a library to read metadata from images created by Stable Diffusion
Project description
Features
Supports reading metadata from images generated with:
- Automatic1111's Stable Diffusion web UI
- ComfyUI *
- Fooocus
- InvokeAI
- NovelAI
Provides a list of prompts used in the generation of the image, as well as generator-specific metadata.
* Custom ComfyUI nodes might parse incorrectly / with incomplete data.
Installation
pip install sd-parsers
Usage
From command line: python3 -m sd_parsers <filenames>
.
Basic usage:
For a simple query, import ParserManager
from sd_parsers
and use its parse()
method to parse an image. (see examples)
Read prompt information from a given filename:
from sd_parsers import ParserManager
parser_manager = ParserManager()
def main():
prompt_info = parser_manager.parse("image.png")
if prompt_info:
for prompt in prompt_info.prompts:
print(f"Prompt: {prompt.value}")
Read prompt information from an already opened image:
from PIL import Image
from sd_parsers import ParserManager
parser_manager = ParserManager()
def main():
with Image.open('image.png') as image:
prompt_info = parser_manager.parse(image)
Each parser module can also be used directly, omitting the use of ParserManager
:
from PIL import Image
from sd_parsers.data import PromptInfo
from sd_parsers.exceptions import ParserError
from sd_parsers.parsers import AUTOMATIC1111Parser
parser = AUTOMATIC1111Parser()
def main():
try:
with Image.open("image.png") as image:
# read_parameters() returns relevant image metadata parameters
# and optional context information needed for parsing
parameters, parsing_context = parser.read_parameters(image)
# parse() builds a standardized data structure from the raw parameters
samplers, metadata = parser.parse(parameters, parsing_context)
except ParserError:
...
# creating a PromptInfo object from the obtained data allows for the use
# of convenience poperties like ".prompts" or ".models"
prompt_info = PromptInfo(parser, samplers, metadata)
Output
The output returned from ParserManager
is a PromptInfo
object (as can be seen when executing python3 -m sd_parsers <image.png>
) or None
if no metadata was found.
PromptInfo
contains the following properties :
-
generator
: Specifies the image generator that may have been used for creating the image. -
full_prompt
: A full prompt if present in the image metadata.Otherwise, a simple concatenation of all prompts found.
-
full_negative_prompt
: A full negative prompt if present in the image metadata.Otherwise, a simple concatenation of all negative prompts found.
-
prompts
: All prompts found in the parsed metadata. -
negative_prompts
: All negative prompts found in the parsed metadata. -
models
: Models used in the image generation process. -
samplers
: Samplers used in the image generation process.Samplers act as the central data autorithy (see PromptInfo).
A Sampler contains the following properties specific to itself:
sampler_id
: A unique id of the sampler (if present in the metadata)name
: The name of the samplerparameters
: Generation parameters, including cfg_scale, seed, steps and others.model
: The model used by this sampler.prompts
: A list of positive prompts used by this sampler.negative_prompts
: A list of negative prompts used by this sampler.
-
metadata
: Additional metadata which could not be attributed to one of the former described.Highly dependent on the provided data structure of the respective image generator.
Contributing
As i don't have the time and resources to keep up with all the available AI-based image generators out there, the scale and features of this library is depending greatly on your help.
If you find the sd-parsers library unable to read metadata from an image, feel free to open an issue.
See CONTRIBUTING.md, if you are willing to help with improving the library itself and/or to create/maintain an additional parser module.
Credits
Idea and motivation using AUTOMATIC1111's stable diffusion webui
Example workflows for testing the ComfyUI parser
Project details
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