279 lines
10 KiB
Python
279 lines
10 KiB
Python
"""
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Custom nodes for SDXL in ComfyUI
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MIT License
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Copyright (c) 2023 Searge
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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"""
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from .mb_pipeline import PipelineAccess
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from .stage import SeargeStage
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from .stage_pre_processing import SeargePreProcessData
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from .stage_load_checkpoints import SeargeStageLoadCheckpoints
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from .stage_apply_loras import SeargeStageApplyLoras
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from .stage_clip_conditioning import SeargeStageClipConditioning
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from .stage_apply_controlnet import SeargeStageApplyControlnet
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from .stage_latent_inputs import SeargeStageLatentInputs
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from .stage_sampling import SeargeStageSampling
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from .stage_latent_detailer import SeargeStageLatentDetailer
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from .stage_vae_decode_sampled import SeargeStageVAEDecodeSampled
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from .stage_high_resolution import SeargeStageHighResolution
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from .stage_hires_detailer import SeargeStageHiresDetailer
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from .stage_vae_decode_hires import SeargeStageVAEDecodeHires
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from .stage_upscaling import SeargeStageUpscaling
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from .stage_image_saving import SeargeStageImageSaving
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from .ui import UI
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# ====================================================================================================
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# Searge's Magic Box
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# ====================================================================================================
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class SeargeMagicBox:
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# processing stages supported by the magic box
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NONE = "none - skip"
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PRE_PROCESS_DATA = "pre-process data"
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LOAD_CHECKPOINTS = "load checkpoints"
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APPLY_LORAS = "apply loras"
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PROMPT_STYLING = "prompt styling"
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CLIP_CONDITIONING = "clip conditioning"
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CLIP_MIXING = "clip mixing"
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APPLY_CONTROLNET = "apply controlnet"
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LATENT_INPUTS = "latent inputs"
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SAMPLING = "sampling"
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LATENT_DETAILER = "latent detailer"
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VAE_DECODE_SAMPLED = "vae decode sampled"
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HIGH_RESOLUTION = "high resolution"
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HIRES_DETAILER = "hires detailer"
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VAE_DECODE_HI_RES = "vae decode hi-res"
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UPSCALING = "upscaling"
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IMAGE_SAVING = "image saving"
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STAGES = [
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NONE,
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PRE_PROCESS_DATA,
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LOAD_CHECKPOINTS,
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APPLY_LORAS,
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PROMPT_STYLING,
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CLIP_CONDITIONING,
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CLIP_MIXING,
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APPLY_CONTROLNET,
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LATENT_INPUTS,
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SAMPLING,
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LATENT_DETAILER,
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VAE_DECODE_SAMPLED,
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HIGH_RESOLUTION,
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HIRES_DETAILER,
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VAE_DECODE_HI_RES,
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UPSCALING,
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IMAGE_SAVING,
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]
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# option to take inputs from a custom stage instead of the data stream
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DATA = "data stream"
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CUSTOM_AND_DATA = "custom stage & data stream"
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INPUT_OUTPUT = [
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DATA,
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CUSTOM_AND_DATA,
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]
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def __init__(self):
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self.stage_pre_process_data = None
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self.stage_load_checkpoints = None
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self.stage_apply_loras = None
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self.stage_prompt_styling = None
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self.stage_clip_conditioning = None
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self.stage_clip_mixing = None
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self.stage_latent_inputs = None
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self.stage_apply_controlnet = None
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self.stage_sampling = None
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self.stage_vae_decode_sampled = None
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self.stage_latent_detailer = None
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self.stage_high_resolution = None
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self.stage_hires_detailer = None
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self.stage_vae_decode_hi_res = None
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self.stage_upscaling = None
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self.stage_image_saving = None
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self.stage_ = None
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"stage": (s.STAGES, {"default": s.NONE},),
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"input_from": (s.INPUT_OUTPUT,),
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"output_to": (s.INPUT_OUTPUT,),
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},
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"optional": {
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"data": ("SRG_DATA_STREAM",),
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"custom_input": ("SRG_STAGE_INPUT",),
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},
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}
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RETURN_TYPES = ("SRG_DATA_STREAM", "SRG_STAGE_OUTPUT",)
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RETURN_NAMES = ("data", "custom_output",)
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FUNCTION = "process"
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CATEGORY = UI.CATEGORY_MAGIC
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def run_stage(self, stage, data, stage_input=None):
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stage_processor = None
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has_data = data is not None
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# clear old stage output from data stream
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stage_output = stage_input
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if has_data:
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data["stage_output"] = None
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# stage: "none - skip" - does nothing, skip processing in this magic box
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if stage == self.NONE:
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pass
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elif stage == self.PRE_PROCESS_DATA:
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if self.stage_pre_process_data is None:
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self.stage_pre_process_data = SeargePreProcessData()
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stage_processor = self.stage_pre_process_data
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elif stage == self.LOAD_CHECKPOINTS:
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if self.stage_load_checkpoints is None:
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self.stage_load_checkpoints = SeargeStageLoadCheckpoints()
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stage_processor = self.stage_load_checkpoints
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elif stage == self.APPLY_LORAS:
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if self.stage_apply_loras is None:
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self.stage_apply_loras = SeargeStageApplyLoras()
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stage_processor = self.stage_apply_loras
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elif stage == self.PROMPT_STYLING:
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if self.stage_prompt_styling is None:
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# print("TODO: implement stage " + stage)
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self.stage_prompt_styling = SeargeStage()
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stage_processor = self.stage_prompt_styling
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elif stage == self.CLIP_CONDITIONING:
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if self.stage_clip_conditioning is None:
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self.stage_clip_conditioning = SeargeStageClipConditioning()
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stage_processor = self.stage_clip_conditioning
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elif stage == self.CLIP_MIXING:
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if self.stage_clip_mixing is None:
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# print("TODO: implement stage " + stage)
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self.stage_clip_mixing = SeargeStage()
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stage_processor = self.stage_clip_mixing
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elif stage == self.APPLY_CONTROLNET:
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if self.stage_apply_controlnet is None:
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self.stage_apply_controlnet = SeargeStageApplyControlnet()
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stage_processor = self.stage_apply_controlnet
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elif stage == self.LATENT_INPUTS:
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if self.stage_latent_inputs is None:
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self.stage_latent_inputs = SeargeStageLatentInputs()
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stage_processor = self.stage_latent_inputs
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elif stage == self.SAMPLING:
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if self.stage_sampling is None:
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self.stage_sampling = SeargeStageSampling()
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stage_processor = self.stage_sampling
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elif stage == self.LATENT_DETAILER:
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if self.stage_latent_detailer is None:
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self.stage_latent_detailer = SeargeStageLatentDetailer()
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stage_processor = self.stage_latent_detailer
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elif stage == self.VAE_DECODE_SAMPLED:
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if self.stage_vae_decode_sampled is None:
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self.stage_vae_decode_sampled = SeargeStageVAEDecodeSampled()
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stage_processor = self.stage_vae_decode_sampled
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elif stage == self.HIGH_RESOLUTION:
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if self.stage_high_resolution is None:
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self.stage_high_resolution = SeargeStageHighResolution()
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stage_processor = self.stage_high_resolution
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elif stage == self.HIRES_DETAILER:
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if self.stage_hires_detailer is None:
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self.stage_hires_detailer = SeargeStageHiresDetailer()
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stage_processor = self.stage_hires_detailer
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elif stage == self.VAE_DECODE_HI_RES:
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if self.stage_vae_decode_hi_res is None:
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self.stage_vae_decode_hi_res = SeargeStageVAEDecodeHires()
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stage_processor = self.stage_vae_decode_hi_res
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elif stage == self.UPSCALING:
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if self.stage_upscaling is None:
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self.stage_upscaling = SeargeStageUpscaling()
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stage_processor = self.stage_upscaling
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elif stage == self.IMAGE_SAVING:
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if self.stage_image_saving is None:
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self.stage_image_saving = SeargeStageImageSaving()
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stage_processor = self.stage_image_saving
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else:
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print("WARNING: implementation for stage " + stage + " is missing!")
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# no stage processor exists, so no processing can happen and no result exists
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if stage_processor is None:
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return (data, None,)
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# get the stage input data that is relevant to the selected stage
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stage_input = stage_processor.get_input(data, stage_output)
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# process the selected stage
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stage_result = None
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if stage_input is not None:
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(data, stage_result) = stage_processor.process(data, stage_input)
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# if we got a result from this stage, put it on the data stream
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if has_data:
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data["stage_output"] = stage_result
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return (data, stage_result,)
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def process(self, stage, input_from, output_to, data=None, custom_input=None):
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if data is None:
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data = {}
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stage_input = None
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custom_output = None
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# input from custom stage ?
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if input_from == self.CUSTOM_AND_DATA:
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stage_input = custom_input
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# if no stage data is provided, the stage will take it from the data stream
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if PipelineAccess(data).is_pipeline_enabled(): # or stage == self.LOAD_CHECKPOINTS:
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(data, stage_result) = self.run_stage(stage, data, stage_input)
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else:
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stage_result = None
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# output to custom stage ?
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if output_to == self.CUSTOM_AND_DATA:
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custom_output = stage_result
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# the result will always be on the data stream, so even without custom output it will be passed on
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return (data, custom_output,)
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