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Merge pull request #292 from mrhan1993/support_imagemeta
Support image meta
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Original file line number | Diff line number | Diff line change |
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@@ -1 +1 @@ | ||
version = '0.4.0.3' | ||
version = '0.4.0.4' |
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,116 @@ | ||
""" | ||
Image meta schema | ||
""" | ||
from typing import List | ||
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from fooocus_version import version | ||
from pydantic import BaseModel | ||
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class ImageMeta(BaseModel): | ||
""" | ||
Image meta data model | ||
""" | ||
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metadata_scheme: str = "fooocus" | ||
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base_model: str | ||
base_model_hash: str | ||
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prompt: str | ||
full_prompt: List[str] | ||
prompt_expansion: str | ||
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negative_prompt: str | ||
full_negative_prompt: List[str] | ||
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performance: str | ||
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style: str | ||
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refiner_model: str = "None" | ||
refiner_switch: float = 0.5 | ||
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loras: List[list] | ||
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resolution: str | ||
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sampler: str = "dpmpp_2m_sde_gpu" | ||
scheduler: str = "karras" | ||
seed: str | ||
adm_guidance: str | ||
guidance_scale: int | ||
sharpness: int | ||
steps: int | ||
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version: str = version | ||
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def __repr__(self): | ||
return "" | ||
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def loras_parser(loras: list) -> list: | ||
""" | ||
Parse lora list | ||
""" | ||
return [ | ||
[ | ||
lora[0].rsplit('.', maxsplit=1)[:1][0], | ||
lora[1], | ||
"hash_not_calculated", | ||
] for lora in loras if lora[0] != 'None' and lora[0] is not None] | ||
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def image_parse( | ||
async_tak: object, | ||
task: dict | ||
) -> dict | str: | ||
""" | ||
Parse image meta data | ||
Generate meta data for image from task and async task object | ||
Args: | ||
async_tak: async task obj | ||
task: task obj | ||
Returns: | ||
dict: image meta data | ||
""" | ||
req_param = async_tak.req_param | ||
meta = ImageMeta( | ||
metadata_scheme=req_param.meta_scheme, | ||
base_model=req_param.base_model_name.rsplit('.', maxsplit=1)[:1][0], | ||
base_model_hash='', | ||
prompt=req_param.prompt, | ||
full_prompt=task['positive'], | ||
prompt_expansion=task['expansion'], | ||
negative_prompt=req_param.negative_prompt, | ||
full_negative_prompt=task['negative'], | ||
performance=req_param.performance_selection, | ||
style=str(req_param.style_selections), | ||
refiner_model=req_param.refiner_model_name, | ||
refiner_switch=req_param.refiner_switch, | ||
loras=loras_parser(req_param.loras), | ||
resolution=str(tuple([int(n) for n in req_param.aspect_ratios_selection.split('*')])), | ||
sampler=req_param.advanced_params.sampler_name, | ||
scheduler=req_param.advanced_params.scheduler_name, | ||
seed=str(task['task_seed']), | ||
adm_guidance=str(( | ||
req_param.advanced_params.adm_scaler_positive, | ||
req_param.advanced_params.adm_scaler_negative, | ||
req_param.advanced_params.adm_scaler_end)), | ||
guidance_scale=req_param.guidance_scale, | ||
sharpness=req_param.sharpness, | ||
steps=-1, | ||
version=version | ||
) | ||
if meta.metadata_scheme not in ["fooocus", "a111"]: | ||
meta.metadata_scheme = "fooocus" | ||
if meta.metadata_scheme == "fooocus": | ||
meta_dict = meta.model_dump() | ||
for i, lora in enumerate(meta.loras): | ||
attr_name = f"lora_combined_{i+1}" | ||
lr = [str(x) for x in lora] | ||
meta_dict[attr_name] = f"{lr[0]} : {lr[1]}" | ||
else: | ||
meta_dict = meta.model_dump() | ||
return meta_dict |
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