Commit cb9d2f87 authored by yfszzx's avatar yfszzx

move to img component to public

parents 994aaadf 9f79e59a
......@@ -72,7 +72,7 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
- No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
- DeepDanbooru integration, creates danbooru style tags for anime prompts (add --deepdanbooru to commandline args)
- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)
- History tab: view, direct and delete images conveniently within the UI
- via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): view, direct and delete images conveniently within the UI
- Generate forever option
- Training tab
- hypernetworks and embeddings options
......@@ -95,6 +95,16 @@ git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-grad
After running this command, make sure that you have `aesthetic-gradients` dir in webui's `extensions` directory and restart
the UI. The interface for Aesthetic Gradients should appear exactly the same as it was.
## Where is History/Image browser?!?!
Image browser is now an extension. You can install it using git:
```commandline
git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser extensions/images-browser
```
After running this command, make sure that you have `images-browser` dir in webui's `extensions` directory and restart
the UI. The interface for Image browser should appear exactly the same as it was.
## Installation and Running
Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
......
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from modules.api.processing import StableDiffusionTxt2ImgProcessingAPI, StableDiffusionImg2ImgProcessingAPI
from modules.api.models import StableDiffusionTxt2ImgProcessingAPI, StableDiffusionImg2ImgProcessingAPI
from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
from modules.sd_samplers import all_samplers
from modules.extras import run_pnginfo
......
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......@@ -46,18 +46,23 @@ def apply_color_correction(correction, image):
return image
def apply_overlay(overlay_exists, overlay, paste_loc, image):
if overlay_exists:
if paste_loc is not None:
x, y, w, h = paste_loc
base_image = Image.new('RGBA', (overlay.width, overlay.height))
image = images.resize_image(1, image, w, h)
base_image.paste(image, (x, y))
image = base_image
image = image.convert('RGBA')
image.alpha_composite(overlay)
image = image.convert('RGB')
def apply_overlay(image, paste_loc, index, overlays):
if overlays is None or index >= len(overlays):
return image
overlay = overlays[index]
if paste_loc is not None:
x, y, w, h = paste_loc
base_image = Image.new('RGBA', (overlay.width, overlay.height))
image = images.resize_image(1, image, w, h)
base_image.paste(image, (x, y))
image = base_image
image = image.convert('RGBA')
image.alpha_composite(overlay)
image = image.convert('RGB')
return image
......@@ -463,11 +468,11 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
if p.color_corrections is not None and i < len(p.color_corrections):
if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction:
image_without_cc = apply_overlay(p.overlay_images is not None and i < len(p.overlay_images), p.overlay_images[i], p.paste_to, image)
image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images)
images.save_image(image_without_cc, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction")
image = apply_color_correction(p.color_corrections[i], image)
image = apply_overlay(p.overlay_images is not None and i < len(p.overlay_images), p.overlay_images[i], p.paste_to, image)
image = apply_overlay(image, p.paste_to, i, p.overlay_images)
if opts.samples_save and not p.do_not_save_samples:
images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p)
......
......@@ -86,6 +86,7 @@ parser.add_argument("--device-id", type=str, help="Select the default CUDA devic
cmd_opts = parser.parse_args()
restricted_opts = [
"samples_filename_pattern",
"directories_filename_pattern",
"outdir_samples",
"outdir_txt2img_samples",
"outdir_img2img_samples",
......@@ -190,7 +191,8 @@ options_templates = {}
options_templates.update(options_section(('saving-images', "Saving images/grids"), {
"samples_save": OptionInfo(True, "Always save all generated images"),
"samples_format": OptionInfo('png', 'File format for images'),
"samples_filename_pattern": OptionInfo("", "Images filename pattern"),
"samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs),
"save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs),
"grid_save": OptionInfo(True, "Always save all generated image grids"),
"grid_format": OptionInfo('png', 'File format for grids'),
......@@ -225,8 +227,8 @@ options_templates.update(options_section(('saving-to-dirs', "Saving to a directo
"save_to_dirs": OptionInfo(False, "Save images to a subdirectory"),
"grid_save_to_dirs": OptionInfo(False, "Save grids to a subdirectory"),
"use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"),
"directories_filename_pattern": OptionInfo("", "Directory name pattern"),
"directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1}),
"directories_filename_pattern": OptionInfo("", "Directory name pattern", component_args=hide_dirs),
"directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1, **hide_dirs}),
}))
options_templates.update(options_section(('upscaling', "Upscaling"), {
......@@ -348,7 +350,7 @@ class Options:
def save(self, filename):
with open(filename, "w", encoding="utf8") as file:
json.dump(self.data, file)
json.dump(self.data, file, indent=4)
def same_type(self, x, y):
if x is None or y is None:
......
......@@ -1889,7 +1889,7 @@ def load_javascript(raw_response):
javascript = f'<script>{jsfile.read()}</script>'
scripts_list = modules.scripts.list_scripts("javascript", ".js")
scripts_list += modules.scripts.list_scripts("scripts", ".js")
for basedir, filename, path in scripts_list:
with open(path, "r", encoding="utf8") as jsfile:
javascript += f"\n<!-- {filename} --><script>{jsfile.read()}</script>"
......
......@@ -9,7 +9,7 @@ from fastapi.middleware.gzip import GZipMiddleware
from modules.paths import script_path
from modules import devices, sd_samplers
from modules import devices, sd_samplers, upscaler
import modules.codeformer_model as codeformer
import modules.extras
import modules.face_restoration
......@@ -73,12 +73,11 @@ def wrap_gradio_gpu_call(func, extra_outputs=None):
def initialize():
modules.scripts.load_scripts()
if cmd_opts.ui_debug_mode:
class enmpty():
name = None
shared.sd_upscalers = [enmpty()]
shared.sd_upscalers = upscaler.UpscalerLanczos().scalers
modules.scripts.load_scripts()
return
modelloader.cleanup_models()
modules.sd_models.setup_model()
codeformer.setup_model(cmd_opts.codeformer_models_path)
......@@ -86,6 +85,8 @@ def initialize():
shared.face_restorers.append(modules.face_restoration.FaceRestoration())
modelloader.load_upscalers()
modules.scripts.load_scripts()
modules.sd_models.load_model()
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
......
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