install_module ) :
show_system_console ( True )
set_system_console_topmost ( True )
module = str ( module )
try :
exec ( " import " + module )
except ModuleNotFoundError :
app_path = site . USER_SITE
if app_path not in sys . path :
sys . path . append ( app_path )
pybin = sys . executable
self . report ( { " INFO " } , " Installing: " + module + " module. " )
print ( " Installing: " + module + " module " )
subprocess . check_call (
[
pybin ,
" -m " ,
" pip " ,
" install " ,
install_module ,
" --no-warn-script-location " ,
" --user " ,
]
)
try :
exec ( " import " + module )
except ModuleNotFoundError :
return False
return True
def install_modules ( self ) :
app_path = site . USER_SITE
if app_path not in sys . path :
sys . path . append ( app_path )
pybin = sys . executable
print ( " Ensuring: pip " )
try :
subprocess . call ( [ pybin , " -m " , " ensurepip " ] )
subprocess . call ( [ pybin , " -m " , " pip " , " install " , " --upgrade " , " pip " ] )
except ImportError :
pass
try :
exec ( " import torch " )
except ModuleNotFoundError :
app_path = site . USER_SITE
if app_path not in sys . path :
sys . path . append ( app_path )
pybin = sys . executable
self . report ( { " INFO " } , " Installing: torch module. " )
print ( " Installing: torch module " )
if os_platform == " Windows " :
subprocess . check_call (
[
pybin ,
" -m " ,
" pip " ,
" install " ,
" torch " ,
" --index-url " ,
" https://download.pytorch.org/whl/cu118 " ,
" --no-warn-script-location " ,
" --user " ,
]
)
subprocess . check_call (
[
pybin ,
" -m " ,
" pip " ,
" install " ,
" torchvision " ,
" --index-url " ,
" https://download.pytorch.org/whl/cu118 " ,
" --no-warn-script-location " ,
" --user " ,
]
)
subprocess . check_call (
[
pybin ,
" -m " ,
" pip " ,
" install " ,
" torchaudio " ,
" --index-url " ,
" https://download.pytorch.org/whl/cu118 " ,
" --no-warn-script-location " ,
" --user " ,
]
)
else :
import_module ( self , " torch " , " torch " )
if os_platform == ' Darwin ' :
import_module ( self , " sox " , " sex " )
else :
import_module ( self , " soundfile " , " PySoundFile " )
import_module ( self , " diffusers " , " diffusers " )
import_module ( self , " accelerate " , " accelerate " )
import_module ( self , " transformers " , " transformers " )
import_module ( self , " cv2 " , " opencv_python " )
import_module ( self , " scipy " , " scipy " )
import_module ( self , " xformers " , " xformers " )
class GeneratorAddonPreferences ( AddonPreferences ) :
bl_idname = __name__
soundselect : EnumProperty (
name = " Sound " ,
items = {
( " ding " , " Ding " , " A simple bell sound " ) ,
( " coin " , " Coin " , " A Mario-like coin sound " ) ,
( " user " , " User " , " Load a custom sound file " ) ,
} ,
default = " ding " ,
)
default_folder = os . path . join (
os . path . dirname ( os . path . abspath ( __file__ ) ) , " sounds " , " *.wav "
)
if default_folder not in sys . path :
sys . path . append ( default_folder )
usersound : StringProperty (
name = " User " ,
description = " Load a custom sound from your computer " ,
subtype = " FILE_PATH " ,
default = default_folder ,
maxlen = 1024 ,
)
playsound : BoolProperty (
name = " Audio Notification " ,
default = True ,
)
def draw ( self , context ) :
layout = self . layout
box = layout . box ( )
box . operator ( " sequencer.install_generator " )
row = box . row ( align = True )
row . prop ( self , " playsound " , text = " Notification " )
row . prop ( self , " soundselect " , text = " " )
if self . soundselect == " user " :
row . prop ( self , " usersound " , text = " " )
row . operator ( " renderreminder.play_notification " , text = " " , icon = " PLAY " )
row . active = self . playsound
class GENERATOR_OT_install ( Operator ) :
""" Install all dependencies """
bl_idname = " sequencer.install_generator "
bl_label = " Install Dependencies "
bl_options = { " REGISTER " , " UNDO " }
def execute ( self , context ) :
preferences = context . preferences
addon_prefs = preferences . addons [ __name__ ] . preferences
install_modules ( self )
return { " FINISHED " }
class GENERATOR_OT_sound_notification ( Operator ) :
""" Test your notification settings """
bl_idname = " renderreminder.play_notification "
bl_label = " Test Notification "
bl_options = { " REGISTER " , " UNDO " }
def execute ( self , context ) :
preferences = context . preferences
addon_prefs = preferences . addons [ __name__ ] . preferences
if addon_prefs . playsound :
device = aud . Device ( )
def coinSound ( ) :
sound = aud . Sound ( " " )
handle = device . play (
sound . triangle ( 1000 )
. highpass ( 20 )
. lowpass ( 2000 )
. ADSR ( 0 , 0.5 , 1 , 0 )
. fadeout ( 0.1 , 0.1 )
. limit ( 0 , 1 )
)
handle = device . play (
sound . triangle ( 1500 )
. highpass ( 20 )
. lowpass ( 2000 )
. ADSR ( 0 , 0.5 , 1 , 0 )
. fadeout ( 0.2 , 0.2 )
. delay ( 0.1 )
. limit ( 0 , 1 )
)
def ding ( ) :
sound = aud . Sound ( " " )
handle = device . play (
sound . triangle ( 3000 )
. highpass ( 20 )
. lowpass ( 1000 )
. ADSR ( 0 , 0.5 , 1 , 0 )
. fadeout ( 0 , 1 )
. limit ( 0 , 1 )
)
if addon_prefs . soundselect == " ding " :
ding ( )
if addon_prefs . soundselect == " coin " :
coinSound ( )
if addon_prefs . soundselect == " user " :
file = str ( addon_prefs . usersound )
if os . path . isfile ( file ) :
sound = aud . Sound ( file )
handle = device . play ( sound )
return { " FINISHED " }
class SEQUENCER_OT_generate_movie ( Operator ) :
""" Generate Video """
bl_idname = " sequencer.generate_movie "
bl_label = " Prompt "
bl_description = " Convert text to video "
bl_options = { " REGISTER " , " UNDO " }
def execute ( self , context ) :
if not bpy . types . Scene . generate_movie_prompt :
return { " CANCELLED " }
show_system_console ( True )
set_system_console_topmost ( True )
scene = context . scene
seq_editor = scene . sequence_editor
if not seq_editor :
scene . sequence_editor_create ( )
try :
import torch
from diffusers import DiffusionPipeline , DPMSolverMultistepScheduler
from diffusers . utils import export_to_video
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 " }
current_frame = scene . frame_current
prompt = scene . generate_movie_prompt
negative_prompt = scene . generate_movie_negative_prompt
movie_x = scene . generate_movie_x
movie_y = scene . generate_movie_y
x = scene . generate_movie_x = closest_divisible_64 ( movie_x )
y = scene . generate_movie_y = closest_divisible_64 ( movie_y )
duration = scene . generate_movie_frames
movie_num_inference_steps = scene . movie_num_inference_steps
movie_num_guidance = scene . movie_num_guidance
#wm = bpy.context.window_manager
#tot = scene.movie_num_batch
#wm.progress_begin(0, tot)
# Options: https://huggingface.co/docs/diffusers/api/pipelines/text_to_video
pipe = DiffusionPipeline . from_pretrained (
" damo-vilab/text-to-video-ms-1.7b " , #"strangeman3107/animov-0.1", #
torch_dtype = torch . float16 ,
variant = " fp16 " ,
)
pipe . scheduler = DPMSolverMultistepScheduler . from_config (
pipe . scheduler . config
)
# memory optimization
pipe . enable_model_cpu_offload ( )
pipe . enable_vae_slicing ( )
for i in range ( scene . movie_num_batch ) :
#wm.progress_update(i)
if i > 0 :
empty_channel = scene . sequence_editor . active_strip . channel
start_frame = (
scene . sequence_editor . active_strip . frame_final_start
+ scene . sequence_editor . active_strip . frame_final_duration
)
scene . frame_current = (
scene . sequence_editor . active_strip . frame_final_start
)
else :
empty_channel = find_first_empty_channel (
scene . frame_current ,
( scene . movie_num_batch * duration ) + scene . frame_current ,
)
start_frame = scene . frame_current
seed = context . scene . movie_num_seed
seed = (
seed
if not context . scene . movie_use_random
else random . randint ( 0 , 2147483647 )
)
context . scene . movie_num_seed = seed
# Use cuda if possible
if torch . cuda . is_available ( ) :
generator = (
torch . Generator ( " cuda " ) . manual_seed ( seed ) if seed != 0 else None
)
else :
if seed != 0 :
generator = torch . Generator ( )
generator . manual_seed ( seed )
else :
generator = None
video_frames = pipe (
prompt ,
negative_prompt = negative_prompt ,
num_inference_steps = movie_num_inference_steps ,
guidance_scale = movie_num_guidance ,
height = y ,
width = x ,
num_frames = duration ,
generator = generator ,
) . frames
# Move to folder
src_path = export_to_video ( video_frames )
dst_path = clean_path ( dirname ( realpath ( __file__ ) ) + " / " + os . path . basename ( src_path ) )
shutil . move ( src_path , dst_path )
# Add strip
if os . path . isfile ( dst_path ) :
strip = scene . sequence_editor . sequences . new_movie (
name = context . scene . generate_movie_prompt + " " + str ( seed ) ,
frame_start = start_frame ,
filepath = dst_path ,
channel = empty_channel ,
fit_method = " FIT " ,
)
scene . sequence_editor . active_strip = strip
if i > 0 :
scene . frame_current = (
scene . sequence_editor . active_strip . frame_final_start
)
else :
print ( " No resulting file found. " )
# Redraw UI to display the new strip. Remove this if Blender crashes: https://docs.blender.org/api/current/info_gotcha.html#can-i-redraw-during-script-execution
#bpy.ops.wm.redraw_timer(type="DRAW_WIN_SWAP", iterations=1)
bpy . ops . renderreminder . play_notification ( )
#wm.progress_end()
scene . frame_current = current_frame
# clear the VRAM
if torch . cuda . is_available ( ) :
torch . cuda . empty_cache ( )
return { " FINISHED " }
class SEQEUNCER_PT_generate_movie ( Panel ) :
""" Generate Video using AI """
bl_idname = " SEQUENCER_PT_sequencer_generate_movie_panel "
bl_label = " Generative AI "
bl_space_type = " SEQUENCE_EDITOR "
bl_region_type = " UI "
bl_category = " Generative AI "
def draw ( self , context ) :
layout = self . layout
layout . use_property_split = False
layout . use_property_decorate = False
scene = context . scene
type = scene . generatorai_typeselect
col = layout . column ( )
col . prop ( context . scene , " generatorai_typeselect " , text = " " )
layout = self . layout
col = layout . column ( align = True )
col . use_property_split = True
col . use_property_decorate = False
col . scale_y = 1.2
col . prop ( context . scene , " generate_movie_prompt " , text = " " , icon = " ADD " )
col . prop ( context . scene , " generate_movie_negative_prompt " , text = " " , icon = " REMOVE " )
layout = self . layout
layout . use_property_split = True
layout . use_property_decorate = False
if type == " movie " or type == " image " :
col = layout . column ( align = True )
col . prop ( context . scene , " generate_movie_x " , text = " X " )
col . prop ( context . scene , " generate_movie_y " , text = " Y " )
col = layout . column ( align = True )
if type == " movie " or type == " image " :
col . prop ( context . scene , " generate_movie_frames " , text = " Frames " )
if type == " audio " :
col . prop ( context . scene , " audio_length_in_f " , text = " Frames " )
col . prop ( context . scene , " movie_num_inference_steps " , text = " Quality Steps " )
col . prop ( context . scene , " movie_num_guidance " , text = " Word Power " )
if type == " movie " :
col . prop ( context . scene , " movie_num_batch " , text = " Batch Count " )
if type == " movie " or type == " image " :
col = layout . column ( align = True )
row = col . row ( align = True )
sub_row = row . row ( align = True )
sub_row . prop ( context . scene , " movie_num_seed " , text = " Seed " )
row . prop ( context . scene , " movie_use_random " , text = " " , icon = " QUESTION " )
sub_row . active = not context . scene . movie_use_random
row = layout . row ( align = True )
row . scale_y = 1.1
if type == " movie " :
row . operator ( " sequencer.generate_movie " , text = " Generate " )
if type == " image " :
row . operator ( " sequencer.generate_image " , text = " Generate " )
if type == " audio " :
row . operator ( " sequencer.generate_audio " , text = " Generate " )
class SEQUENCER_OT_generate_audio ( Operator ) :
""" Generate Audio """
bl_idname = " sequencer.generate_audio "
bl_label = " Prompt "
bl_description = " Convert text to audio "
bl_options = { " REGISTER " , " UNDO " }
def execute ( self , context ) :
if not bpy . types . Scene . generate_movie_prompt :
self . report ( { " INFO " } , " Text prompt in the GeneratorAI tab is empty! " )
return { " CANCELLED " }
scene = context . scene
if not scene . sequence_editor :
scene . sequence_editor_create ( )
current_frame = scene . frame_current
prompt = scene . generate_movie_prompt
negative_prompt = scene . generate_movie_negative_prompt
movie_num_inference_steps = scene . movie_num_inference_steps
movie_num_guidance = scene . movie_num_guidance
audio_length_in_s = scene . audio_length_in_f / ( scene . render . fps / scene . render . fps_base )
try :
from diffusers import AudioLDMPipeline
import torch
import scipy
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 " }
repo_id = " cvssp/audioldm "
pipe = AudioLDMPipeline . from_pretrained ( repo_id ) # , torch_dtype=torch.float16z
# Use cuda if possible
if torch . cuda . is_available ( ) :
pipe = pipe . to ( " cuda " )
for i in range ( 1 ) : #scene.movie_num_batch): seed do not work for audio
#wm.progress_update(i)
if i > 0 :
empty_channel = scene . sequence_editor . active_strip . channel
start_frame = (
scene . sequence_editor . active_strip . frame_final_start
+ scene . sequence_editor . active_strip . frame_final_duration
)
scene . frame_current = (
scene . sequence_editor . active_strip . frame_final_start
)
else :
empty_channel = find_first_empty_channel (
scene . frame_current ,
( scene . movie_num_batch * scene . audio_length_in_f ) + scene . frame_current ,
)
start_frame = scene . frame_current
seed = context . scene . movie_num_seed
seed = (
seed
if not context . scene . movie_use_random
else random . randint ( 0 , 2147483647 )
)
context . scene . movie_num_seed = seed
# Use cuda if possible
if torch . cuda . is_available ( ) :
generator = (
torch . Generator ( " cuda " ) . manual_seed ( seed ) if seed != 0 else None
)
else :
if seed != 0 :
generator = torch . Generator ( )
generator . manual_seed ( seed )
else :
generator = None
prompt = context . scene . generate_movie_prompt
# Options: https://huggingface.co/docs/diffusers/main/en/api/pipelines/audioldm
audio = pipe (
prompt ,
num_inference_steps = movie_num_inference_steps ,
audio_length_in_s = audio_length_in_s ,
guidance_scale = movie_num_guidance ,
generator = generator ,
) . audios [ 0 ]
filename = clean_path ( dirname ( realpath ( __file__ ) ) + " / " + prompt + " .wav " )
scipy . io . wavfile . write ( filename , 16000 , audio . transpose ( ) )
filepath = filename
if os . path . isfile ( filepath ) :
empty_channel = empty_channel
strip = scene . sequence_editor . sequences . new_sound (
name = prompt ,
filepath = filepath ,
channel = empty_channel ,
frame_start = start_frame ,
)
scene . sequence_editor . active_strip = strip
if i > 0 :
scene . frame_current = (
scene . sequence_editor . active_strip . frame_final_start
)
else :
print ( " No resulting file found! " )
# clear the VRAM
if torch . cuda . is_available ( ) :
torch . cuda . empty_cache ( )
bpy . ops . renderreminder . play_notification ( )
return { " FINISHED " }
#class SEQEUNCER_PT_generate_audio(Panel):
# """Generate Audio with AI"""
# bl_idname = "SEQUENCER_PT_sequencer_generate_audio_panel"
# bl_label = "Generate Audio"
# bl_space_type = "SEQUENCE_EDITOR"
# bl_region_type = "UI"
# bl_category = "Generative AI"
# def draw(self, context):
# layout = self.layout
# scene = context.scene
# row = layout.row()
# row.scale_y = 1.2
# row.prop(context.scene, "generate_audio_prompt", text="")
# row = layout.row()
# row.scale_y = 1.2
# row.operator("sequencer.generate_audio", text="Generate Audio")
class SEQUENCER_OT_generate_image ( Operator ) :
""" Generate Image """
bl_idname = " sequencer.generate_image "
bl_label = " Prompt "
bl_description = " Convert text to image "
bl_options = { " REGISTER " , " UNDO " }
def execute ( self , context ) :
if not bpy . types . Scene . generate_movie_prompt :
return { " CANCELLED " }
show_system_console ( True )
set_system_console_topmost ( True )
scene = context . scene
seq_editor = scene . sequence_editor
if not seq_editor :
scene . sequence_editor_create ( )
try :
from diffusers import DiffusionPipeline , DPMSolverMultistepScheduler
import torch
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 " }
current_frame = scene . frame_current
prompt = scene . generate_movie_prompt
negative_prompt = scene . generate_movie_negative_prompt
image_x = scene . generate_movie_x
image_y = scene . generate_movie_y
x = scene . generate_movie_x = closest_divisible_64 ( image_x )
y = scene . generate_movie_y = closest_divisible_64 ( image_y )
duration = scene . generate_movie_frames
image_num_inference_steps = scene . movie_num_inference_steps
image_num_guidance = scene . movie_num_guidance
#wm = bpy.context.window_manager
#tot = scene.movie_num_batch
#wm.progress_begin(0, tot)
# Options: https://huggingface.co/docs/diffusers/api/pipelines/text_to_video
pipe = DiffusionPipeline . from_pretrained (
" stabilityai/stable-diffusion-2 " ,
torch_dtype = torch . float16 ,
variant = " fp16 " ,
)
pipe . scheduler = DPMSolverMultistepScheduler . from_config ( pipe . scheduler . config )
# memory optimization
pipe . enable_model_cpu_offload ( )
pipe . enable_vae_slicing ( )
for i in range ( scene . movie_num_batch ) :
#wm.progress_update(i)
if i > 0 :
empty_channel = scene . sequence_editor . active_strip . channel
start_frame = (
scene . sequence_editor . active_strip . frame_final_start
+ scene . sequence_editor . active_strip . frame_final_duration
)
scene . frame_current = (
scene . sequence_editor . active_strip . frame_final_start
)
else :
empty_channel = find_first_empty_channel (
scene . frame_current ,
( scene . movie_num_batch * duration ) + scene . frame_current ,
)
start_frame = scene . frame_current
seed = context . scene . movie_num_seed
seed = (
seed
if not context . scene . movie_use_random
else random . randint ( 0 , 2147483647 )
)
context . scene . movie_num_seed = seed
# Use cuda if possible
if torch . cuda . is_available ( ) :
generator = (
torch . Generator ( " cuda " ) . manual_seed ( seed ) if seed != 0 else None
)
else :
if seed != 0 :
generator = torch . Generator ( )
generator . manual_seed ( seed )
else :
generator = None
image = pipe (
prompt ,
negative_prompt = negative_prompt ,
num_inference_steps = image_num_inference_steps ,
guidance_scale = image_num_guidance ,
height = y ,
width = x ,
generator = generator ,
) . images [ 0 ]
# Move to folder
image . save ( " temp.png " )
#print(src_path)
dst_path = clean_path ( dirname ( realpath ( __file__ ) ) + " / " + context . scene . generate_movie_prompt + " .png " )
shutil . move ( " temp.png " , dst_path )
# Add strip
if os . path . isfile ( dst_path ) :
strip = scene . sequence_editor . sequences . new_image (
name = context . scene . generate_movie_prompt + " " + str ( seed ) ,
frame_start = start_frame ,
filepath = dst_path ,
channel = empty_channel ,
fit_method = " FIT " ,
)
strip . frame_final_duration = scene . generate_movie_frames
scene . sequence_editor . active_strip = strip
if i > 0 :
scene . frame_current = (
scene . sequence_editor . active_strip . frame_final_start
)
else :
print ( " No resulting file found. " )
# Redraw UI to display the new strip. Remove this if Blender crashes: https://docs.blender.org/api/current/info_gotcha.html#can-i-redraw-during-script-execution
#bpy.ops.wm.redraw_timer(type="DRAW_WIN_SWAP", iterations=1)
bpy . ops . renderreminder . play_notification ( )
#wm.progress_end()
scene . frame_current = current_frame
# clear the VRAM
if torch . cuda . is_available ( ) :
torch . cuda . empty_cache ( )
return { " FINISHED " }
class SEQUENCER_OT_strip_to_generatorAI ( Operator ) :
""" Convert selected text strips to GeneratorAI """
bl_idname = " sequencer.text_to_generator "
bl_label = " Convert Text Strips to GeneratorAI "
bl_options = { " INTERNAL " }
bl_description = " Adds selected text strips as GeneratorAI strips "
@classmethod
def poll ( cls , context ) :
return context . scene and context . scene . sequence_editor
def execute ( self , context ) :
preferences = context . preferences
addon_prefs = preferences . addons [ __name__ ] . preferences
play_sound = addon_prefs . playsound
addon_prefs . playsound = False
scene = context . scene
sequencer = bpy . ops . sequencer
sequences = bpy . context . sequences
strips = context . selected_sequences
prompt = scene . generate_movie_prompt
current_frame = scene . frame_current
type = scene . generatorai_typeselect
for strip in strips :
if strip . type == " TEXT " :
if strip . text :
print ( " Processing: " + strip . text )
scene . generate_movie_prompt = strip . text
scene . frame_current = strip . frame_final_start
if type == " movie " :
sequencer . generate_movie ( )
if type == " audio " :
sequencer . generate_audio ( )
scene . frame_current = current_frame
context . scene . generate_movie_prompt = prompt
addon_prefs . playsound = play_sound
bpy . ops . renderreminder . play_notification ( )
return { " FINISHED " }
def panel_text_to_generatorAI ( self , context ) :
layout = self . layout
layout . separator ( )
layout . operator (
" sequencer.text_to_generator " , text = " Text to GeneratorAI " , icon = " SHADERFX "
)
classes = (
SEQUENCER_OT_generate_movie ,
SEQUENCER_OT_generate_audio ,
SEQUENCER_OT_generate_image ,
SEQEUNCER_PT_generate_movie ,
# SEQEUNCER_PT_generate_audio,
GeneratorAddonPreferences ,
GENERATOR_OT_sound_notification ,
SEQUENCER_OT_strip_to_generatorAI ,
GENERATOR_OT_install ,
)
def register ( ) :
for cls in classes :
bpy . utils . register_class ( cls )
bpy . types . Scene . generate_movie_prompt = bpy . props . StringProperty (
name = " generate_movie_prompt " , default = " "
)
bpy . types . Scene . generate_movie_negative_prompt = bpy . props . StringProperty (
name = " generate_movie_negative_prompt " ,
default = " text, watermark, copyright, blurry, grainy, copyright " ,
)
bpy . types . Scene . generate_audio_prompt = bpy . props . StringProperty (
name = " generate_audio_prompt " , default = " "
)
bpy . types . Scene . generate_movie_x = bpy . props . IntProperty (
name = " generate_movie_x " ,
default = 512 ,
step = 64 ,
min = 192 ,
max = 1024 ,
)
bpy . types . Scene . generate_movie_y = bpy . props . IntProperty (
name = " generate_movie_y " ,
default = 256 ,
step = 64 ,
min = 192 ,
max = 1024 ,
)
# The number of frames to be generated.
bpy . types . Scene . generate_movie_frames = bpy . props . IntProperty (
name = " generate_movie_y " ,
default = 16 ,
min = 1 ,
max = 125 ,
)
# The number of denoising steps. More denoising steps usually lead to a higher quality audio at the expense of slower inference.
bpy . types . Scene . movie_num_inference_steps = bpy . props . IntProperty (
name = " movie_num_inference_steps " ,
default = 25 ,
min = 1 ,
max = 100 ,
)
# The number of videos to generate.
bpy . types . Scene . movie_num_batch = bpy . props . IntProperty (
name = " movie_num_batch " ,
default = 1 ,
min = 1 ,
max = 100 ,
)
# The seed number.
bpy . types . Scene . movie_num_seed = bpy . props . IntProperty (
name = " movie_num_seed " ,
default = 1 ,
min = 1 ,
max = 2147483647 ,
)
# The seed number.
bpy . types . Scene . movie_use_random = bpy . props . BoolProperty (
name = " movie_use_random " ,
default = 0 ,
)
# The seed number.
bpy . types . Scene . movie_num_guidance = bpy . props . IntProperty (
name = " movie_num_guidance " ,
default = 17 ,
min = 1 ,
max = 100 ,
)
# The frame ausio duration.
bpy . types . Scene . audio_length_in_f = bpy . props . IntProperty (
name = " audio_length_in_f " ,
default = 80 ,
min = 1 ,
max = 10000 ,
)
bpy . types . Scene . generatorai_typeselect = bpy . props . EnumProperty (
name = " Sound " ,
items = {
( " movie " , " Video " , " Generate Video " ) ,
( " image " , " Image " , " Generate Image " ) ,
( " audio " , " Audio " , " Generate Audio " ) ,
} ,
default = " movie " ,
)
bpy . types . SEQUENCER_MT_add . append ( panel_text_to_generatorAI )
def unregister ( ) :
for cls in classes :
bpy . utils . unregister_class ( cls )
del bpy . types . Scene . generate_movie_prompt
del bpy . types . Scene . generate_audio_prompt
del bpy . types . Scene . generate_movie_x
del bpy . types . Scene . generate_movie_y
del bpy . types . Scene . movie_num_inference_steps
del bpy . types . Scene . movie_num_batch
del bpy . types . Scene . movie_num_seed
del bpy . types . Scene . movie_use_random
del bpy . types . Scene . movie_num_guidance
del bpy . types . Scene . generatorai_typeselect
bpy . types . SEQUENCER_MT_add . remove ( panel_text_to_generatorAI )
if __name__ == " __main__ " :
register ( )
