nodes/SeargeDP-SeargeSDXL
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SeargeDP
2023-08-03 08:48:06 +02:00
parent 2bf6ce5856
commit 359fb31471
1 changed files with 16 additions and 7 deletions
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searge_sdxl_sampler_node.py
+16 -7
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@@ -29,6 +29,7 @@ import datetime
import comfy.samplers
import comfy_extras.nodes_upscale_model
import comfy_extras.nodes_post_processing
import folder_paths
import json
import nodes
@@ -64,7 +65,7 @@ class SeargeSDXLSampler:
"optional": {
"refiner_prep_steps": ("INT", {"default": 0, "min": 0, "max": 10}),
"noise_offset": ("INT", {"default": 1, "min": 0, "max": 1}),
"refiner_strength": ("FLOAT", {"default": 1.0, "min": 0.01, "max": 1.0, "step": 0.1}),
"refiner_strength": ("FLOAT", {"default": 1.0, "min": 0.01, "max": 1.0, "step": 0.05}),
},
}
@@ -74,7 +75,7 @@ class SeargeSDXLSampler:
CATEGORY = "Searge/Sampling"
def sample(self, base_model, base_positive, base_negative, refiner_model, refiner_positive, refiner_negative, latent_image, noise_seed, steps, cfg, sampler_name, scheduler, base_ratio, denoise, refiner_prep_steps=None, noise_offset=None, refiner_strength=None):
base_steps = int(steps * base_ratio)
base_steps = int(steps * (base_ratio + 0.0001))
if noise_offset is None:
noise_offset = 1
@@ -135,7 +136,7 @@ class SeargeSDXLImage2ImageSampler:
"scaled_width": ("INT", {"default": 1536, "min": 0, "max": nodes.MAX_RESOLUTION, "step": 8}),
"scaled_height": ("INT", {"default": 1536, "min": 0, "max": nodes.MAX_RESOLUTION, "step": 8}),
"noise_offset": ("INT", {"default": 1, "min": 0, "max": 1}),
"refiner_strength": ("FLOAT", {"default": 1.0, "min": 0.1, "max": 1.0, "step": 0.1}),
"refiner_strength": ("FLOAT", {"default": 1.0, "min": 0.1, "max": 1.0, "step": 0.05}),
"softness": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.05}),
},
}
@@ -146,7 +147,7 @@ class SeargeSDXLImage2ImageSampler:
CATEGORY = "Searge/Sampling"
def sample(self, base_model, base_positive, base_negative, refiner_model, refiner_positive, refiner_negative, image, vae, noise_seed, steps, cfg, sampler_name, scheduler, base_ratio, denoise, softness, upscale_model=None, scaled_width=None, scaled_height=None, noise_offset=None, refiner_strength=None):
base_steps = int(steps * base_ratio)
base_steps = int(steps * (base_ratio + 0.0001))
if noise_offset is None:
noise_offset = 1
@@ -162,7 +163,8 @@ class SeargeSDXLImage2ImageSampler:
scaled_image = image
if upscale_model is not None:
use_upscale_model = upscale_model is not None and softness < 0.9999
if use_upscale_model:
upscale_result = comfy_extras.nodes_upscale_model.ImageUpscaleWithModel().upscale(upscale_model, image)
scaled_image = upscale_result[0]
@@ -170,6 +172,13 @@ class SeargeSDXLImage2ImageSampler:
upscale_result = nodes.ImageScale().upscale(scaled_image, "bicubic", scaled_width, scaled_height, "center")
scaled_image = upscale_result[0]
if use_upscale_model:
upscale_result = nodes.ImageScale().upscale(image, "bicubic", scaled_width, scaled_height, "center")
scaled_original = upscale_result[0]
blend_result = comfy_extras.nodes_post_processing.Blend().blend_images(scaled_image, scaled_original, softness, "normal")
scaled_image = blend_result[0]
if denoise < 0.01:
return (scaled_image, )
@@ -993,7 +1002,7 @@ class SeargeInput3:
def INPUT_TYPES(s):
return {"required": {
"base_ratio": ("FLOAT", {"default": 0.8, "min": 0.0, "max": 1.0, "step": 0.01}),
"refiner_strength": ("FLOAT", {"default": 1.0, "min": 0.1, "max": 1.0, "step": 0.1}),
"refiner_strength": ("FLOAT", {"default": 1.0, "min": 0.1, "max": 1.0, "step": 0.05}),
"refiner_intensity": (SeargeParameterProcessor.REFINER_INTENSITY, {"default": "soft"}),
"precondition_steps": ("INT", {"default": 0, "min": 0, "max": 10}),
"batch_size": ("INT", {"default": 1, "min": 1, "max": 4}),
@@ -1265,7 +1274,7 @@ class SeargeInput7:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"lora_strength": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0, "step": 0.1}),
"lora_strength": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0, "step": 0.05}),
"operation_mode": (SeargeParameterProcessor.OPERATION_MODE, {"default": "text to image"}),
"prompt_style": (SeargeParameterProcessor.PROMPT_STYLE, {"default": "simple"}),
},