Files
FizzleDorf-ComfyUI_FizzNodes/ScheduledNodes.py
T

867 lines
38 KiB
Python

#These nodes were made using code from the Deforum extension for A1111 webui
#You can find the project here: https://github.com/deforum-art/sd-webui-deforum
import comfy
import numexpr
import torch
import numpy as np
import pandas as pd
import re
import json
from .ScheduleFuncs import *
from .BatchFuncs import *
from .ValueFuncs import *
from .ScheduleTypes import *
#Max resolution value for Gligen area calculation.
MAX_RESOLUTION=8192
#Default prompt for the prompt schedules.
defaultPrompt=""""0" :"",
"11" :"",
"23" :"",
"35" :"",
"47" :"",
"59" :"",
"71" :"",
"83" :"",
"95" :"",
"107" :"",
"119" :""
"""
#Default prompt for the value schedules.
defaultValue="""0:(0),
11:(0),
23:(0),
35:(0),
47:(0),
59:(0),
71:(0),
83:(0),
95:(0),
107:(0),
119:(0)
"""
#This node parses the user's formatted prompt,
#sequences the current prompt,next prompt, and
#conditioning strength, evaluates expressions in
#the prompts, and then returns either current,
#next or averaged conditioning.
class PromptSchedule:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"text": ("STRING", {"multiline": True, "default":defaultPrompt}),
"clip": ("CLIP", ),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"current_frame": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0, "forceInput": True }),
"print_output":("BOOLEAN", {"default": False,}),
},
"optional": {"pre_text": ("STRING", {"multiline": True, "forceInput": True}),
"app_text": ("STRING", {"multiline": True, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
}
}
RETURN_TYPES = ("CONDITIONING", "CONDITIONING",)
RETURN_NAMES = ("POS", "NEG",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/ScheduleNodes"
def animate(self, text, max_frames, print_output, current_frame,clip, pw_a=0, pw_b=0, pw_c=0, pw_d=0, pre_text='', app_text=''
):
settings = ScheduleSettings(
text_g=text,
pre_text_G=pre_text,
app_text_G=app_text,
text_L=None,
pre_text_L=None,
app_text_L=None,
max_frames=max_frames,
current_frame=current_frame,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=0,
end_frame=max_frames,
width=None,
height=None,
crop_w=None,
crop_h=None,
target_width=None,
target_height=None,
)
return prompt_schedule(settings,clip)
# This node parses the user's formatted prompt,
# sequences the current prompt,next prompt, and
# conditioning strength, evaluates expressions in
# the prompts, and then returns a batch of
# conditionings with the schedule applied.
class BatchPromptSchedule:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"text": ("STRING", {"multiline": True, "default": defaultPrompt}),
"clip": ("CLIP",),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"print_output":("BOOLEAN", {"default": False}),
},
"optional": {
"pre_text": ("STRING", {"multiline": True, "forceInput": True}),
"app_text": ("STRING", {"multiline": True, "forceInput": True}),
"start_frame": ("INT", {"default": 0, "min": 0, "max": 9999, "step": 1, "display": "start_frame(print_only)", }),
"end_frame": ("INT", {"default": 0, "min": 0, "max": 9999, "step": 1, "display": "end_frame(print_only)",}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
}
}
RETURN_TYPES = ("CONDITIONING", "CONDITIONING",)
RETURN_NAMES = ("POS", "NEG",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, text, max_frames, print_output, clip, start_frame, end_frame, pw_a=0, pw_b=0, pw_c=0, pw_d=0, pre_text='', app_text=''
):
settings = ScheduleSettings(
text_g=text,
pre_text_G=pre_text,
app_text_G=app_text,
text_L=None,
pre_text_L=None,
app_text_L=None,
max_frames=max_frames,
current_frame=None,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=start_frame,
end_frame=end_frame,
width=None,
height=None,
crop_w=None,
crop_h=None,
target_width=None,
target_height=None,
)
return batch_prompt_schedule(settings, clip)
# This node parses the user's formatted prompt,
# sequences the current prompt,next prompt, and
# conditioning strength, evaluates expressions in
# the prompts, and then returns a batch of
# conditionings with the schedule applied.
# This alternate batch node takes a latent as
# an input instead of max_frames
class BatchPromptScheduleLatentInput:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"text": ("STRING", {"multiline": True, "default": defaultPrompt}),
"clip": ("CLIP",),
"num_latents": ("LATENT", ),
"print_output":("BOOLEAN", {"default": False}),
},
"optional": {"pre_text": ("STRING", {"multiline": True, "forceInput": True}),
"app_text": ("STRING", {"multiline": True, "forceInput": True}),
"start_frame": ("INT", {"default": 0.0, "min": 0, "max": 9999, "step": 1, "display": "start_frame(print_only)", }),
"end_frame": ("INT", {"default": 0, "min": 0, "max": 9999, "step": 1, "display": "end_frame(print_only)", }),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
}
}
RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT",) #"CONDITIONING", "CONDITIONING", "CONDITIONING", "CONDITIONING",)
RETURN_NAMES = ("POS", "NEG", "INPUT_LATENTS", ) #"POS_CUR", "NEG_CUR", "POS_NXT", "NEG_NXT",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, text, num_latents, print_output, clip, start_frame, end_frame, pw_a=0, pw_b=0, pw_c=0, pw_d=0, pre_text='', app_text=''
):
settings = ScheduleSettings(
text_g=text,
pre_text_G=pre_text,
app_text_G=app_text,
text_L=None,
pre_text_L=None,
app_text_L=None,
max_frames=sum(tensor.size(0) for tensor in num_latents.values()),
current_frame=None,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=start_frame,
end_frame=end_frame,
width=None,
height=None,
crop_w=None,
crop_h=None,
target_width=None,
target_height=None,
)
return batch_prompt_schedule_latentInput(settings,clip, num_latents)
# This node prepares the strings and calculates
# the numexpr expressions. It returns a single
# string at the current_frame input.
class StringSchedule:
@classmethod
def INPUT_TYPES(s):
return {"required": {"text": ("STRING", {"multiline": True, "default": defaultPrompt}),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"current_frame": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0, }),
"print_output":("BOOLEAN", {"default": False}),},
"optional": {"pre_text": ("STRING", {"multiline": True, "forceInput": True}),
"app_text": ("STRING", {"multiline": True, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
}
}
RETURN_TYPES = ("STRING", "STRING",)
RETURN_NAMES = ("POS", "NEG",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/ScheduleNodes"
def animate(self, text, max_frames, current_frame, pw_a=0, pw_b=0, pw_c=0, pw_d=0, pre_text='', app_text='', print_output = False ):
settings = ScheduleSettings(
text_g = text,
pre_text_G = pre_text,
app_text_G = app_text,
text_L = None,
pre_text_L = None,
app_text_L = None,
max_frames = max_frames,
current_frame = current_frame,
print_output = print_output,
pw_a = pw_a,
pw_b = pw_b,
pw_c = pw_c,
pw_d = pw_d,
start_frame = 0,
end_frame=max_frames,
width = None,
height = None,
crop_w = None,
crop_h = None,
target_width = None,
target_height = None,
)
return string_schedule(settings)
# This node prepares the strings and calculates
# the numexpr expressions. It returns a batch of
# strings.
class BatchStringSchedule:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"text": ("STRING", {"multiline": True, "default": defaultPrompt}),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"print_output": ("BOOLEAN", {"default": False}),
},
"optional": {
"pre_text": ("STRING", {"multiline": True, "forceInput": True}),
"app_text": ("STRING", {"multiline": True, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
}
}
RETURN_TYPES = ("STRING", "STRING",)
RETURN_NAMES = ("POS", "NEG",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, text, max_frames, pw_a=0, pw_b=0, pw_c=0, pw_d=0, pre_text='', app_text='',
print_output=False):
settings = ScheduleSettings(
text_g=text,
pre_text_G=pre_text,
app_text_G=app_text,
text_L=None,
pre_text_L=None,
app_text_L=None,
max_frames=max_frames,
current_frame=None,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=0,
end_frame=max_frames,
width=None,
height=None,
crop_w=None,
crop_h=None,
target_width=None,
target_height=None,
)
return batch_string_schedule(settings)
# Same as the regular node just for SDXL
# clips instead. the G and L clip can be
# scheduled separately before tokenization,
# goes through the same add_weighted process
# and returns the current, next or averaged
# conditioning.
class PromptScheduleEncodeSDXL:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"crop_w": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"crop_h": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"target_width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"target_height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"text_g": ("STRING", {"multiline": True, }), "clip": ("CLIP", ),
"text_l": ("STRING", {"multiline": True, }), "clip": ("CLIP", ),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"current_frame": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0}),
"print_output":("BOOLEAN", {"default": False}),
},
"optional": {
"pre_text_G": ("STRING", {"multiline": True, "forceInput": True}),
"app_text_G": ("STRING", {"multiline": True, "forceInput": True}),
"pre_text_L": ("STRING", {"multiline": True, "forceInput": True}),
"app_text_L": ("STRING", {"multiline": True, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
}
}
RETURN_TYPES = ("CONDITIONING","CONDITIONING",)
RETURN_NAMES = ("POS", "NEG",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/ScheduleNodes"
def animate(self, clip, text_g, text_l, width, height, crop_w, crop_h, target_width, target_height, max_frames, current_frame, print_output, app_text_G = '', app_text_L = '', pre_text_G = '', pre_text_L = '', pw_a=0, pw_b=0, pw_c=0, pw_d=0):
settings = ScheduleSettings(
text_g=text_g,
pre_text_G=pre_text_G,
app_text_G=app_text_G,
text_L=text_l,
pre_text_L=pre_text_L,
app_text_L=app_text_L,
max_frames=max_frames,
current_frame=current_frame,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=0,
end_frame=max_frames,
width=width,
height=height,
crop_w=crop_w,
crop_h=crop_h,
target_width=target_width,
target_height=target_height,
)
return prompt_schedule_SDXL(settings,clip)
# Same as the regular node just for SDXL
# clips instead. the G and L clip can be
# scheduled separately before tokenization,
# goes through the same add_weighted process
# and returns a batch of conditionings.
class BatchPromptScheduleEncodeSDXL:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"crop_w": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"crop_h": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"target_width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"target_height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"text_g": ("STRING", {"multiline": True, }), "clip": ("CLIP", ),
"text_l": ("STRING", {"multiline": True, }), "clip": ("CLIP", ),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"print_output":("BOOLEAN", {"default": False}),
},
"optional": {
"pre_text_G": ("STRING", {"multiline": True, "forceInput": True}),
"app_text_G": ("STRING", {"multiline": True, "forceInput": True}),
"pre_text_L": ("STRING", {"multiline": True, "forceInput": True}),
"app_text_L": ("STRING", {"multiline": True, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"start_frame": (
"INT", {"default": 0, "min": 0, "max": 9999, "step": 1, "display": "start_frame(print_only)", }),
"end_frame": (
"INT", {"default": 120, "min": 0, "max": 9999, "step": 1, "display": "end_frame(print_only)", }),
}
}
RETURN_TYPES = ("CONDITIONING", "CONDITIONING",)# "CONDITIONING", "CONDITIONING", "CONDITIONING", "CONDITIONING",)
RETURN_NAMES = ("POS", "NEG")#, "POS_CUR", "NEG_CUR", "POS_NXT", "NEG_NXT",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, clip, text_g, text_l, width, height, crop_w, crop_h, target_width, target_height, max_frames, print_output, app_text_G = '', app_text_L = '', pre_text_G = '', pre_text_L = '', pw_a=0, pw_b=0, pw_c=0, pw_d=0, start_frame=0, end_frame=120):
settings = ScheduleSettings(
text_g=text_g,
pre_text_G=pre_text_G,
app_text_G=app_text_G,
text_L=text_l,
pre_text_L=pre_text_L,
app_text_L=app_text_L,
max_frames=max_frames,
current_frame=None,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=start_frame,
end_frame=end_frame,
width=width,
height=height,
crop_w=crop_w,
crop_h=crop_h,
target_width=target_width,
target_height=target_height,
)
return batch_prompt_schedule_SDXL(settings, clip)
# Same as the regular node just for SDXL
# clips instead. the G and L clip can be
# scheduled separately before tokenization,
# goes through the same add_weighted process
# and returns a batch of conditionings. The
# max_size is input by the number of latents
# in the input.
class BatchPromptScheduleEncodeSDXLLatentInput:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"crop_w": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"crop_h": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"target_width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"target_height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"text_g": ("STRING", {"multiline": True, }), "clip": ("CLIP", ),
"text_l": ("STRING", {"multiline": True, }), "clip": ("CLIP", ),
"num_latents": ("LATENT", ),
"print_output":("BOOLEAN", {"default": False}),
},
"optional": {
"pre_text_G": ("STRING", {"multiline": True, "forceInput": True}),
"app_text_G": ("STRING", {"multiline": True, "forceInput": True}),
"pre_text_L": ("STRING", {"multiline": True, "forceInput": True}),
"app_text_L": ("STRING", {"multiline": True, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"start_frame": (
"INT", {"default": 0, "min": 0, "max": 9999, "step": 1, "display": "start_frame(print_only)", }),
"end_frame": (
"INT", {"default": 120, "min": 0, "max": 9999, "step": 1, "display": "end_frame(print_only)", }),
}
}
RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT",)# "CONDITIONING", "CONDITIONING", "CONDITIONING", "CONDITIONING",)
RETURN_NAMES = ("POS", "NEG", "INPUT_LATENTS")#, "NEG_CUR", "POS_NXT", "NEG_NXT",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, clip, text_g, text_l, width, height, crop_w, crop_h, target_width, target_height, num_latents, print_output, app_text_G = '', app_text_L = '', pre_text_G = '', pre_text_L = '', pw_a=0, pw_b=0, pw_c=0, pw_d=0, start_frame=0, end_frame=120):
settings = ScheduleSettings(
text_g=text_g,
pre_text_G=pre_text_G,
app_text_G=app_text_G,
text_L=text_l,
pre_text_L=pre_text_L,
app_text_L=app_text_L,
max_frames=sum(tensor.size(0) for tensor in num_latents.values()),
current_frame=None,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=start_frame,
end_frame=end_frame,
width=width,
height=height,
crop_w=crop_w,
crop_h=crop_h,
target_width=target_width,
target_height=target_height,
)
return batch_prompt_schedule_SDXL_latentInput(settings, clip, num_latents)
# This node schedules the prompt using separate nodes as the keyframes.
# The values in the prompt are evaluated in NodeFlowEnd.
class PromptScheduleNodeFlow:
@classmethod
def INPUT_TYPES(s):
return {"required": {"text": ("STRING", {"multiline": True}),
"num_frames": ("INT", {"default": 24.0, "min": 0.0, "max": 9999.0, "step": 1.0}),},
"optional": {"in_text": ("STRING", {"multiline": False, }), # "forceInput": True}),
"max_frames": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0,})}}
RETURN_TYPES = ("INT","STRING",)
FUNCTION = "addString"
CATEGORY = "FizzNodes 📅🅕🅝/ScheduleNodes"
def addString(self, text, in_text='', max_frames=0, num_frames=0):
if in_text:
# Remove trailing comma from in_text if it exists
in_text = in_text.rstrip(',')
new_max = num_frames + max_frames
if max_frames == 0:
# Construct a new JSON object with a single key-value pair
new_text = in_text + (', ' if in_text else '') + f'"{max_frames}": "{text}"'
else:
# Construct a new JSON object with a single key-value pair
new_text = in_text + (', ' if in_text else '') + f'"{new_max}": "{text}"'
return (new_max, new_text,)
#Last node in the Node Flow for evaluating the json produced by the above node.
class PromptScheduleNodeFlowEnd:
@classmethod
def INPUT_TYPES(s):
return {"required": {"text": ("STRING", {"multiline": False, "forceInput": True}),
"clip": ("CLIP", ),
"max_frames": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0,}),
"print_output": ("BOOLEAN", {"default": False}),
"current_frame": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0, "forceInput": True}),},
"optional": {"pre_text": ("STRING", {"multiline": True, "forceInput": True}),
"app_text": ("STRING", {"multiline": True, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
}}
RETURN_TYPES = ("CONDITIONING","CONDITIONING",)
RETURN_NAMES = ("POS", "NEG",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/ScheduleNodes"
def animate(self, text, max_frames, print_output, current_frame, clip, pw_a = 0, pw_b = 0, pw_c = 0, pw_d = 0, pre_text = '', app_text = ''):
if text[-1] == ",":
text = text[:-1]
if text[0] == ",":
text = text[:0]
settings = ScheduleSettings(
text_g=text,
pre_text_G=pre_text,
app_text_G=app_text,
text_L=None,
pre_text_L=None,
app_text_L=None,
max_frames=max_frames,
current_frame=current_frame,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=0,
end_frame=max_frames,
width=None,
height=None,
crop_w=None,
crop_h=None,
target_width=None,
target_height=None,
)
return prompt_schedule(settings, clip)
#same as the other node end except it returns a batch
class BatchPromptScheduleNodeFlowEnd:
@classmethod
def INPUT_TYPES(s):
return {"required": {"text": ("STRING", {"multiline": False, "forceInput": True}),
"clip": ("CLIP", ),
"max_frames": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0,}),
"print_output": ("BOOLEAN", {"default": False}),
},
"optional": {"pre_text": ("STRING", {"multiline": False, "forceInput": True}),
"app_text": ("STRING", {"multiline": False, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True}),
}}
RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "CONDITIONING", "CONDITIONING", "CONDITIONING", "CONDITIONING",)
RETURN_NAMES = ("POS", "NEG", "POS_CUR", "NEG_CUR", "POS_NXT", "NEG_NXT",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, text, max_frames, start_frame, end_frame, print_output, clip, pw_a=0, pw_b=0, pw_c=0, pw_d=0, pre_text='',
app_text=''):
if text[-1] == ",":
text = text[:-1]
if text[0] == ",":
text = text[:0]
settings = ScheduleSettings(
text_g=text,
pre_text_G=pre_text,
app_text_G=app_text,
text_L=None,
pre_text_L=None,
app_text_L=None,
max_frames=max_frames,
current_frame=None,
print_output=print_output,
pw_a=pw_a,
pw_b=pw_b,
pw_c=pw_c,
pw_d=pw_d,
start_frame=start_frame,
end_frame=end_frame,
width=None,
height=None,
crop_w=None,
crop_h=None,
target_width=None,
target_height=None,
)
return batch_prompt_schedule(settings, clip)
# WIP, requires some hijacking but otherwise
# applies every scheduled gligen bound box to
# a batch of latents with the scheduled
# conditionings
class BatchGLIGENSchedule:
@classmethod
def INPUT_TYPES(s):
return {"required": {"conditioning_to": ("CONDITIONING",),
"clip": ("CLIP",),
"gligen_textbox_model": ("GLIGEN",),
"text": ("STRING", {"multiline": True, "default":defaultPrompt}),
"width": ("INT", {"default": 64, "min": 8, "max": MAX_RESOLUTION, "step": 8}),
"height": ("INT", {"default": 64, "min": 8, "max": MAX_RESOLUTION, "step": 8}),
"x": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
"y": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"print_output":("BOOLEAN", {"default": False})},
"optional": {"pre_text": ("STRING", {"multiline": True, "forceInput": True}),
"app_text": ("STRING", {"multiline": True, "forceInput": True}),
"pw_a": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_b": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_c": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
"pw_d": ("FLOAT", {"default": 0.0, "min": -9999.0, "max": 9999.0, "step": 0.1, "forceInput": True }),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, conditioning_to, clip, gligen_textbox_model, text, width, height, x, y, max_frames, print_output, pw_a, pw_b, pw_c, pw_d, pre_text='', app_text=''):
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
animation_prompts = json.loads(inputText.strip())
cur_series, nxt_series, weight_series = interpolate_prompt_series(animation_prompts, max_frames, pre_text, app_text, pw_a, pw_b, pw_c, pw_d, print_output)
out = []
for i in range(0, max_frames - 1):
# Calculate changes in x and y here, based on your logic
x_change = 8
y_change = 0
# Update x and y values
x += x_change
y += y_change
out.append(self.append(conditioning_to, clip, gligen_textbox_model, pre_text, width, height, x, y))
return (out,)
def append(self, conditioning_to, clip, gligen_textbox_model, text, width, height, x, y):
c = []
cond, cond_pooled = clip.encode_from_tokens(clip.tokenize(text), return_pooled=True)
for t in range(0, len(conditioning_to)):
n = [conditioning_to[t][0], conditioning_to[t][1].copy()]
position_params = [(cond_pooled, height // 8, width // 8, y // 8, x // 8)]
prev = []
if "gligen" in n[1]:
prev = n[1]['gligen'][2]
n[1]['gligen'] = ("position", gligen_textbox_model, prev + position_params)
c.append(n)
return c
#This node parses the user's test input into
#interpolated floats. Expressions can be input
#and evaluated.
class ValueSchedule:
@classmethod
def INPUT_TYPES(s):
return {"required": {"text": ("STRING", {"multiline": True, "default":defaultValue}),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"current_frame": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0, "forceInput": True}),
"print_output": ("BOOLEAN", {"default": False})}}
RETURN_TYPES = ("FLOAT", "INT")
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/ScheduleNodes"
def animate(self, text, max_frames, current_frame, print_output):
current_frame = current_frame % max_frames
t = get_inbetweens(parse_key_frames(text, max_frames), max_frames)
if (print_output is True):
print("ValueSchedule: ",current_frame,"\n","current_frame: ",current_frame)
return (t[current_frame],int(t[current_frame]),)
class BatchValueSchedule:
@classmethod
def INPUT_TYPES(s):
return {"required": {"text": ("STRING", {"multiline": True, "default": defaultValue}),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"print_output": ("BOOLEAN", {"default": False})}}
RETURN_TYPES = ("FLOAT", "INT")
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, text, max_frames, print_output):
t = batch_get_inbetweens(batch_parse_key_frames(text, max_frames), max_frames)
if print_output is True:
print("ValueSchedule: ", t)
return (t, list(map(int,t)),)
class BatchValueScheduleLatentInput:
@classmethod
def INPUT_TYPES(s):
return {"required": {"text": ("STRING", {"multiline": True, "default": defaultValue}),
"num_latents": ("LATENT", ),
"print_output": ("BOOLEAN", {"default": False})}}
RETURN_TYPES = ("FLOAT", "INT", "LATENT", )
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/BatchScheduleNodes"
def animate(self, text, num_latents, print_output):
num_elements = sum(tensor.size(0) for tensor in num_latents.values())
max_frames = num_elements
t = batch_get_inbetweens(batch_parse_key_frames(text, max_frames), max_frames)
if print_output is True:
print("ValueSchedule: ", t)
return (t, list(map(int,t)), num_latents, )
# Expects a Batch Value Schedule list input,
# it exports an image batch with images taken
# from an input image batch.
# Original code is from:
# ComfyUI-Image-Selector by SLAPaper
# https://github.com/SLAPaper/ComfyUI-Image-Selector
# licensed under Apache-2.0
class ImagesFromBatchSchedule:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"images": ("IMAGE",),
"text": ("STRING", {"multiline": True, "default":defaultPrompt}),
"current_frame": ("INT", {"default": 0.0, "min": 0.0, "max": 999999.0, "step": 1.0, }),
"max_frames": ("INT", {"default": 120.0, "min": 1.0, "max": 999999.0, "step": 1.0}),
"print_output": ("BOOLEAN", {"default": False}),
}
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "animate"
CATEGORY = "FizzNodes 📅🅕🅝/ScheduleNodes"
def animate(self, images, text, current_frame, max_frames, print_output):
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
animation_prompts = json.loads(inputText.strip())
pos_cur_prompt, pos_nxt_prompt, weight = interpolate_prompt_series(animation_prompts, max_frames, 0, "",
"", 0,
0, 0, 0, print_output)
selImages = selectImages(images,pos_cur_prompt[current_frame])
return selImages
def selectImages(images: torch.Tensor, selected_indexes: str):
shape = images.shape
len_first_dim = shape[0]
selected_index: list[int] = []
total_indexes: list[int] = list(range(len_first_dim))
for s in selected_indexes.strip().split(','):
try:
if ":" in s:
_li = s.strip().split(':', maxsplit=1)
_start = _li[0]
_end = _li[1]
if _start and _end:
selected_index.extend(
total_indexes[int(_start) - 1:int(_end) - 1]
)
elif _start:
selected_index.extend(
total_indexes[int(_start) - 1:]
)
elif _end:
selected_index.extend(
total_indexes[:int(_end) - 1]
)
else:
x: int = int(s.strip()) - 1
if x < len_first_dim:
selected_index.append(x)
except:
pass
if selected_index:
print(f"ImageSelector: selected: {len(selected_index)} images")
return (images[selected_index], )
print(f"ImageSelector: selected no images, passthrough")
return images