333 lines
15 KiB
Python
333 lines
15 KiB
Python
import json
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from ..exif.base_format import BaseFormat
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from ....components import utility
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# comfyui node types
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KSAMPLER_TYPES = ["KSampler", "KSamplerAdvanced"]
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VAE_ENCODE_TYPE = ["VAEEncode", "VAEEncodeForInpaint"]
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CHECKPOINT_LOADER_TYPE = [
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"CheckpointLoader",
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"CheckpointLoaderSimple",
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"unCLIPCheckpointLoader",
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"Checkpoint Loader (Simple)",
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]
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CLIP_TEXT_ENCODE_TYPE = [
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"CLIPTextEncode",
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"CLIPTextEncodeSDXL",
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"CLIPTextEncodeSDXLRefiner",
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]
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SAVE_IMAGE_TYPE = ["SaveImage", "Image Save"]
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class ComfyUI(BaseFormat):
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def __init__(self, info: dict = None, raw: str = ""):
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super().__init__(info, raw)
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self._comfy_png()
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def _comfy_png(self):
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prompt = self._info.get("prompt") or {}
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workflow = self._info.get("workflow") or {}
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prompt_json = json.loads(prompt)
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# find end node of each flow
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end_nodes = list(filter( lambda item: item[-1].get("class_type") in ["SaveImage"] + KSAMPLER_TYPES, prompt_json.items(),))
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longest_flow = {}
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longest_nodes = []
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longest_flow_len = 0
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for end_node in end_nodes:
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flow, nodes = self._comfy_traverse(prompt_json, str(end_node[0]))
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if len(nodes) > longest_flow_len:
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longest_flow = flow
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longest_nodes = nodes
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longest_flow_len = len(nodes)
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SizeID = None
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ModelID = None
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PositiveID = None
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NegativeID = None
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if 'latent_image' in flow:
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SizeID = flow['latent_image'][0]
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if 'model' in flow:
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ModelID = flow['model'][0]
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if 'positive' in flow:
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PositiveID = flow['positive'][0]
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if 'negative' in flow:
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NegativeID = flow['negative'][0]
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FINAL_DICT = {}
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FINAL_DICT['negative'] = ""
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FINAL_DICT['positive'] = ""
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if PositiveID and NegativeID and 'text_g' in prompt_json[PositiveID]['inputs']:
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FINAL_DICT['positive'] = prompt_json[PositiveID]['inputs']['text_g']
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FINAL_DICT['negative'] = prompt_json[NegativeID]['inputs']['text_g']
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if PositiveID and NegativeID and 'text' in prompt_json[PositiveID]['inputs']:
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FINAL_DICT['positive'] = prompt_json[PositiveID]['inputs']['text']
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FINAL_DICT['negative'] = prompt_json[NegativeID]['inputs']['text']
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if PositiveID == None or ('text_g' not in prompt_json[PositiveID]['inputs'] and 'text' not in prompt_json[PositiveID]['inputs']):
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if hasattr(self, '_positive'):
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FINAL_DICT['positive'] = self._positive
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if hasattr(self, '_negative'):
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FINAL_DICT['negative'] = self._negative
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if 'steps' in flow and type(flow['steps']) == int:
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FINAL_DICT['steps'] = flow['steps']
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if 'sampler_name' in flow and 'scheduler' in flow and type(flow['sampler_name']) == str and type(flow['scheduler']) == str:
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FINAL_DICT['sampler'] = flow['sampler_name'] + ' ' + flow['scheduler']
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if 'seed' in flow and type(flow['seed']) == int:
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FINAL_DICT['seed'] = flow['seed']
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if 'cfg' in flow and (type(flow['cfg']) == int or type(flow['cfg']) == float):
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FINAL_DICT['cfg_scale'] = flow['cfg']
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if ModelID and 'ckpt_name' in prompt_json[ModelID]['inputs'] and type(prompt_json[ModelID]['inputs']['ckpt_name']) == str:
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FINAL_DICT['model_name'] = prompt_json[ModelID]['inputs']['ckpt_name'] # flow['ckpt_name']
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elif 'ckpt_name' in flow and type(flow['ckpt_name']) == str:
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FINAL_DICT['model_name'] = flow['ckpt_name']
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if SizeID and 'width' in prompt_json[SizeID]['inputs'] and 'height' in prompt_json[SizeID]['inputs'] and type(prompt_json[SizeID]['inputs']['width']) == int:
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origwidth = str(prompt_json[SizeID]['inputs']['width'])
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origheight = str(prompt_json[SizeID]['inputs']['height'])
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FINAL_DICT['width'] = int(origwidth)
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FINAL_DICT['height'] = int(origheight)
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FINAL_DICT['size_string'] = origwidth + 'x' + origheight
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self._parameter = FINAL_DICT
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def _comfy_traverse(self, prompt, end_node):
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flow = {}
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node = [end_node]
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inputs = {}
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try:
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inputs = prompt[end_node]["inputs"]
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except:
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print("node error")
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return flow, node
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match prompt[end_node]["class_type"]:
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case node_type if node_type in SAVE_IMAGE_TYPE:
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try:
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["images"][0]
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)
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flow = utility.merge_dict(flow, last_flow)
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node += last_node
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except:
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print("comfyUI SaveImage error")
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case node_type if node_type in KSAMPLER_TYPES:
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try:
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flow = inputs
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last_flow1, last_node1 = self._comfy_traverse(
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prompt, inputs["model"][0]
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)
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last_flow2, last_node2 = self._comfy_traverse(
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prompt, inputs["latent_image"][0]
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)
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positive = self._comfy_traverse(prompt, inputs["positive"][0])
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if isinstance(positive, str):
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self._positive = positive
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elif isinstance(positive, dict):
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self._positive_sdxl.update(positive)
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negative = self._comfy_traverse(prompt, inputs["negative"][0])
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if isinstance(negative, str):
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self._negative = negative
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elif isinstance(negative, dict):
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self._negative_sdxl.update(negative)
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seed = None
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# handle "CR Seed"
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if inputs.get("seed") and isinstance(inputs.get("seed"), list):
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seed = {"seed": self._comfy_traverse(prompt, inputs["seed"][0])}
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elif inputs.get("noise_seed") and isinstance(
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inputs.get("noise_seed"), list
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):
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seed = {
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"noise_seed": self._comfy_traverse(
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prompt, inputs["noise_seed"][0]
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)
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}
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if seed:
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flow.update(seed)
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flow = utility.merge_dict(flow, last_flow1)
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flow = utility.merge_dict(flow, last_flow2)
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node += last_node1 + last_node2
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except:
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print("comfyUI KSampler error")
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case node_type if node_type in CLIP_TEXT_ENCODE_TYPE:
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try:
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match node_type:
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case "CLIPTextEncode":
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# SDXLPromptStyler
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if isinstance(inputs["text"], list):
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text = int(inputs["text"][0])
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prompt_styler = self._comfy_traverse(prompt, str(text))
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self._positive = prompt_styler[0]
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self._negative = prompt_styler[1]
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return
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elif isinstance(inputs["text"], str):
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return inputs.get("text")
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case "CLIPTextEncodeSDXL":
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# SDXLPromptStyler
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self._is_sdxl = True
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if isinstance(inputs["text_g"], list):
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text_g = int(inputs["text_g"][0])
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text_l = int(inputs["text_l"][0])
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prompt_styler_g = self._comfy_traverse(
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prompt, str(text_g)
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)
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prompt_styler_l = self._comfy_traverse(
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prompt, str(text_l)
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)
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self._positive_sdxl["Clip G"] = prompt_styler_g[0]
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self._positive_sdxl["Clip L"] = prompt_styler_l[0]
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self._negative_sdxl["Clip G"] = prompt_styler_g[1]
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self._negative_sdxl["Clip L"] = prompt_styler_l[1]
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return
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elif isinstance(inputs["text_g"], str):
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return {
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"Clip G": inputs.get("text_g"),
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"Clip L": inputs.get("text_l"),
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}
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case "CLIPTextEncodeSDXLRefiner":
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self._is_sdxl = True
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if isinstance(inputs["text"], list):
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# SDXLPromptStyler
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text = int(inputs["text"][0])
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prompt_styler = self._comfy_traverse(prompt, str(text))
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self._positive_sdxl["Refiner"] = prompt_styler[0]
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self._negative_sdxl["Refiner"] = prompt_styler[1]
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return
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elif isinstance(inputs["text"], str):
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return {"Refiner": inputs.get("text")}
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except:
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print("comfyUI CLIPText error")
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case "LoraLoader":
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try:
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flow = inputs
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["model"][0]
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)
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flow = utility.merge_dict(flow, last_flow)
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node += last_node
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except:
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print("comfyUI LoraLoader error")
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case node_type if node_type in CHECKPOINT_LOADER_TYPE:
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try:
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return inputs, node
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except:
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print("comfyUI CheckpointLoader error")
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case node_type if node_type in VAE_ENCODE_TYPE:
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try:
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["pixels"][0]
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)
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flow = utility.merge_dict(flow, last_flow)
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node += last_node
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except:
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print("comfyUI VAE error")
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case "ControlNetApplyAdvanced":
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try:
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positive = self._comfy_traverse(prompt, inputs["positive"][0])
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if isinstance(positive, str):
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self._positive = positive
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elif isinstance(positive, dict):
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self._positive_sdxl.update(positive)
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negative = self._comfy_traverse(prompt, inputs["negative"][0])
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if isinstance(negative, str):
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self._negative = negative
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elif isinstance(negative, dict):
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self._negative_sdxl.update(negative)
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["image"][0]
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)
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flow = utility.merge_dict(flow, last_flow)
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node += last_node
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except:
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print("comfyUI ControlNetApply error")
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case "ImageScale":
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try:
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flow = inputs
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["image"][0]
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)
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flow = utility.merge_dict(flow, last_flow)
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node += last_node
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except:
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print("comfyUI ImageScale error")
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case "UpscaleModelLoader":
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try:
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return {"upscaler": inputs["model_name"]}
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except:
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print("comfyUI UpscaleLoader error")
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case "ImageUpscaleWithModel":
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try:
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flow = inputs
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["image"][0]
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)
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model = self._comfy_traverse(prompt, inputs["upscale_model"][0])
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flow = utility.merge_dict(flow, last_flow)
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flow = utility.merge_dict(flow, model)
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node += last_node
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except:
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print("comfyUI UpscaleModel error")
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case "ConditioningCombine":
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try:
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last_flow1, last_node1 = self._comfy_traverse(
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prompt, inputs["conditioning_1"][0]
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)
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last_flow2, last_node2 = self._comfy_traverse(
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prompt, inputs["conditioning_2"][0]
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)
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flow = utility.merge_dict(flow, last_flow1)
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flow = utility.merge_dict(flow, last_flow2)
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node += last_node1 + last_node2
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except:
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print("comfyUI ConditioningCombine error")
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# custom nodes
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case "SDXLPromptStyler":
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try:
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return inputs.get("text_positive"), inputs.get("text_negative")
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except:
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print("comfyUI SDXLPromptStyler error")
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case "CR Seed":
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try:
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return inputs.get("seed")
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except:
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print("comfyUI CR Seed error")
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case _:
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try:
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last_flow = {}
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last_node = []
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if inputs.get("samples"):
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["samples"][0]
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)
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elif inputs.get("image") and isinstance(inputs.get("image"), list):
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["image"][0]
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)
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elif inputs.get("model"):
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["model"][0]
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)
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elif inputs.get("clip"):
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["clip"][0]
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)
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elif inputs.get("samples_from"):
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last_flow, last_node = self._comfy_traverse(
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prompt, inputs["samples_from"][0]
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)
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elif inputs.get("conditioning"):
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result = self._comfy_traverse(prompt, inputs["conditioning"][0])
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if isinstance(result, str):
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return result
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elif isinstance(result, list):
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last_flow, last_node = result
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flow = utility.merge_dict(flow, last_flow)
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node += last_node
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except:
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print("comfyUI bridging node error")
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return flow, node |