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#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 (
check_is_number, interpolate_prompts_SDXL, PoolAnimConditioning,
interpolate_string, addWeighted, reverseConcatenation, split_weighted_subprompts
)
from .BatchFuncs import interpolate_prompt_series, BatchPoolAnimConditioning, BatchInterpolatePromptsSDXL, batch_split_weighted_subprompts #, BatchGLIGENConditioning
from .ValueFuncs import batch_get_inbetweens, batch_parse_key_frames, parse_key_frames, get_inbetweens, sanitize_value
#Max resolution value for Gligen area calculation.
MAX_RESOLUTION=8192
defaultPrompt=""""0" :"",
"12" :"",
"24" :"",
"36" :"",
"48" :"",
"60" :"",
"72" :"",
"84" :"",
"96" :"",
"108" :"",
"120" :""
"""
defaultValue="""0:(0),
12:(0),
24:(0),
36:(0),
48:(0),
60:(0),
72:(0),
84:(0),
96:(0),
108:(0),
120:(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,}),
"print_output":("BOOLEAN", {"default": False}),},# "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 πŸ“…πŸ…•πŸ…/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=''):
current_frame = current_frame % max_frames
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
animation_prompts = json.loads(inputText.strip())
start_frame = 0
pos, neg = batch_split_weighted_subprompts(animation_prompts, pre_text, app_text)
pos_cur_prompt, pos_nxt_prompt, weight = interpolate_prompt_series(pos, max_frames, start_frame, pre_text, app_text, pw_a,
pw_b, pw_c, pw_d, print_output)
pc = PoolAnimConditioning(pos_cur_prompt[current_frame], pos_nxt_prompt[current_frame], weight[current_frame], clip)
neg_cur_prompt, neg_nxt_prompt, weight = interpolate_prompt_series(neg, max_frames, start_frame, pre_text, app_text, pw_a,
pw_b, pw_c, pw_d, print_output)
nc = PoolAnimConditioning(neg_cur_prompt[current_frame], neg_nxt_prompt[current_frame], weight[current_frame], clip)
return (pc, nc,)
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}),},
# "forceInput": True}),},
"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, }),
"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 πŸ“…πŸ…•πŸ…/BatchScheduleNodes"
def animate(self, text, max_frames, print_output, clip, start_frame, pw_a, pw_b, pw_c, pw_d, pre_text='', app_text=''):
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
max_frames += start_frame
animation_prompts = json.loads(inputText.strip())
pos, neg = batch_split_weighted_subprompts(animation_prompts, pre_text, app_text)
pos_cur_prompt, pos_nxt_prompt, weight = interpolate_prompt_series(pos, max_frames, start_frame, pre_text, app_text, pw_a, pw_b, pw_c, pw_d, print_output)
pc = BatchPoolAnimConditioning( pos_cur_prompt, pos_nxt_prompt, weight, clip,)
neg_cur_prompt, neg_nxt_prompt, weight = interpolate_prompt_series(neg, max_frames, start_frame, pre_text, app_text, pw_a, pw_b, pw_c, pw_d, print_output)
nc = BatchPoolAnimConditioning(neg_cur_prompt, neg_nxt_prompt, weight, clip, )
return (pc, nc, )
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}),},
# "forceInput": True}),},
"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, }),
"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", )
RETURN_NAMES = ("POS", "NEG", "INPUT_LATENTS",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/BatchScheduleNodes"
def animate(self, text, num_latents, print_output, clip, start_frame, pw_a, pw_b, pw_c, pw_d, pre_text='', app_text=''):
max_frames = sum(tensor.size(0) for tensor in num_latents.values())
max_frames += start_frame
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
animation_prompts = json.loads(inputText.strip())
pos, neg = batch_split_weighted_subprompts(animation_prompts, pre_text, app_text)
pos_cur_prompt, pos_nxt_prompt, weight = interpolate_prompt_series(pos, max_frames, start_frame, pre_text,
app_text, pw_a, pw_b, pw_c, pw_d,
print_output)
pc = BatchPoolAnimConditioning(pos_cur_prompt, pos_nxt_prompt, weight, clip, )
neg_cur_prompt, neg_nxt_prompt, weight = interpolate_prompt_series(neg, max_frames, start_frame, pre_text,
app_text, pw_a, pw_b, pw_c, pw_d,
print_output)
nc = BatchPoolAnimConditioning(neg_cur_prompt, neg_nxt_prompt, weight, clip, )
return (pc, nc, num_latents,)
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, })},
# "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 = ("STRING",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/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=''):
current_frame = current_frame % max_frames
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
animation_prompts = json.loads(inputText.strip())
cur_prompt = interpolate_string(animation_prompts, max_frames, current_frame, pre_text,
app_text, pw_a, pw_b, pw_c, pw_d)
#c = PoolAnimConditioning(cur_prompt, nxt_prompt, weight, clip, )
return (cur_prompt,)
class PromptScheduleSDXLRefiner:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"ascore": ("FLOAT", {"default": 6.0, "min": 0.0, "max": 1000.0, "step": 0.01}),
"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"text": ("STRING", {"multiline": True, "default":defaultPrompt}), "clip": ("CLIP", ),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "encode"
CATEGORY = "advanced/conditioning"
def encode(self, clip, ascore, width, height, text):
tokens = clip.tokenize(text)
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True)
return ([[cond, {"pooled_output": pooled, "aesthetic_score": ascore, "width": width,"height": height}]], )
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}),},
# "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 = ("STRING",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/BatchScheduleNodes"
def animate(self, text, max_frames, pw_a=0, pw_b=0, pw_c=0, pw_d=0, pre_text='', app_text=''):
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
start_frame = 0
animation_prompts = json.loads(inputText.strip())
cur_prompt_series, nxt_prompt_series, weight_series = interpolate_prompt_series(animation_prompts, max_frames, start_frame, pre_text,
app_text, pw_a, pw_b, pw_c, pw_d)
return (cur_prompt_series,)
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 }),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/BatchScheduleNodes"
def animate(self, clip, width, height, crop_w, crop_h, target_width, target_height, text_g, text_l, app_text_G, app_text_L, pre_text_G, pre_text_L, max_frames, print_output, pw_a, pw_b, pw_c, pw_d):
inputTextG = str("{" + text_g + "}")
inputTextL = str("{" + text_l + "}")
inputTextG = re.sub(r',\s*}', '}', inputTextG)
inputTextL = re.sub(r',\s*}', '}', inputTextL)
animation_promptsG = json.loads(inputTextG.strip())
animation_promptsL = json.loads(inputTextL.strip())
return (BatchInterpolatePromptsSDXL(animation_promptsG, animation_promptsL, max_frames, clip, app_text_G, app_text_L, pre_text_G, pre_text_L, pw_a, pw_b, pw_c, pw_d, width, height, crop_w, crop_h, target_width, target_height, print_output,),)
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 }),
}}
RETURN_TYPES = ("CONDITIONING", "LATENT",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/BatchScheduleNodes"
def animate(self, clip, width, height, crop_w, crop_h, target_width, target_height, text_g, text_l, app_text_G, app_text_L, pre_text_G, pre_text_L, num_latents, print_output, pw_a, pw_b, pw_c, pw_d):
max_frames = sum(tensor.size(0) for tensor in num_latents.values())
inputTextG = str("{" + text_g + "}")
inputTextL = str("{" + text_l + "}")
inputTextG = re.sub(r',\s*}', '}', inputTextG)
inputTextL = re.sub(r',\s*}', '}', inputTextL)
animation_promptsG = json.loads(inputTextG.strip())
animation_promptsL = json.loads(inputTextL.strip())
return (BatchInterpolatePromptsSDXL(animation_promptsG, animation_promptsL, max_frames, clip, app_text_G, app_text_L, pre_text_G, pre_text_L, pw_a, pw_b, pw_c, pw_d, width, height, crop_w, crop_h, target_width, target_height, print_output, ), num_latents, )
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",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/ScheduleNodes"
def animate(self, clip, width, height, crop_w, crop_h, target_width, target_height, text_g, text_l, app_text_G, app_text_L, pre_text_G, pre_text_L, max_frames, current_frame, print_output, pw_a, pw_b, pw_c, pw_d):
current_frame = current_frame % max_frames
inputTextG = str("{" + text_g + "}")
inputTextL = str("{" + text_l + "}")
inputTextG = re.sub(r',\s*}', '}', inputTextG)
inputTextL = re.sub(r',\s*}', '}', inputTextL)
animation_promptsG = json.loads(inputTextG.strip())
animation_promptsL = json.loads(inputTextL.strip())
return (interpolate_prompts_SDXL(animation_promptsG, animation_promptsL, max_frames, current_frame, clip, app_text_G, app_text_L, pre_text_G, pre_text_L, pw_a, pw_b, pw_c, pw_d, width, height, crop_w, crop_h, target_width, target_height, print_output,),)
# 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,})}} # "forceInput": True}),}}
RETURN_TYPES = ("INT","STRING",)
FUNCTION = "addString"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/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 πŸ“…πŸ…•πŸ…/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 = ''):
current_frame = current_frame % max_frames
if text[-1] == ",":
text = text[:-1]
if text[0] == ",":
text = text[:0]
start_frame = 0
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
animation_prompts = json.loads(inputText.strip())
max_frames += start_frame
pos, neg = batch_split_weighted_subprompts(animation_prompts, pre_text, app_text)
pos_cur_prompt, pos_nxt_prompt, weight = interpolate_prompt_series(pos, max_frames, start_frame, pre_text, app_text, pw_a,
pw_b, pw_c, pw_d, print_output)
pc = PoolAnimConditioning(pos_cur_prompt[current_frame], pos_nxt_prompt[current_frame], weight[current_frame],
clip, )
neg_cur_prompt, neg_nxt_prompt, weight = interpolate_prompt_series(neg, max_frames, start_frame, pre_text, app_text, pw_a,
pw_b, pw_c, pw_d, print_output)
nc = PoolAnimConditioning(neg_cur_prompt[current_frame], neg_nxt_prompt[current_frame], weight[current_frame],
clip, )
return (pc, nc,)
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",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/BatchScheduleNodes"
def animate(self, text, max_frames, start_frame, print_output, clip, pw_a=0, pw_b=0, pw_c=0, pw_d=0, pre_text='', current_frame = 0,
app_text=''):
if text[-1] == ",":
text = text[:-1]
if text[0] == ",":
text = text[:0]
inputText = str("{" + text + "}")
inputText = re.sub(r',\s*}', '}', inputText)
animation_prompts = json.loads(inputText.strip())
max_frames += start_frame
pos, neg = batch_split_weighted_subprompts(animation_prompts, pre_text, app_text)
pos_cur_prompt, pos_nxt_prompt, weight = interpolate_prompt_series(pos, max_frames, start_frame, pre_text, app_text, pw_a,
pw_b, pw_c, pw_d, print_output)
pc = BatchPoolAnimConditioning(pos_cur_prompt[current_frame], pos_nxt_prompt[current_frame], weight[current_frame],
clip, )
neg_cur_prompt, neg_nxt_prompt, weight = interpolate_prompt_series(neg, max_frames, start_frame, pre_text, app_text, pw_a,
pw_b, pw_c, pw_d, print_output)
nc = BatchPoolAnimConditioning(neg_cur_prompt[current_frame], neg_nxt_prompt[current_frame], weight[current_frame],
clip, )
return (pc, nc,)
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})},
# "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",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/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
print(x)
print(y)
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 πŸ“…πŸ…•πŸ…/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 πŸ“…πŸ…•πŸ…/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 πŸ“…πŸ…•πŸ…/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
class ImageBatchFromValueSchedule:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"images": ("IMAGE",),
"values": ("FLOAT", { "default": 1.0, "min": -1.0, "max": 1.0, "label": "values" }),
}
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "animate"
CATEGORY = "FizzNodes πŸ“…πŸ…•πŸ…/BatchScheduleNodes"
def animate(self, images, values):
values = [values] * n if isinstance(values, float) else values
min_value, max_value = min(values), max(values)
i = [(x - min_value) / (max_value - min_value) * (images.shape[0] - 1) for x in values]
return (images[i], )