nodes/bash-j-mikey_nodes
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reducing the amout of print to the console

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bash-j
2023-09-19 11:42:37 +09:30
parent b701516c2b
commit 7e9e0e1cc1
1 changed files with 111 additions and 69 deletions
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mikey_nodes.py
+111 -69
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@@ -251,7 +251,7 @@ def search_and_replace(text, extra_pnginfo, prompt):
if extra_pnginfo is None or prompt is None:
return text
# if %date: in text, then replace with date
print(text)
#print(text)
if '%date:' in text:
for match in re.finditer(r'%date:(.*?)%', text):
date_match = match.group(1)
@@ -297,10 +297,13 @@ def search_and_replace(text, extra_pnginfo, prompt):
# Map from "Node name for S&R" to id in the workflow
node_to_id_map = {}
for node in extra_pnginfo['workflow']['nodes']:
node_name = node['properties'].get('Node name for S&R')
node_id = node['id']
node_to_id_map[node_name] = node_id
try:
for node in extra_pnginfo['workflow']['nodes']:
node_name = node['properties'].get('Node name for S&R')
node_id = node['id']
node_to_id_map[node_name] = node_id
except:
return text
# Find all patterns in the text that need to be replaced
patterns = re.findall(r"%([^%]+)%", text)
@@ -311,18 +314,18 @@ def search_and_replace(text, extra_pnginfo, prompt):
# Find the id for this node name
node_id = node_to_id_map.get(node_name)
if node_id is None:
print(f"No node with name {node_name} found.")
#print(f"No node with name {node_name} found.")
continue
# Find the value of the specified widget in prompt JSON
prompt_node = prompt.get(str(node_id))
if prompt_node is None:
print(f"No prompt data for node with id {node_id}.")
#print(f"No prompt data for node with id {node_id}.")
continue
widget_value = prompt_node['inputs'].get(widget_name)
if widget_value is None:
print(f"No widget with name {widget_name} found for node {node_name}.")
#print(f"No widget with name {widget_name} found for node {node_name}.")
continue
# Replace the pattern in the text
@@ -398,24 +401,7 @@ def extract_and_load_loras(text, model, clip):
return model, clip, stripped_text
def process_random_syntax(text, seed):
# The syntax for a random number is <random:lower_bound:upper_bound>
# For example, <random:-1:0.5> will generate a random number between -1 and 0.5
print('checking for random syntax')
random.seed(seed)
random_re = r'<random:(-?\d*\.?\d+):(-?\d*\.?\d+)>'
matches = re.findall(random_re, text)
print(matches)
for match in matches:
lower_bound, upper_bound = map(float, match)
random_value = random.uniform(lower_bound, upper_bound)
random_value = round(random_value, 4)
# Replace the syntax with the generated number
text = text.replace(f'<random:{lower_bound}:{upper_bound}>', str(random_value))
print(text)
return text
def process_random_syntax(text, seed):
print('checking for random syntax')
#print('checking for random syntax')
random.seed(seed)
random_re = r'<random:(-?\d*\.?\d+):(-?\d*\.?\d+)>'
matches = re.finditer(random_re, text)
@@ -443,7 +429,7 @@ def process_random_syntax(text, seed):
# Combine the list into a single string
new_text = ''.join(new_text_list)
print(new_text)
#print(new_text)
return new_text
def read_cluts():
@@ -511,7 +497,11 @@ class WildcardProcessor:
FUNCTION = 'process'
CATEGORY = 'Mikey/Text'
def process(self, prompt, seed, prompt_, extra_pnginfo):
def process(self, prompt, seed, prompt_=None, extra_pnginfo=None):
if prompt_ is None:
prompt_ = {}
if extra_pnginfo is None:
extra_pnginfo = {}
prompt = search_and_replace(prompt, extra_pnginfo, prompt_)
prompt = find_and_replace_wildcards(prompt, seed)
return (prompt, )
@@ -810,6 +800,50 @@ class FLOATtoSTRING:
else:
return (f'{float_}', )
class RangeFloat:
# using the seed value as the step in a range
# generate a list of numbers from start to end with a step value
# then select the number at the offset value
@classmethod
def INPUT_TYPES(s):
return {"required": {"start": ("FLOAT", {"default": 0, "min": 0, "step": 0.0001, "max": 0xffffffffffffffff}),
"end": ("FLOAT", {"default": 0, "min": 0, "step": 0.0001, "max": 0xffffffffffffffff}),
"step": ("FLOAT", {"default": 0, "min": 0, "step": 0.0001, "max": 0xffffffffffffffff}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff})}}
RETURN_TYPES = ('FLOAT','STRING',)
FUNCTION = 'generate'
CATEGORY = 'Mikey/Utils'
def generate(self, start, end, step, seed):
range_ = np.arange(start, end, step)
list_of_numbers = list(range_)
# offset
offset = seed % len(list_of_numbers)
return (list_of_numbers[offset], f'{list_of_numbers[offset]}',)
class RangeInteger:
# using the seed value as the step in a range
# generate a list of numbers from start to end with a step value
# then select the number at the offset value
@classmethod
def INPUT_TYPES(s):
return {"required": {"start": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"end": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"step": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff})}}
RETURN_TYPES = ('INT','STRING',)
FUNCTION = 'generate'
CATEGORY = 'Mikey/Utils'
def generate(self, start, end, step, seed):
range_ = np.arange(start, end, step)
list_of_numbers = list(range_)
# offset
offset = seed % len(list_of_numbers)
return (list_of_numbers[offset], f'{list_of_numbers[offset]}',)
class ResizeImageSDXL:
crop_methods = ["disabled", "center"]
upscale_methods = ["nearest-exact", "bilinear", "area", "bicubic"]
@@ -831,7 +865,7 @@ class ResizeImageSDXL:
def resize(self, image, upscale_method, crop):
w, h = find_latent_size(image.shape[2], image.shape[1])
print('Resizing image from {}x{} to {}x{}'.format(image.shape[2], image.shape[1], w, h))
#print('Resizing image from {}x{} to {}x{}'.format(image.shape[2], image.shape[1], w, h))
img = self.upscale(image, upscale_method, w, h, crop)[0]
return (img, )
@@ -1000,7 +1034,7 @@ class BatchLoadImages:
img = Image.open(os.path.join(image_directory, file))
img = pil2tensor(img)
images.append(img)
print(f'Loaded {len(images)} images')
#print(f'Loaded {len(images)} images')
return (images,)
class BatchLoadTxtPrompts:
@@ -1026,7 +1060,7 @@ class BatchLoadTxtPrompts:
if file.endswith('.txt'):
with open(os.path.join(text_directory, file), 'r') as f:
strings.append(f.read())
print(f'Loaded {len(strings)} strings')
#print(f'Loaded {len(strings)} strings')
return (strings,)
def get_save_image_path(filename_prefix, output_dir, image_width=0, image_height=0):
@@ -1059,7 +1093,7 @@ def get_save_image_path(filename_prefix, output_dir, image_width=0, image_height
full_output_folder = os.path.join(output_dir, subfolder)
if os.path.commonpath((output_dir, os.path.abspath(full_output_folder))) != output_dir:
print("Saving image outside the output folder is not allowed.")
#print("Saving image outside the output folder is not allowed.")
return {}
try:
@@ -1457,12 +1491,12 @@ class PromptWithStyle:
positive_prompt = process_random_syntax(positive_prompt, seed)
negative_prompt = process_random_syntax(negative_prompt, seed)
# process wildcards
print('Positive Prompt Entered:', positive_prompt)
#print('Positive Prompt Entered:', positive_prompt)
pos_prompt = find_and_replace_wildcards(positive_prompt, seed, debug=True)
print('Positive Prompt:', pos_prompt)
print('Negative Prompt Entered:', negative_prompt)
#print('Positive Prompt:', pos_prompt)
#print('Negative Prompt Entered:', negative_prompt)
neg_prompt = find_and_replace_wildcards(negative_prompt, seed, debug=True)
print('Negative Prompt:', neg_prompt)
#print('Negative Prompt:', neg_prompt)
if pos_prompt != '' and pos_prompt != 'Positive Prompt' and pos_prompt is not None:
if '{prompt}' in self.pos_style[style]:
pos_prompt = self.pos_style[style].replace('{prompt}', pos_prompt)
@@ -1486,9 +1520,9 @@ class PromptWithStyle:
target_width, target_height = (4096, 4096 * ratio // 8 * 8) if width > height else (4096 * ratio // 8 * 8, 4096)
refiner_width = target_width
refiner_height = target_height
print('Width:', width, 'Height:', height,
'Target Width:', target_width, 'Target Height:', target_height,
'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
#print('Width:', width, 'Height:', height,
# 'Target Width:', target_width, 'Target Height:', target_height,
# 'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
latent = torch.zeros([batch_size, 4, height // 8, width // 8])
return ({"samples":latent},
str(pos_prompt),
@@ -1540,9 +1574,9 @@ class PromptWithStyleV2:
target_width, target_height = (4096, 4096 * ratio // 8 * 8) if width > height else (4096 * ratio // 8 * 8, 4096)
refiner_width = target_width
refiner_height = target_height
print('Width:', width, 'Height:', height,
'Target Width:', target_width, 'Target Height:', target_height,
'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
#print('Width:', width, 'Height:', height,
# 'Target Width:', target_width, 'Target Height:', target_height,
# 'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
# encode text
sdxl_pos_cond = CLIPTextEncodeSDXL.encode(self, clip_base, width, height, 0, 0, target_width, target_height, pos_prompt, pos_style)[0]
sdxl_neg_cond = CLIPTextEncodeSDXL.encode(self, clip_base, width, height, 0, 0, target_width, target_height, neg_prompt, neg_style)[0]
@@ -1595,9 +1629,9 @@ class PromptWithSDXL:
target_width, target_height = (4096, 4096 * ratio // 8 * 8) if width > height else (4096 * ratio // 8 * 8, 4096)
refiner_width = target_width
refiner_height = target_height
print('Width:', width, 'Height:', height,
'Target Width:', target_width, 'Target Height:', target_height,
'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
#print('Width:', width, 'Height:', height,
# 'Target Width:', target_width, 'Target Height:', target_height,
# 'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
return ({"samples":latent},
str(positive_prompt),
str(negative_prompt),
@@ -1665,7 +1699,7 @@ class PromptWithStyleV3:
lora_filename += '.safetensors'
# get the lora multiplier
lora_multiplier = float(lora_prompt[1]) if lora_prompt[1] != '' else 1.0
print('Loading LoRA: ' + lora_filename + ' with multiplier: ' + str(lora_multiplier))
#print('Loading LoRA: ' + lora_filename + ' with multiplier: ' + str(lora_multiplier))
# apply the lora to the clip using the LoraLoader.load_lora function
# def load_lora(self, model, clip, lora_name, strength_model, strength_clip):
# ...
@@ -1721,7 +1755,7 @@ class PromptWithStyleV3:
height = self.ratio_dict[ratio_selected]["height"]
latent = torch.zeros([batch_size, 4, height // 8, width // 8])
print(batch_size, 4, height // 8, width // 8)
#print(batch_size, 4, height // 8, width // 8)
# calculate dimensions for target_width, target height (base) and refiner_width, refiner_height (refiner)
ratio = min([width, height]) / max([width, height])
if target_mode == 'match':
@@ -1760,9 +1794,9 @@ class PromptWithStyleV3:
target_width, target_height = (2048, 2048 * ratio // 8 * 8) if width < height else (2048 * ratio // 8 * 8, 2048)
refiner_width, refiner_height = width * 4, height * 4
#refiner_width, refiner_height = (4096, 4096 * ratio // 8 * 8) if width > height else (4096 * ratio // 8 * 8, 4096)
print('Width:', width, 'Height:', height,
'Target Width:', target_width, 'Target Height:', target_height,
'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
#print('Width:', width, 'Height:', height,
# 'Target Width:', target_width, 'Target Height:', target_height,
# 'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
add_metadata_to_dict(prompt_with_style, width=width, height=height, target_width=target_width, target_height=target_height,
refiner_width=refiner_width, refiner_height=refiner_height, crop_w=0, crop_h=0)
# search and replace
@@ -1809,7 +1843,7 @@ class PromptWithStyleV3:
neg_style_prompts = re.findall(style_re, neg_prompt)
# concat style prompts
style_prompts = pos_style_prompts + neg_style_prompts
print(style_prompts)
#print(style_prompts)
base_pos_conds = []
base_neg_conds = []
refiner_pos_conds = []
@@ -1820,10 +1854,10 @@ class PromptWithStyleV3:
pos_style_, neg_style_ = pos_prompt_, neg_prompt_
pos_prompt_, neg_prompt_ = strip_all_syntax(pos_prompt_), strip_all_syntax(neg_prompt_)
pos_style_, neg_style_ = strip_all_syntax(pos_style_), strip_all_syntax(neg_style_)
print("pos_prompt_", pos_prompt_)
print("neg_prompt_", neg_prompt_)
print("pos_style_", pos_style_)
print("neg_style_", neg_style_)
#print("pos_prompt_", pos_prompt_)
#print("neg_prompt_", neg_prompt_)
#print("pos_style_", pos_style_)
#print("neg_style_", neg_style_)
# encode text
add_metadata_to_dict(prompt_with_style, style=style_, clip_g_positive=pos_prompt, clip_l_positive=pos_style_)
add_metadata_to_dict(prompt_with_style, clip_g_negative=neg_prompt, clip_l_negative=neg_style_)
@@ -1840,13 +1874,13 @@ class PromptWithStyleV3:
""" get output from PromptWithStyle.start """
# strip all style syntax from prompt
style_ = style_prompt
print(style_ in self.styles)
#print(style_ in self.styles)
if style_ not in self.styles:
# try to match a key without being case sensitive
style_search = next((x for x in self.styles if x.lower() == style_.lower()), None)
# if there are still no matches
if style_search is None:
print(f'Could not find style: {style_}')
#print(f'Could not find style: {style_}')
style_ = 'none'
continue
else:
@@ -1950,6 +1984,7 @@ class LoraSyntaxProcessor:
lora_prompts = re.findall(lora_re, text)
stripped_text = text
# if we found any lora prompts
clip_lora = clip
if len(lora_prompts) > 0:
# loop through each lora prompt
for lora_prompt in lora_prompts:
@@ -1960,7 +1995,7 @@ class LoraSyntaxProcessor:
lora_filename += '.safetensors'
# get the lora multiplier
lora_multiplier = float(lora_prompt[1]) if lora_prompt[1] != '' else 1.0
print('Loading LoRA: ' + lora_filename + ' with multiplier: ' + str(lora_multiplier))
#print('Loading LoRA: ' + lora_filename + ' with multiplier: ' + str(lora_multiplier))
model, clip_lora = LoraLoader.load_lora(self, model, clip, lora_filename, lora_multiplier, lora_multiplier)
# strip lora syntax from text
stripped_text = re.sub(lora_re, '', stripped_text)
@@ -1997,6 +2032,7 @@ class WildcardAndLoraSyntaxProcessor:
lora_prompts = re.findall(lora_re, text)
stripped_text = text
# if we found any lora prompts
clip_lora = clip
if len(lora_prompts) > 0:
# loop through each lora prompt
for lora_prompt in lora_prompts:
@@ -2007,7 +2043,7 @@ class WildcardAndLoraSyntaxProcessor:
lora_filename += '.safetensors'
# get the lora multiplier
lora_multiplier = float(lora_prompt[1]) if lora_prompt[1] != '' else 1.0
print('Loading LoRA: ' + lora_filename + ' with multiplier: ' + str(lora_multiplier))
#print('Loading LoRA: ' + lora_filename + ' with multiplier: ' + str(lora_multiplier))
# apply the lora to the clip using the LoraLoader.load_lora function
# def load_lora(self, model, clip, lora_name, strength_model, strength_clip):
# ...
@@ -2209,7 +2245,7 @@ class MikeySampler:
return (vaeencoder.encode(vae, img)[0],)
# Adjust start_step based on complexity
image_complexity = calculate_image_complexity(img)
print('Image Complexity:', image_complexity)
#print('Image Complexity:', image_complexity)
start_step = self.adjust_start_step(image_complexity, hires_strength)
# encode image
latent = vaeencoder.encode(vae, img)[0]
@@ -2271,7 +2307,7 @@ class MikeySamplerBaseOnly:
return (vaeencoder.encode(vae, img)[0],)
# Adjust start_step based on complexity
image_complexity = calculate_image_complexity(img)
print('Image Complexity:', image_complexity)
#print('Image Complexity:', image_complexity)
start_step = self.adjust_start_step(image_complexity, hires_strength)
# encode image
latent = vaeencoder.encode(vae, img)[0]
@@ -2331,7 +2367,7 @@ class MikeySamplerBaseOnlyAdvanced:
last_step = steps // 2 - 1
else:
last_step = steps // 2
print(f'base model start_step: {start_step}, last_step: {last_step}')
#print(f'base model start_step: {start_step}, last_step: {last_step}')
sample1 = common_ksampler(base_model, seed, steps, cfg_1, sampler_name, scheduler,
positive_cond_base, negative_cond_base, samples,
start_step=start_step, last_step=last_step, force_full_denoise=False)[0]
@@ -2489,7 +2525,7 @@ def ai_upscale(tile, base_model, vae, seed, positive_cond_base, negative_cond_ba
vaeencoder = VAEEncode()
tile = pil2tensor(tile)
complexity = calculate_image_complexity(tile)
print('Tile Complexity:', complexity)
#print('Tile Complexity:', complexity)
if use_complexity_score == 'true':
if complexity < 8:
start_step = 15
@@ -2617,13 +2653,13 @@ class MikeySamplerTiledAdvanced:
last_step = steps // 2 - 1
else:
last_step = steps // 2
print(f'base model start_step: {start_step}, last_step: {last_step}')
#print(f'base model start_step: {start_step}, last_step: {last_step}')
sample1 = common_ksampler(base_model, seed, steps, cfg, sampler_name, scheduler, positive_cond_base, negative_cond_base, samples,
start_step=start_step, last_step=last_step, force_full_denoise=False)[0]
# step 2 run refiner model
start_step = last_step + 1
total_steps = steps + smooth_step
print(f'refiner model start_step: {start_step}, last_step: {total_steps}')
#print(f'refiner model start_step: {start_step}, last_step: {total_steps}')
sample2 = common_ksampler(refiner_model, seed, total_steps, cfg, sampler_name, scheduler, positive_cond_refiner, negative_cond_refiner, sample1,
disable_noise=True, start_step=start_step, force_full_denoise=True)[0]
# step 3 upscale image using a simple AI image upscaler
@@ -2706,7 +2742,7 @@ class MikeySamplerTiledBaseOnly(MikeySamplerTiled):
# phase 1: run base, refiner, then upscaler model
img, upscaled_width, upscaled_height = self.phase_one(base_model, samples, positive_cond_base, negative_cond_base,
upscale_by, model_name, seed, vae)
print('img shape: ', img.shape)
#print('img shape: ', img.shape)
# phase 2: run tiler
img = tensor2pil(img)
tiled_image = run_tiler(img, base_model, vae, seed, positive_cond_base, negative_cond_base, tiler_denoise)
@@ -2812,14 +2848,14 @@ class UpscaleTileCalculator:
def resize(self, image, width, height, upscale_method, crop):
w, h = find_latent_size(image.shape[2], image.shape[1])
print('Resizing image from {}x{} to {}x{}'.format(image.shape[2], image.shape[1], w, h))
#print('Resizing image from {}x{} to {}x{}'.format(image.shape[2], image.shape[1], w, h))
img = self.upscale(image, upscale_method, w, h, crop)[0]
return (img, )
def calculate(self, image, tile_resolution):
width, height = image.shape[2], image.shape[1]
tile_width, tile_height = find_tile_dimensions(width, height, 1.0, tile_resolution)
print('Tile width: ' + str(tile_width), 'Tile height: ' + str(tile_height))
#print('Tile width: ' + str(tile_width), 'Tile height: ' + str(tile_height))
return (image, tile_width, tile_height)
class IntegerAndString:
@@ -2881,7 +2917,9 @@ class ImageCaption:
wrapped_lines.append(new_line)
return wrapped_lines
def caption(self, image, font, caption, extra_pnginfo, prompt):
def caption(self, image, font, caption, extra_pnginfo=None, prompt=None):
if extra_pnginfo is None:
extra_pnginfo = {}
# search and replace
caption = search_and_replace(caption, extra_pnginfo, prompt)
# Convert tensor to PIL image
@@ -3144,6 +3182,8 @@ NODE_CLASS_MAPPINGS = {
'Ratio Advanced': RatioAdvanced,
'Int to String': INTtoSTRING,
'Float to String': FLOATtoSTRING,
'Range Float': RangeFloat,
'Range Integer': RangeInteger,
'Save Image With Prompt Data': SaveImagesMikey,
'Save Images Mikey': SaveImagesMikeyML,
'Save Images No Display': SaveImageNoDisplay,
@@ -3189,6 +3229,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
'Ratio Advanced': 'Ratio Advanced (Mikey)',
'Int to String': 'Int to String (Mikey)',
'Float to String': 'Float to String (Mikey)',
'Range Float': 'Range Float (Mikey)',
'Range Integer': 'Range Integer (Mikey)',
'Save Images With Prompt Data': 'Save Image With Prompt Data (Mikey)',
'Save Images Mikey': 'Save Images Mikey (Mikey)',
'Save Images No Display': 'Save Images No Display (Mikey)',