nodes/KLL535-ComfyUI_SimpleButcher
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v1.0.4_alfa

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KLL535
2025-02-03 02:20:37 +03:00
parent 458ff3b6f2
commit 423fdec4fe
2 changed files with 148 additions and 89 deletions
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CHANGELOG.md
+2 -1
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@@ -1,7 +1,8 @@
# nightly
- update `Simple Load Image With Metadata` and `Simple Image Saver (as Forge)`
# v1.0.3
- fix random
- add node Simple Load Image With Metadata
- add node `Simple Load Image With Metadata`
# v1.0.2
- fastest load LoRA hash
- add button **Update LoRA dictionary** in `Simple Lora Loader` for update **lora_name.json**
nodes/nodes.py
+146 -88
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@@ -482,12 +482,12 @@ class SimpleImageSaver:
return {
"required": {
"images": ("IMAGE", { "tooltip": "image(s) to save", "forceInput": True}),
"prompt": ("STRING", {"default": "", "multiline": False, "tooltip": "STRING", "forceInput": True}),
"output_path": ("STRING", {"default": "", "multiline": False, "tooltip": "Path where images will be saved"}),
"SEED": ("INT", {"default": '0', "tooltip": "INT", "forceInput": True}),
"modelname": ("STRING", {"default": '', "multiline": False, "tooltip": "STRING, use Checkpoint Loader with Name (Image Saver) node", "forceInput": True}),
},
"optional": {
"prompt_text": ("STRING", {"default": "", "multiline": False, "tooltip": "STRING", "forceInput": True}),
"SEED": ("INT", {"default": None, "tooltip": "INT", "forceInput": True}),
"modelname": ("STRING", {"default": '', "multiline": False, "tooltip": "STRING, use Checkpoint Loader with Name (Image Saver) node", "forceInput": True}),
"steps": ("INT", {"default": 0, "tooltip": "INT", "forceInput": True}),
"sampler": (any, {"default": None, "tooltip": "ANY, use Sampler Selector (Image Saver) node", "forceInput": True}),
"schedule": (any, {"default": None, "tooltip": "ANY, use Scheduler Selector (Image Saver) node", "forceInput": True}),
@@ -500,10 +500,15 @@ class SimpleImageSaver:
"civitai_lora": ("STRING", {"default": '', "multiline": False, "tooltip": "STRING, Loras name from Simple Lora Loader node", "forceInput": True}),
"civitai_lora_hash": ("STRING", {"default": '', "multiline": False, "tooltip": "STRING, Loras hash from Simple Lora Loader node", "forceInput": True}),
"negative": ("STRING", {"default": '', "multiline": False, "tooltip": "STRING, Negative prompt", "forceInput": True}),
"save_workflow": ("BOOLEAN", {"default": False, "tooltip": "if True, saves workflow in the image"}),
"save_comfy_workflow": ("BOOLEAN", {"default": True, "tooltip": "if True, saves workflow in the image"}),
"save_comfy_prompt": ("BOOLEAN", {"default": False, "tooltip": "if True, saves workflow in the image"}),
"override_parameters": ("STRING", {"default": None, "multiline": False, "tooltip": "If present, this text will be written to image metadata (parameters)", "forceInput": True}),
"override_workflow": ("STRING", {"default": None, "multiline": False, "tooltip": "If present, this text will be written to image metadata (workflow)", "forceInput": True}),
"override_prompt": ("STRING", {"default": None, "multiline": False, "tooltip": "If present, this text will be written to image metadata (prompt)", "forceInput": True}),
},
"hidden": {
"extra_pnginfo": "EXTRA_PNGINFO",
"prompt": "PROMPT",
"extra_pnginfo": "EXTRA_PNGINFO",
},
}
@@ -528,22 +533,123 @@ class SimpleImageSaver:
i = new
return i+1
def image_saver(self, images, prompt, output_path, SEED, modelname, steps=0, sampler=None, schedule=None, CFG_scale=0.0, distilled_CFG_scale=0.0, width=0, height=0, beta_schedule_alpha=0.0, beta_schedule_beta=0.0, civitai_lora="", civitai_lora_hash="",negative="",save_workflow=False,extra_pnginfo=None):
def parse_parameters(self, text):
pattern = r"\s*,\s*(?![^\"]*\"\,)"
items = re.split(pattern, text)
params = {}
for item in items:
if ":" in item:
key, value = item.split(":", 1)
params[key.strip()] = value.strip()
return params
metadata_text = ""
def image_saver(self, images, output_path, prompt_text = "", SEED = None, modelname = "", steps=0, sampler=None, schedule=None, CFG_scale=0.0, distilled_CFG_scale=0.0, width=0, height=0, beta_schedule_alpha=0.0, beta_schedule_beta=0.0, civitai_lora="", civitai_lora_hash="", negative="", save_comfy_workflow=True, save_comfy_prompt=False, override_parameters=None, override_workflow=None, override_prompt=None, prompt=None, extra_pnginfo=None):
now = datetime.now()
date = now.strftime("%Y-%m-%d")
output_path = output_path.strip()
if output_path == '':
return ()
return ("",)
output_path = os.path.join(output_path, date)
if not os.path.exists(output_path):
os.makedirs(output_path, exist_ok=True)
seed_text = ""
if SEED != None:
seed_text = str(SEED)
##### metadata parameters (Forge style) #####
forge = ""
if override_parameters == None:
prompt_and_lora = prompt_text
if civitai_lora != "":
prompt_and_lora = prompt_and_lora + ' ' + civitai_lora
forge = prompt_and_lora + '\n'
if negative != "":
forge = forge + "Negative prompt: "+ negative + '\n'
if steps != 0:
forge = forge + "Steps: "+str(steps)+", "
if sampler != None:
forge = forge + "Sampler: "+str(sampler)+", "
if schedule != None:
forge = forge + "Schedule type: "+str(schedule)+", "
if CFG_scale != 0.0:
forge = forge + "CFG scale: "+str(CFG_scale)+", "
if distilled_CFG_scale != 0.0:
forge = forge + "Distilled CFG Scale: "+str(distilled_CFG_scale)+", "
forge = forge + "Seed: "+seed_text+", "
if width != 0:
if height != 0:
forge = forge + "Size: " + str(width) + "x" + str(height) + ", "
if modelname != "":
ckpt_path = folder_paths.get_full_path("checkpoints", modelname)
if not ckpt_path:
ckpt_path = folder_paths.get_full_path("diffusion_models", modelname)
if ckpt_path:
modelhash = get_sha256(self,ckpt_path)[:10]
else:
modelhash = ""
if modelhash != "":
forge = forge + "Model hash: "+modelhash+", "
modelname = os.path.basename(modelname)
modelname = os.path.splitext(modelname)[0]
if modelname != "":
forge = forge + "Model: "+modelname+", "
if beta_schedule_alpha != 0.0:
forge = forge + "Beta schedule alpha: "+str(beta_schedule_alpha)+", "
if beta_schedule_beta != 0.0:
forge = forge + "Beta schedule beta: "+str(beta_schedule_beta)+", "
if civitai_lora_hash != "":
forge = forge + "Lora hashes: \"" + civitai_lora_hash + "\", "
forge = forge + "Version: ComfyUI"
else:
forge = override_parameters
params = self.parse_parameters(forge)
seed = params.get("Seed")
if seed is not None:
seed_text = seed
##### metadata prompt (Сomfy-ui style) #####
prompt_json = ""
if save_comfy_prompt:
if override_prompt == None:
if prompt is not None:
try:
prompt_json = json.dumps(prompt)
except Exception as e:
print(f"\033[91mJSON coding error (prompt)\033[0m")
else:
prompt_json = override_prompt
##### metadata workflow (Сomfy-ui style) #####
workflow_json = ""
if save_comfy_workflow:
if override_workflow == None:
if extra_pnginfo is not None:
if "workflow" in extra_pnginfo:
try:
workflow_json = json.dumps(extra_pnginfo["workflow"])
except Exception as e:
print(f"\033[91mJSON coding error (workflow)\033[0m")
else:
workflow_json = override_workflow
##### images #####
for image in images:
i = 255. * image.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
@@ -551,79 +657,25 @@ class SimpleImageSaver:
free_number = self.find_free_number(output_path)
if free_number > 99999:
print(f"\033[91mToo many files\033[0m")
return ()
seed_text = str(SEED)
####################
##### metadata #####
prompt_and_lora = prompt
if civitai_lora != "":
prompt_and_lora = prompt_and_lora + ' ' + civitai_lora
metadata_text = prompt_and_lora + '\n'
if negative != "":
metadata_text = metadata_text + "Negative prompt: "+ negative + '\n'
if steps != 0:
metadata_text = metadata_text + "Steps: "+str(steps)+", "
if sampler != None:
metadata_text = metadata_text + "Sampler: "+str(sampler)+", "
if schedule != None:
metadata_text = metadata_text + "Schedule type: "+str(schedule)+", "
if CFG_scale != 0.0:
metadata_text = metadata_text + "CFG scale: "+str(CFG_scale)+", "
if distilled_CFG_scale != 0.0:
metadata_text = metadata_text + "Distilled CFG Scale: "+str(distilled_CFG_scale)+", "
metadata_text = metadata_text + "Seed: "+seed_text+", "
if width != 0:
if height != 0:
metadata_text = metadata_text + "Size: " + str(width) + "x" + str(height) + ", "
ckpt_path = folder_paths.get_full_path("checkpoints", modelname)
if not ckpt_path:
ckpt_path = folder_paths.get_full_path("diffusion_models", modelname)
if ckpt_path:
modelhash = get_sha256(self,ckpt_path)[:10]
else:
modelhash = ""
if modelhash != "":
metadata_text = metadata_text + "Model hash: "+modelhash+", "
modelname = os.path.basename(modelname)
modelname = os.path.splitext(modelname)[0]
if modelname != "":
metadata_text = metadata_text + "Model: "+modelname+", "
if beta_schedule_alpha != 0.0:
metadata_text = metadata_text + "Beta schedule alpha: "+str(beta_schedule_alpha)+", "
if beta_schedule_beta != 0.0:
metadata_text = metadata_text + "Beta schedule beta: "+str(beta_schedule_beta)+", "
if civitai_lora_hash != "":
metadata_text = metadata_text + "Lora hashes: \"" + civitai_lora_hash + "\", "
metadata_text = metadata_text + "Version: ComfyUI"
return ("",)
metadata = PngInfo()
metadata.add_text("parameters", metadata_text)
metadata.add_text("parameters", forge)
if prompt_json != "":
metadata.add_text("prompt", prompt_json)
if workflow_json != "":
metadata.add_text("workflow", workflow_json)
if save_workflow:
if prompt_and_lora != "":
metadata.add_text("prompt", prompt_and_lora)
if extra_pnginfo is not None:
for x in extra_pnginfo:
print(f"Write {x}")
metadata.add_text(x, json.dumps(extra_pnginfo[x]))
##### metadata #####
####################
filename = f"{free_number:05d}-{seed_text}.png"
if seed_text != "":
filename = f"{free_number:05d}-{seed_text}.png"
else:
filename = f"{free_number:05d}.png"
img.save(os.path.join(output_path, filename), pnginfo=metadata, optimize=False)
return (metadata_text,)
print(f"\033[92mImage save\033[0m")
return (forge,)
################################
@@ -637,8 +689,8 @@ class SimpleLoadImageWithMetadataString:
{"image": (sorted(files), )},
}
CATEGORY = "📚 SimpleButcher"
RETURN_TYPES = ("IMAGE", "MASK", "STRING", "STRING")
RETURN_NAMES = ("image", "mask", "metadata_forge", "prompt")
RETURN_TYPES = ("IMAGE", "MASK", "STRING", "STRING", "STRING")
RETURN_NAMES = ("image", "mask", "metadata_parameters (forge)", "metadata_workflow", "metadata_prompt")
FUNCTION = "read_image"
DESCRIPTION = "Load Image with metadata in simple string!"
@@ -658,19 +710,25 @@ class SimpleLoadImageWithMetadataString:
format = i.format
metadata = i.info
#exif_workflow = ""
#if "workflow" in metadata:
# exif_workflow = metadata["workflow"]
##### metadata parameters (Forge style) #####
exif_prompt = ""
if "prompt" in metadata:
exif_prompt = metadata["prompt"]
exif_metadata = ""
forge = ""
if "parameters" in metadata:
exif_metadata = metadata["parameters"]
forge = metadata["parameters"]
return (image, mask, exif_metadata, exif_prompt)
##### metadata prompt (Сomfy-ui style) #####
prompt_json = ""
if "prompt" in metadata:
prompt_json = metadata["prompt"]
##### metadata workflow (Сomfy-ui style) #####
workflow_json = ""
if "workflow" in metadata:
workflow_json = metadata["workflow"]
return (image, mask, forge, workflow_json, prompt_json)
@classmethod
def IS_CHANGED(s, image):