test / modules /api /generate.py
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from threading import Lock
from fastapi.responses import JSONResponse
from modules import errors, shared, scripts, ui
from modules.api import models, script, helpers
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
errors.install()
class APIGenerate():
def __init__(self, queue_lock: Lock):
self.queue_lock = queue_lock
self.default_script_arg_txt2img = []
self.default_script_arg_img2img = []
def sanitize_args(self, args: dict):
args = vars(args)
args.pop('include_init_images', None) # this is meant to be done by "exclude": True in model
args.pop('script_name', None)
args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them
args.pop('alwayson_scripts', None)
args.pop('face', None)
args.pop('face_id', None)
args.pop('ip_adapter', None)
args.pop('save_images', None)
return args
def sanitize_b64(self, request):
def sanitize_str(args: list):
for idx in range(0, len(args)):
if isinstance(args[idx], str) and len(args[idx]) >= 1000:
args[idx] = f"<str {len(args[idx])}>"
if hasattr(request, "alwayson_scripts") and request.alwayson_scripts:
for script_name in request.alwayson_scripts.keys():
script_obj = request.alwayson_scripts[script_name]
if script_obj and "args" in script_obj and script_obj["args"]:
sanitize_str(script_obj["args"])
if hasattr(request, "script_args") and request.script_args:
sanitize_str(request.script_args)
def prepare_face_module(self, request):
if hasattr(request, "face") and request.face and not request.script_name and (not request.alwayson_scripts or "face" not in request.alwayson_scripts.keys()):
request.script_name = "face"
request.script_args = [
request.face.mode,
request.face.source_images,
request.face.ip_model,
request.face.ip_override_sampler,
request.face.ip_cache_model,
request.face.ip_strength,
request.face.ip_structure,
request.face.id_strength,
request.face.id_conditioning,
request.face.id_cache,
request.face.pm_trigger,
request.face.pm_strength,
request.face.pm_start,
request.face.fs_cache
]
del request.face
def post_text2img(self, txt2imgreq: models.ReqTxt2Img):
self.prepare_face_module(txt2imgreq)
script_runner = scripts.scripts_txt2img
if not script_runner.scripts:
script_runner.initialize_scripts(False)
ui.create_ui(None)
if not self.default_script_arg_txt2img:
self.default_script_arg_txt2img = script.init_default_script_args(script_runner)
selectable_scripts, selectable_script_idx = script.get_selectable_script(txt2imgreq.script_name, script_runner)
populate = txt2imgreq.copy(update={ # Override __init__ params
"sampler_name": helpers.validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index),
"do_not_save_samples": not txt2imgreq.save_images,
"do_not_save_grid": not txt2imgreq.save_images,
})
if populate.sampler_name:
populate.sampler_index = None # prevent a warning later on
args = self.sanitize_args(populate)
send_images = args.pop('send_images', True)
with self.queue_lock:
p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)
p.scripts = script_runner
p.outpath_grids = shared.opts.outdir_grids or shared.opts.outdir_txt2img_grids
p.outpath_samples = shared.opts.outdir_samples or shared.opts.outdir_txt2img_samples
shared.state.begin('api-txt2img', api=True)
script_args = script.init_script_args(p, txt2imgreq, self.default_script_arg_txt2img, selectable_scripts, selectable_script_idx, script_runner)
if selectable_scripts is not None:
processed = scripts.scripts_txt2img.run(p, *script_args) # Need to pass args as list here
else:
p.script_args = tuple(script_args) # Need to pass args as tuple here
processed = process_images(p)
shared.state.end(api=False)
b64images = list(map(helpers.encode_pil_to_base64, processed.images)) if send_images else []
self.sanitize_b64(txt2imgreq)
return models.ResTxt2Img(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
def post_img2img(self, img2imgreq: models.ReqImg2Img):
self.prepare_face_module(img2imgreq)
init_images = img2imgreq.init_images
if init_images is None:
return JSONResponse(status_code=400, content={"error": "Init image is none"})
mask = img2imgreq.mask
if mask:
mask = helpers.decode_base64_to_image(mask)
script_runner = scripts.scripts_img2img
if not script_runner.scripts:
script_runner.initialize_scripts(True)
ui.create_ui(None)
if not self.default_script_arg_img2img:
self.default_script_arg_img2img = script.init_default_script_args(script_runner)
selectable_scripts, selectable_script_idx = script.get_selectable_script(img2imgreq.script_name, script_runner)
populate = img2imgreq.copy(update={ # Override __init__ params
"sampler_name": helpers.validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index),
"do_not_save_samples": not img2imgreq.save_images,
"do_not_save_grid": not img2imgreq.save_images,
"mask": mask,
})
if populate.sampler_name:
populate.sampler_index = None # prevent a warning later on
args = self.sanitize_args(populate)
send_images = args.pop('send_images', True)
with self.queue_lock:
p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)
p.init_images = [helpers.decode_base64_to_image(x) for x in init_images]
p.scripts = script_runner
p.outpath_grids = shared.opts.outdir_img2img_grids
p.outpath_samples = shared.opts.outdir_img2img_samples
shared.state.begin('api-img2img', api=True)
script_args = script.init_script_args(p, img2imgreq, self.default_script_arg_img2img, selectable_scripts, selectable_script_idx, script_runner)
if selectable_scripts is not None:
processed = scripts.scripts_img2img.run(p, *script_args) # Need to pass args as list here
else:
p.script_args = tuple(script_args) # Need to pass args as tuple here
processed = process_images(p)
shared.state.end(api=False)
b64images = list(map(helpers.encode_pil_to_base64, processed.images)) if send_images else []
if not img2imgreq.include_init_images:
img2imgreq.init_images = None
img2imgreq.mask = None
self.sanitize_b64(img2imgreq)
return models.ResImg2Img(images=b64images, parameters=vars(img2imgreq), info=processed.js())