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control refine/secondpass/hires

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Vladimir Mandic
2024-03-08 10:44:21 -05:00
parent 116e6b3f64
commit e46c5d2995
5 changed files with 61 additions and 25 deletions
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modules/processing_class.py
+14 -11
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@@ -1,5 +1,4 @@
import os
import math
import hashlib
from typing import Any, Dict, List
from dataclasses import dataclass, field
@@ -237,10 +236,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
self.width = self.width or 512
self.height = self.height or 512
def init_hr(self):
def init_hr(self, scale = None, upscaler = None):
scale = scale or self.hr_scale
upscaler = upscaler or self.hr_upscaler
if self.hr_resize_x == 0 and self.hr_resize_y == 0:
self.hr_upscale_to_x = int(self.width * self.hr_scale)
self.hr_upscale_to_y = int(self.height * self.hr_scale)
self.hr_upscale_to_x = int(self.width * scale)
self.hr_upscale_to_y = int(self.height * scale)
else:
if self.hr_resize_y == 0:
self.hr_upscale_to_x = self.hr_resize_x
@@ -262,7 +263,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
self.truncate_x = (self.hr_upscale_to_x - target_w) // 8
self.truncate_y = (self.hr_upscale_to_y - target_h) // 8
if shared.backend == shared.Backend.ORIGINAL: # diffusers are handled in processing_diffusers
if (self.hr_upscale_to_x == self.width and self.hr_upscale_to_y == self.height) or self.hr_upscaler is None or self.hr_upscaler == 'None': # special case: the user has chosen to do nothing
if (self.hr_upscale_to_x == self.width and self.hr_upscale_to_y == self.height) or upscaler is None or upscaler == 'None': # special case: the user has chosen to do nothing
self.is_hr_pass = False
return
self.is_hr_pass = True
@@ -283,6 +284,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
self.resize_mode: int = resize_mode
self.resize_name: str = resize_name
self.denoising_strength: float = denoising_strength
self.hr_denoising_strength: float = denoising_strength
self.image_cfg_scale: float = image_cfg_scale
self.init_latent = None
self.image_mask = mask
@@ -477,14 +479,15 @@ class StableDiffusionProcessingControl(StableDiffusionProcessingImg2Img):
def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): # abstract
pass
def init_hr(self):
if self.resize_name == 'None' or self.scale_by == 1.0:
def init_hr(self, scale = None, upscaler = None):
scale = scale or self.scale_by
upscaler = upscaler or self.resize_name
if upscaler == 'None' or scale == 1.0:
return
self.is_hr_pass = True
self.hr_force = True
self.hr_upscaler = self.resize_name
self.hr_upscale_to_x, self.hr_upscale_to_y = int(self.width * self.scale_by), int(self.height * self.scale_by)
self.hr_upscale_to_x, self.hr_upscale_to_y = 8 * math.ceil(self.hr_upscale_to_x / 8), 8 * math.ceil(self.hr_upscale_to_y / 8)
self.hr_upscaler = upscaler
self.hr_upscale_to_x, self.hr_upscale_to_y = 8 * int(self.width * scale / 8), 8 * int(self.height * scale / 8)
# hypertile_set(self, hr=True)
shared.state.job_count = 2 * self.n_iter
shared.log.debug(f'Control hires: upscaler="{self.hr_upscaler}" upscale={self.scale_by} size={self.hr_upscale_to_x}x{self.hr_upscale_to_y}')
shared.log.debug(f'Control hires: upscaler="{self.hr_upscaler}" upscale={scale} size={self.hr_upscale_to_x}x{self.hr_upscale_to_y}')