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Merge branch 'upstream/develop' 

# Conflicts:
#	webui.py
This commit is contained in:
Manuel Schmid 2024-04-30 15:26:19 +02:00
parent 2bd9936d5b dbf49d323e
commit d687ea73c4
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9 changed files with 116 additions and 44 deletions
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1
docker.md
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@ -54,6 +54,7 @@ Docker specified environments are there. They are used by 'entrypoint.sh'
|CMDARGS|Arguments for [entry_with_update.py](entry_with_update.py) which is called by [entrypoint.sh](entrypoint.sh)|
|config_path|'config.txt' location|
|config_example_path|'config_modification_tutorial.txt' location|
|HF_MIRROR| huggingface mirror site domain|
You can also use the same json key names and values explained in the 'config_modification_tutorial.txt' as the environments.
See examples in the [docker-compose.yml](docker-compose.yml)

98
extras/vae_interpose.py
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@ -1,69 +1,85 @@
# https://github.com/city96/SD-Latent-Interposer/blob/main/interposer.py
import os
import torch
import safetensors.torch as sf
import torch.nn as nn
import ldm_patched.modules.model_management
import safetensors.torch as sf
import torch
import torch.nn as nn
import ldm_patched.modules.model_management
from ldm_patched.modules.model_patcher import ModelPatcher
from modules.config import path_vae_approx
class Block(nn.Module):
def __init__(self, size):
class ResBlock(nn.Module):
"""Block with residuals"""
def __init__(self, ch):
super().__init__()
self.join = nn.ReLU()
self.norm = nn.BatchNorm2d(ch)
self.long = nn.Sequential(
nn.Conv2d(size, size, kernel_size=3, stride=1, padding=1),
nn.LeakyReLU(0.1),
nn.Conv2d(size, size, kernel_size=3, stride=1, padding=1),
nn.LeakyReLU(0.1),
nn.Conv2d(size, size, kernel_size=3, stride=1, padding=1),
nn.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1),
nn.SiLU(),
nn.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1),
nn.SiLU(),
nn.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1),
nn.Dropout(0.1)
)
def forward(self, x):
y = self.long(x)
z = self.join(y + x)
return z
x = self.norm(x)
return self.join(self.long(x) + x)
class Interposer(nn.Module):
def __init__(self):
class ExtractBlock(nn.Module):
"""Increase no. of channels by [out/in]"""
def __init__(self, ch_in, ch_out):
super().__init__()
self.chan = 4
self.hid = 128
self.head_join = nn.ReLU()
self.head_short = nn.Conv2d(self.chan, self.hid, kernel_size=3, stride=1, padding=1)
self.head_long = nn.Sequential(
nn.Conv2d(self.chan, self.hid, kernel_size=3, stride=1, padding=1),
nn.LeakyReLU(0.1),
nn.Conv2d(self.hid, self.hid, kernel_size=3, stride=1, padding=1),
nn.LeakyReLU(0.1),
nn.Conv2d(self.hid, self.hid, kernel_size=3, stride=1, padding=1),
)
self.core = nn.Sequential(
Block(self.hid),
Block(self.hid),
Block(self.hid),
)
self.tail = nn.Sequential(
nn.ReLU(),
nn.Conv2d(self.hid, self.chan, kernel_size=3, stride=1, padding=1)
self.join = nn.ReLU()
self.short = nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=1, padding=1)
self.long = nn.Sequential(
nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=1, padding=1),
nn.SiLU(),
nn.Conv2d(ch_out, ch_out, kernel_size=3, stride=1, padding=1),
nn.SiLU(),
nn.Conv2d(ch_out, ch_out, kernel_size=3, stride=1, padding=1),
nn.Dropout(0.1)
)
def forward(self, x):
y = self.head_join(
self.head_long(x) +
self.head_short(x)
return self.join(self.long(x) + self.short(x))
class InterposerModel(nn.Module):
"""Main neural network"""
def __init__(self, ch_in=4, ch_out=4, ch_mid=64, scale=1.0, blocks=12):
super().__init__()
self.ch_in = ch_in
self.ch_out = ch_out
self.ch_mid = ch_mid
self.blocks = blocks
self.scale = scale
self.head = ExtractBlock(self.ch_in, self.ch_mid)
self.core = nn.Sequential(
nn.Upsample(scale_factor=self.scale, mode="nearest"),
*[ResBlock(self.ch_mid) for _ in range(blocks)],
nn.BatchNorm2d(self.ch_mid),
nn.SiLU(),
)
self.tail = nn.Conv2d(self.ch_mid, self.ch_out, kernel_size=3, stride=1, padding=1)
def forward(self, x):
y = self.head(x)
z = self.core(y)
return self.tail(z)
vae_approx_model = None
vae_approx_filename = os.path.join(path_vae_approx, 'xl-to-v1_interposer-v3.1.safetensors')
vae_approx_filename = os.path.join(path_vae_approx, 'xl-to-v1_interposer-v4.0.safetensors')
def parse(x):
@ -72,7 +88,7 @@ def parse(x):
x_origin = x.clone()
if vae_approx_model is None:
model = Interposer()
model = InterposerModel()
model.eval()
sd = sf.load_file(vae_approx_filename)
model.load_state_dict(sd)

37
javascript/script.js
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@ -122,6 +122,43 @@ document.addEventListener("DOMContentLoaded", function() {
initStylePreviewOverlay();
});
var onAppend = function(elem, f) {
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
if (m.addedNodes.length) {
f(m.addedNodes);
}
});
});
observer.observe(elem, {childList: true});
}
function addObserverIfDesiredNodeAvailable(querySelector, callback) {
var elem = document.querySelector(querySelector);
if (!elem) {
window.setTimeout(() => addObserverIfDesiredNodeAvailable(querySelector, callback), 1000);
return;
}
onAppend(elem, callback);
}
/**
* Show reset button on toast "Connection errored out."
*/
addObserverIfDesiredNodeAvailable(".toast-wrap", function(added) {
added.forEach(function(element) {
if (element.innerText.includes("Connection errored out.")) {
window.setTimeout(function() {
document.getElementById("reset_button").classList.remove("hidden");
document.getElementById("generate_button").classList.add("hidden");
document.getElementById("skip_button").classList.add("hidden");
document.getElementById("stop_button").classList.add("hidden");
});
}
});
});
/**
* Add a ctrl+enter as a shortcut to start a generation
*/

1
language/en.json
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@ -4,6 +4,7 @@
"Generate": "Generate",
"Skip": "Skip",
"Stop": "Stop",
"Reconnect and Reset UI": "Reconnect and Reset UI",
"Input Image": "Input Image",
"Advanced": "Advanced",
"Upscale or Variation": "Upscale or Variation",

8
launch.py
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@ -63,8 +63,8 @@ def prepare_environment():
vae_approx_filenames = [
('xlvaeapp.pth', 'https://huggingface.co/lllyasviel/misc/resolve/main/xlvaeapp.pth'),
('vaeapp_sd15.pth', 'https://huggingface.co/lllyasviel/misc/resolve/main/vaeapp_sd15.pt'),
('xl-to-v1_interposer-v3.1.safetensors',
'https://huggingface.co/lllyasviel/misc/resolve/main/xl-to-v1_interposer-v3.1.safetensors')
('xl-to-v1_interposer-v4.0.safetensors',
'https://huggingface.co/mashb1t/misc/resolve/main/xl-to-v1_interposer-v4.0.safetensors')
]
@ -81,6 +81,10 @@ if args.gpu_device_id is not None:
os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_device_id)
print("Set device to:", args.gpu_device_id)
if args.hf_mirror is not None :
os.environ['HF_MIRROR'] = str(args.hf_mirror)
print("Set hf_mirror to:", args.hf_mirror)
from modules import config
os.environ["U2NET_HOME"] = config.path_inpaint

1
ldm_patched/modules/args_parser.py
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@ -37,6 +37,7 @@ parser.add_argument("--listen", type=str, default="127.0.0.1", metavar="IP", nar
parser.add_argument("--port", type=int, default=8188)
parser.add_argument("--disable-header-check", type=str, default=None, metavar="ORIGIN", nargs="?", const="*")
parser.add_argument("--web-upload-size", type=float, default=100)
parser.add_argument("--hf-mirror", type=str, default=None)
parser.add_argument("--external-working-path", type=str, default=None, metavar="PATH", nargs='+', action='append')
parser.add_argument("--output-path", type=str, default=None)

2
modules/model_loader.py
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@ -14,6 +14,8 @@ def load_file_from_url(
Returns the path to the downloaded file.
"""
domain = os.environ.get("HF_MIRROR", "https://huggingface.co").rstrip('/')
url = str.replace(url, "https://huggingface.co", domain, 1)
os.makedirs(model_dir, exist_ok=True)
if not file_name:
parts = urlparse(url)

1
readme.md
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@ -565,6 +565,7 @@ A safer way is just to try "run_anime.bat" or "run_realistic.bat" - they should
entry_with_update.py [-h] [--listen [IP]] [--port PORT]
[--disable-header-check [ORIGIN]]
[--web-upload-size WEB_UPLOAD_SIZE]
[--hf-mirror HF_MIRROR]
[--external-working-path PATH [PATH ...]]
[--output-path OUTPUT_PATH] [--temp-path TEMP_PATH]
[--cache-path CACHE_PATH] [--in-browser]

11
webui.py
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@ -123,8 +123,9 @@ with shared.gradio_root:
with gr.Column(scale=3, min_width=0):
generate_button = gr.Button(label="Generate", value="Generate", elem_classes='type_row', elem_id='generate_button', visible=True)
reset_button = gr.Button(label="Reconnect and Reset UI", value="Reconnect and Reset UI", elem_classes='type_row', elem_id='reset_button', visible=False)
load_parameter_button = gr.Button(label="Load Parameters", value="Load Parameters", elem_classes='type_row', elem_id='load_parameter_button', visible=False)
skip_button = gr.Button(label="Skip", value="Skip", elem_classes='type_row_half', visible=False)
skip_button = gr.Button(label="Skip", value="Skip", elem_classes='type_row_half', elem_id='skip_button', visible=False)
stop_button = gr.Button(label="Stop", value="Stop", elem_classes='type_row_half', elem_id='stop_button', visible=False)
def stop_clicked(currentTask):
@ -775,6 +776,14 @@ with shared.gradio_root:
.then(fn=update_history_link, outputs=history_link) \
.then(fn=lambda: None, _js='playNotification').then(fn=lambda: None, _js='refresh_grid_delayed')
reset_button.click(lambda: [worker.AsyncTask(args=[]), False, gr.update(visible=True, interactive=True)] +
[gr.update(visible=False)] * 6 +
[gr.update(visible=True, value=[])],
outputs=[currentTask, state_is_generating, generate_button,
reset_button, stop_button, skip_button,
progress_html, progress_window, progress_gallery, gallery],
queue=False)
def trigger_describe(mode, img):
if mode == flags.desc_type_photo:
from extras.interrogate import default_interrogator as default_interrogator_photo