Is there has some tool which help extract png-info and convert to python dict

[zacard-orc]

Is there has some tool which help extract png-info and convert to python dict?

png-info =>
model photoshoot,1girl,expressionless,beautiful young woman,28 yo,villa,palm trees,outdoor,pool,dress,random hair color,slim waist,sporty,ginger hair,dreamy face,detailed,8k,natural colors,clothed,(ultra wide angle:1.5),victorias secret,hollywood,face the lens,
masterpiece,extremely detailed CG unity 8k wallpaper,best quality,Amazing,finely detail,solo,cinematic lighting,close-up,outdoors,detailed background,beautiful detailed eyes,bright pupils,full body,dynamic pose,dynamic angle,12 noon,
Negative prompt: bad art,ugly,messed up face,poorly drawn hands,bad hands,professional photo shoot,makeup,photoshop,doll,plastic_doll,anime,cartoon,filter,airbrush,3d max,infant,featureless,colourless,impassive,shaders,asian,cut off,amputee,fat,nude,naked,indoor,glasses,an open mouth,
badhandv4,
Steps: 40, Sampler: DPM++ SDE Karras, CFG scale: 12, Seed: 3944440566, Size: 1200x1600, Model hash: e4a30e4607, Model: majicmixRealistic_v6, Denoising strength: 0.3, Version: v1.3.2
Template: model photoshoot,1girl,expressionless,beautiful young woman,28 yo,villa,palm trees,outdoor,pool,dress,random hair color,slim waist,sporty,ginger hair,dreamy face,detailed,8k,natural colors,clothed,(ultra wide angle:1.5),victorias secret,hollywood,face the lens,
masterpiece,extremely detailed CG unity 8k wallpaper,best quality,Amazing,finely detail,solo,cinematic lighting,close-up,outdoors,detailed background,beautiful detailed eyes,bright pupils,full body,dynamic pose,dynamic angle,12 noon,
Negative Template: bad art,ugly,messed up face,poorly drawn hands,bad hands,professional photo shoot,makeup,photoshop,doll,plastic_doll,anime,cartoon,filter,airbrush,3d max,infant,featureless,colourless,impassive,shaders,asian,cut off,amputee,fat,nude,naked,indoor,glasses,an open mouth,
badhandv4,

=> want to convert into
{
"aaa":"xxxx",
"bbb":"xxxx",
"ccc":"xxxx",
...
"zzzz":"xxxx",

}

[missionfloyd]

Here's how it's currently done.

stable-diffusion-webui/modules/generation_parameters_copypaste.py

Lines 210 to 307 in 68f336b

	def parse_generation_parameters(x: str):
	"""parses generation parameters string, the one you see in text field under the picture in UI:
	```
	girl with an artist's beret, determined, blue eyes, desert scene, computer monitors, heavy makeup, by Alphonse Mucha and Charlie Bowater, ((eyeshadow)), (coquettish), detailed, intricate
	Negative prompt: ugly, fat, obese, chubby, (((deformed))), [blurry], bad anatomy, disfigured, poorly drawn face, mutation, mutated, (extra_limb), (ugly), (poorly drawn hands), messy drawing
	Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model hash: 45dee52b
	```
	returns a dict with field values
	"""
	res = {}
	prompt = ""
	negative_prompt = ""
	done_with_prompt = False
	*lines, lastline = x.strip().split("\n")
	if len(re_param.findall(lastline)) < 3:
	lines.append(lastline)
	lastline = ''
	for line in lines:
	line = line.strip()
	if line.startswith("Negative prompt:"):
	done_with_prompt = True
	line = line[16:].strip()
	if done_with_prompt:
	negative_prompt += ("" if negative_prompt == "" else "\n") + line
	else:
	prompt += ("" if prompt == "" else "\n") + line
	if shared.opts.infotext_styles != "Ignore":
	found_styles, prompt, negative_prompt = shared.prompt_styles.extract_styles_from_prompt(prompt, negative_prompt)
	if shared.opts.infotext_styles == "Apply":
	res["Styles array"] = found_styles
	elif shared.opts.infotext_styles == "Apply if any" and found_styles:
	res["Styles array"] = found_styles
	res["Prompt"] = prompt
	res["Negative prompt"] = negative_prompt
	for k, v in re_param.findall(lastline):
	try:
	if v[0] == '"' and v[-1] == '"':
	v = unquote(v)
	m = re_imagesize.match(v)
	if m is not None:
	res[f"{k}-1"] = m.group(1)
	res[f"{k}-2"] = m.group(2)
	else:
	res[k] = v
	except Exception:
	print(f"Error parsing \"{k}: {v}\"")
	# Missing CLIP skip means it was set to 1 (the default)
	if "Clip skip" not in res:
	res["Clip skip"] = "1"
	hypernet = res.get("Hypernet", None)
	if hypernet is not None:
	res["Prompt"] += f"""<hypernet:{hypernet}:{res.get("Hypernet strength", "1.0")}>"""
	if "Hires resize-1" not in res:
	res["Hires resize-1"] = 0
	res["Hires resize-2"] = 0
	if "Hires sampler" not in res:
	res["Hires sampler"] = "Use same sampler"
	if "Hires prompt" not in res:
	res["Hires prompt"] = ""
	if "Hires negative prompt" not in res:
	res["Hires negative prompt"] = ""
	restore_old_hires_fix_params(res)
	# Missing RNG means the default was set, which is GPU RNG
	if "RNG" not in res:
	res["RNG"] = "GPU"
	if "Schedule type" not in res:
	res["Schedule type"] = "Automatic"
	if "Schedule max sigma" not in res:
	res["Schedule max sigma"] = 0
	if "Schedule min sigma" not in res:
	res["Schedule min sigma"] = 0
	if "Schedule rho" not in res:
	res["Schedule rho"] = 0
	return res