Merge branch 'upstream/develop'

# Conflicts:
#	webui.py

docker.md

@@ -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)

extras/vae_interpose.py

@@ -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):
+class ResBlock(nn.Module):
-    def __init__(self, size):
+    """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.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1),
-            nn.LeakyReLU(0.1),
+            nn.SiLU(),
-            nn.Conv2d(size, size, kernel_size=3, stride=1, padding=1),
+            nn.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1),
-            nn.LeakyReLU(0.1),
+            nn.SiLU(),
-            nn.Conv2d(size, size, kernel_size=3, stride=1, padding=1),
+            nn.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1),
+            nn.Dropout(0.1)
         )
 
     def forward(self, x):
-        y = self.long(x)
+        x = self.norm(x)
-        z = self.join(y + x)
+        return self.join(self.long(x) + x)
-        return z
 
 
-class Interposer(nn.Module):
+class ExtractBlock(nn.Module):
-    def __init__(self):
+    """Increase no. of channels by [out/in]"""
+
+    def __init__(self, ch_in, ch_out):
         super().__init__()
-        self.chan = 4
+        self.join = nn.ReLU()
-        self.hid = 128
+        self.short = nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=1, padding=1)
-
+        self.long = nn.Sequential(
-        self.head_join = nn.ReLU()
+            nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=1, padding=1),
-        self.head_short = nn.Conv2d(self.chan, self.hid, kernel_size=3, stride=1, padding=1)
+            nn.SiLU(),
-        self.head_long = nn.Sequential(
+            nn.Conv2d(ch_out, ch_out, kernel_size=3, stride=1, padding=1),
-            nn.Conv2d(self.chan, self.hid, kernel_size=3, stride=1, padding=1),
+            nn.SiLU(),
-            nn.LeakyReLU(0.1),
+            nn.Conv2d(ch_out, ch_out, kernel_size=3, stride=1, padding=1),
-            nn.Conv2d(self.hid, self.hid, kernel_size=3, stride=1, padding=1),
+            nn.Dropout(0.1)
-            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)
         )
 
     def forward(self, x):
-        y = self.head_join(
+        return self.join(self.long(x) + self.short(x))
-            self.head_long(x) +
+
-            self.head_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)

javascript/script.js

@@ -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
  */

language/en.json

@@ -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",

launch.py

@@ -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',
+    ('xl-to-v1_interposer-v4.0.safetensors',
-     'https://huggingface.co/lllyasviel/misc/resolve/main/xl-to-v1_interposer-v3.1.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
 

ldm_patched/modules/args_parser.py

@@ -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)

modules/model_loader.py

@@ -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)

readme.md

@@ -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]

webui.py

@@ -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