Merge branch 'master' of https://github.com/cluder/stable-diffusion-webui into 4448_fix_ckpt_cache

CODEOWNERS

 *       @AUTOMATIC1111
-/localizations/ar_AR.json   @xmodar @blackneoo
-/localizations/de_DE.json   @LunixWasTaken
-/localizations/es_ES.json   @innovaciones
-/localizations/fr_FR.json   @tumbly
-/localizations/it_IT.json   @EugenioBuffo
-/localizations/ja_JP.json   @yuuki76
-/localizations/ko_KR.json   @36DB
-/localizations/pt_BR.json   @M-art-ucci
-/localizations/ru_RU.json   @kabachuha
-/localizations/tr_TR.json   @camenduru
-/localizations/zh_CN.json   @dtlnor @bgluminous
-/localizations/zh_TW.json   @benlisquare
+
+# if you were managing a localization and were removed from this file, this is because
+# the intended way to do localizations now is via extensions. See:
+# https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Developing-extensions
+# Make a repo with your localization and since you are still listed as a collaborator
+# you can add it to the wiki page yourself. This change is because some people complained
+# the git commit log is cluttered with things unrelated to almost everyone and
+# because I believe this is the best overall for the project to handle localizations almost
+# entirely without my oversight.
+
+

javascript/ui.js

@@ -208,4 +208,6 @@ function update_token_counter(button_id) {
 function restart_reload(){
     document.body.innerHTML='<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>';
     setTimeout(function(){location.reload()},2000)
+
+    return []
 }

modules/api/api.py

@@ -63,6 +63,7 @@ class Api:
         self.app.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
         self.app.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse)
         self.app.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse)
+        self.app.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"])
         self.app.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"])
         self.app.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel)
         self.app.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"])
@@ -214,6 +215,19 @@ class Api:
 
         return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image)
 
+    def interrogateapi(self, interrogatereq: InterrogateRequest):
+        image_b64 = interrogatereq.image
+        if image_b64 is None:
+            raise HTTPException(status_code=404, detail="Image not found") 
+
+        img = self.__base64_to_image(image_b64)
+
+        # Override object param
+        with self.queue_lock:
+            processed = shared.interrogator.interrogate(img)
+        
+        return InterrogateResponse(caption=processed)
+
     def interruptapi(self):
         shared.state.interrupt()
 

modules/api/models.py

@@ -65,6 +65,7 @@ class PydanticModelGenerator:
 
         self._model_name = model_name
         self._class_data = merge_class_params(class_instance)
+
         self._model_def = [
             ModelDef(
                 field=underscore(k),
@@ -167,6 +168,12 @@ class ProgressResponse(BaseModel):
     state: dict = Field(title="State", description="The current state snapshot")
     current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.")
 
+class InterrogateRequest(BaseModel):
+    image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.")
+
+class InterrogateResponse(BaseModel):
+    caption: str = Field(default=None, title="Caption", description="The generated caption for the image.")
+
 fields = {}
 for key, value in opts.data.items():
     metadata = opts.data_labels.get(key)
@@ -231,3 +238,4 @@ class ArtistItem(BaseModel):
     name: str = Field(title="Name")
     score: float = Field(title="Score")
     category: str = Field(title="Category")
+

modules/ldsr_model_arch.py

@@ -101,8 +101,8 @@ class LDSR:
         down_sample_rate = target_scale / 4
         wd = width_og * down_sample_rate
         hd = height_og * down_sample_rate
-        width_downsampled_pre = int(wd)
-        height_downsampled_pre = int(hd)
+        width_downsampled_pre = int(np.ceil(wd))
+        height_downsampled_pre = int(np.ceil(hd))
 
         if down_sample_rate != 1:
             print(
@@ -110,7 +110,12 @@ class LDSR:
             im_og = im_og.resize((width_downsampled_pre, height_downsampled_pre), Image.LANCZOS)
         else:
             print(f"Down sample rate is 1 from {target_scale} / 4 (Not downsampling)")
-        logs = self.run(model["model"], im_og, diffusion_steps, eta)
+        
+        # pad width and height to multiples of 64, pads with the edge values of image to avoid artifacts
+        pad_w, pad_h = np.max(((2, 2), np.ceil(np.array(im_og.size) / 64).astype(int)), axis=0) * 64 - im_og.size
+        im_padded = Image.fromarray(np.pad(np.array(im_og), ((0, pad_h), (0, pad_w), (0, 0)), mode='edge'))
+        
+        logs = self.run(model["model"], im_padded, diffusion_steps, eta)
 
         sample = logs["sample"]
         sample = sample.detach().cpu()
@@ -120,6 +125,9 @@ class LDSR:
         sample = np.transpose(sample, (0, 2, 3, 1))
         a = Image.fromarray(sample[0])
 
+        # remove padding
+        a = a.crop((0, 0) + tuple(np.array(im_og.size) * 4))
+
         del model
         gc.collect()
         torch.cuda.empty_cache()

modules/localization.py

@@ -3,6 +3,7 @@ import os
 import sys
 import traceback
 
+
 localizations = {}
 
 
@@ -16,6 +17,11 @@ def list_localizations(dirname):
 
         localizations[fn] = os.path.join(dirname, file)
 
+    from modules import scripts
+    for file in scripts.list_scripts("localizations", ".json"):
+        fn, ext = os.path.splitext(file.filename)
+        localizations[fn] = file.path
+
 
 def localization_js(current_localization_name):
     fn = localizations.get(current_localization_name, None)

modules/safe.py

@@ -23,11 +23,18 @@ def encode(*args):
 
 
 class RestrictedUnpickler(pickle.Unpickler):
+    extra_handler = None
+
     def persistent_load(self, saved_id):
         assert saved_id[0] == 'storage'
         return TypedStorage()
 
     def find_class(self, module, name):
+        if self.extra_handler is not None:
+            res = self.extra_handler(module, name)
+            if res is not None:
+                return res
+
         if module == 'collections' and name == 'OrderedDict':
             return getattr(collections, name)
         if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter']:
@@ -52,7 +59,7 @@ class RestrictedUnpickler(pickle.Unpickler):
             return set
 
         # Forbid everything else.
-        raise pickle.UnpicklingError(f"global '{module}/{name}' is forbidden")
+        raise Exception(f"global '{module}/{name}' is forbidden")
 
 
 allowed_zip_names = ["archive/data.pkl", "archive/version"]
@@ -69,7 +76,7 @@ def check_zip_filenames(filename, names):
         raise Exception(f"bad file inside {filename}: {name}")
 
 
-def check_pt(filename):
+def check_pt(filename, extra_handler):
     try:
 
         # new pytorch format is a zip file
@@ -78,6 +85,7 @@ def check_pt(filename):
 
             with z.open('archive/data.pkl') as file:
                 unpickler = RestrictedUnpickler(file)
+                unpickler.extra_handler = extra_handler
                 unpickler.load()
 
     except zipfile.BadZipfile:
@@ -85,16 +93,42 @@ def check_pt(filename):
         # if it's not a zip file, it's an olf pytorch format, with five objects written to pickle
         with open(filename, "rb") as file:
             unpickler = RestrictedUnpickler(file)
+            unpickler.extra_handler = extra_handler
             for i in range(5):
                 unpickler.load()
 
 
 def load(filename, *args, **kwargs):
+    return load_with_extra(filename, *args, **kwargs)
+
+
+def load_with_extra(filename, extra_handler=None, *args, **kwargs):
+    """
+    this functon is intended to be used by extensions that want to load models with
+    some extra classes in them that the usual unpickler would find suspicious.
+
+    Use the extra_handler argument to specify a function that takes module and field name as text,
+    and returns that field's value:
+
+    ```python
+    def extra(module, name):
+        if module == 'collections' and name == 'OrderedDict':
+            return collections.OrderedDict
+
+        return None
+
+    safe.load_with_extra('model.pt', extra_handler=extra)
+    ```
+
+    The alternative to this is just to use safe.unsafe_torch_load('model.pt'), which as the name implies is
+    definitely unsafe.
+    """
+
     from modules import shared
 
     try:
         if not shared.cmd_opts.disable_safe_unpickle:
-            check_pt(filename)
+            check_pt(filename, extra_handler)
 
     except pickle.UnpicklingError:
         print(f"Error verifying pickled file from {filename}:", file=sys.stderr)

modules/script_callbacks.py

@@ -7,6 +7,7 @@ from typing import Optional
 from fastapi import FastAPI
 from gradio import Blocks
 
+
 def report_exception(c, job):
     print(f"Error executing callback {job} for {c.script}", file=sys.stderr)
     print(traceback.format_exc(), file=sys.stderr)
@@ -45,15 +46,21 @@ class CFGDenoiserParams:
         """Total number of sampling steps planned"""
 
 
+class UiTrainTabParams:
+    def __init__(self, txt2img_preview_params):
+        self.txt2img_preview_params = txt2img_preview_params
+
+
 ScriptCallback = namedtuple("ScriptCallback", ["script", "callback"])
 callback_map = dict(
     callbacks_app_started=[],
     callbacks_model_loaded=[],
     callbacks_ui_tabs=[],
+    callbacks_ui_train_tabs=[],
     callbacks_ui_settings=[],
     callbacks_before_image_saved=[],
     callbacks_image_saved=[],
-    callbacks_cfg_denoiser=[]
+    callbacks_cfg_denoiser=[],
 )
 
 
@@ -61,6 +68,7 @@ def clear_callbacks():
     for callback_list in callback_map.values():
         callback_list.clear()
 
+
 def app_started_callback(demo: Optional[Blocks], app: FastAPI):
     for c in callback_map['callbacks_app_started']:
         try:
@@ -79,7 +87,7 @@ def model_loaded_callback(sd_model):
 
 def ui_tabs_callback():
     res = []
-    
+
     for c in callback_map['callbacks_ui_tabs']:
         try:
             res += c.callback() or []
@@ -89,6 +97,14 @@ def ui_tabs_callback():
     return res
 
 
+def ui_train_tabs_callback(params: UiTrainTabParams):
+    for c in callback_map['callbacks_ui_train_tabs']:
+        try:
+            c.callback(params)
+        except Exception:
+            report_exception(c, 'callbacks_ui_train_tabs')
+
+
 def ui_settings_callback():
     for c in callback_map['callbacks_ui_settings']:
         try:
@@ -169,6 +185,13 @@ def on_ui_tabs(callback):
     add_callback(callback_map['callbacks_ui_tabs'], callback)
 
 
+def on_ui_train_tabs(callback):
+    """register a function to be called when the UI is creating new tabs for the train tab.
+    Create your new tabs with gr.Tab.
+    """
+    add_callback(callback_map['callbacks_ui_train_tabs'], callback)
+
+
 def on_ui_settings(callback):
     """register a function to be called before UI settings are populated; add your settings
     by using shared.opts.add_option(shared.OptionInfo(...)) """

modules/scripts.py

@@ -3,7 +3,6 @@ import sys
 import traceback
 from collections import namedtuple
 
-import modules.ui as ui
 import gradio as gr
 
 from modules.processing import StableDiffusionProcessing

modules/shared.py

@@ -221,8 +221,6 @@ interrogator = modules.interrogate.InterrogateModels("interrogate")
 
 face_restorers = []
 
-localization.list_localizations(cmd_opts.localizations_dir)
-
 
 def realesrgan_models_names():
     import modules.realesrgan_model

modules/ui.py

@@ -174,9 +174,9 @@ def save_pil_to_file(pil_image, dir=None):
 gr.processing_utils.save_pil_to_file = save_pil_to_file
 
 
-def wrap_gradio_call(func, extra_outputs=None):
+def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
     def f(*args, extra_outputs_array=extra_outputs, **kwargs):
-        run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled
+        run_memmon = opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled and add_stats
         if run_memmon:
             shared.mem_mon.monitor()
         t = time.perf_counter()
@@ -203,11 +203,18 @@ def wrap_gradio_call(func, extra_outputs=None):
 
             res = extra_outputs_array + [f"<div class='error'>{plaintext_to_html(type(e).__name__+': '+str(e))}</div>"]
 
+        shared.state.skipped = False
+        shared.state.interrupted = False
+        shared.state.job_count = 0
+
+        if not add_stats:
+            return tuple(res)
+
         elapsed = time.perf_counter() - t
         elapsed_m = int(elapsed // 60)
         elapsed_s = elapsed % 60
         elapsed_text = f"{elapsed_s:.2f}s"
-        if (elapsed_m > 0):
+        if elapsed_m > 0:
             elapsed_text = f"{elapsed_m}m "+elapsed_text
 
         if run_memmon:
@@ -225,10 +232,6 @@ def wrap_gradio_call(func, extra_outputs=None):
         # last item is always HTML
         res[-1] += f"<div class='performance'><p class='time'>Time taken: <wbr>{elapsed_text}</p>{vram_html}</div>"
 
-        shared.state.skipped = False
-        shared.state.interrupted = False
-        shared.state.job_count = 0
-
         return tuple(res)
 
     return f
@@ -1138,7 +1141,7 @@ def create_ui(wrap_gradio_gpu_call):
             outputs=[html, generation_info, html2],
         )
 
-    with gr.Blocks() as modelmerger_interface:
+    with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='panel'):
                 gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>checkpoint</b> directory.</p>")
@@ -1158,7 +1161,7 @@ def create_ui(wrap_gradio_gpu_call):
 
     sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings()
 
-    with gr.Blocks() as train_interface:
+    with gr.Blocks(analytics_enabled=False) as train_interface:
         with gr.Row().style(equal_height=False):
             gr.HTML(value="<p style='margin-bottom: 0.7em'>See <b><a href=\"https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Textual-Inversion\">wiki</a></b> for detailed explanation.</p>")
 
@@ -1267,6 +1270,10 @@ def create_ui(wrap_gradio_gpu_call):
                         train_hypernetwork = gr.Button(value="Train Hypernetwork", variant='primary')
                         train_embedding = gr.Button(value="Train Embedding", variant='primary')
 
+                params = script_callbacks.UiTrainTabParams(txt2img_preview_params)
+
+                script_callbacks.ui_train_tabs_callback(params)
+
             with gr.Column():
                 progressbar = gr.HTML(elem_id="ti_progressbar")
                 ti_output = gr.Text(elem_id="ti_output", value="", show_label=False)
@@ -1417,15 +1424,14 @@ def create_ui(wrap_gradio_gpu_call):
 
         if info.refresh is not None:
             if is_quicksettings:
-                res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {}))
+                res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
                 create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
             else:
                 with gr.Row(variant="compact"):
-                    res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {}))
+                    res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
                     create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
         else:
-            res = comp(label=info.label, value=fun, elem_id=elem_id, **(args or {}))
-
+            res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
 
         return res
 
@@ -1436,7 +1442,7 @@ def create_ui(wrap_gradio_gpu_call):
     opts.reorder()
 
     def run_settings(*args):
-        changed = 0
+        changed = []
 
         for key, value, comp in zip(opts.data_labels.keys(), args, components):
             assert comp == dummy_component or opts.same_type(value, opts.data_labels[key].default), f"Bad value for setting {key}: {value}; expecting {type(opts.data_labels[key].default).__name__}"
@@ -1454,12 +1460,12 @@ def create_ui(wrap_gradio_gpu_call):
                 if opts.data_labels[key].onchange is not None:
                     opts.data_labels[key].onchange()
 
-                changed += 1
+                changed.append(key)
         try:
             opts.save(shared.config_filename)
         except RuntimeError:
-            return opts.dumpjson(), f'{changed} settings changed without save.'
-        return opts.dumpjson(), f'{changed} settings changed.'
+            return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.'
+        return opts.dumpjson(), f'{len(changed)} settings changed: {", ".join(changed)}.'
 
     def run_settings_single(value, key):
         if not opts.same_type(value, opts.data_labels[key].default):
@@ -1563,11 +1569,10 @@ def create_ui(wrap_gradio_gpu_call):
             shared.state.need_restart = True
 
         restart_gradio.click(
-
             fn=request_restart,
+            _js='restart_reload',
             inputs=[],
             outputs=[],
-            _js='restart_reload'
         )
 
         if column is not None:
@@ -1637,6 +1642,17 @@ def create_ui(wrap_gradio_gpu_call):
                 outputs=[component, text_settings],
             )
 
+        component_keys = [k for k in opts.data_labels.keys() if k in component_dict]
+
+        def get_settings_values():
+            return [getattr(opts, key) for key in component_keys]
+
+        demo.load(
+            fn=get_settings_values,
+            inputs=[],
+            outputs=[component_dict[k] for k in component_keys],
+        )
+
         def modelmerger(*args):
             try:
                 results = modules.extras.run_modelmerger(*args)
@@ -1740,7 +1756,7 @@ def create_ui(wrap_gradio_gpu_call):
     return demo
 
 
-def load_javascript(raw_response):
+def reload_javascript():
     with open(os.path.join(script_path, "script.js"), "r", encoding="utf8") as jsfile:
         javascript = f'<script>{jsfile.read()}</script>'
 
@@ -1756,7 +1772,7 @@ def load_javascript(raw_response):
     javascript += f"\n<script>{localization.localization_js(shared.opts.localization)}</script>"
 
     def template_response(*args, **kwargs):
-        res = raw_response(*args, **kwargs)
+        res = shared.GradioTemplateResponseOriginal(*args, **kwargs)
         res.body = res.body.replace(
             b'</head>', f'{javascript}</head>'.encode("utf8"))
         res.init_headers()
@@ -1765,4 +1781,5 @@ def load_javascript(raw_response):
     gradio.routes.templates.TemplateResponse = template_response
 
 
-reload_javascript = partial(load_javascript, gradio.routes.templates.TemplateResponse)
+if not hasattr(shared, 'GradioTemplateResponseOriginal'):
+    shared.GradioTemplateResponseOriginal = gradio.routes.templates.TemplateResponse