Update controlnet.py

extensions-builtin/sd_forge_controlnet/scripts/controlnet.py

@@ -166,22 +166,7 @@ def get_pytorch_control(x: np.ndarray) -> torch.Tensor:
     return y
 
 
-class Script(scripts.Script, metaclass=(
-    utils.TimeMeta if logger.level == logging.DEBUG else type)):
-
-    model_cache = OrderedDict()
-
-    def __init__(self) -> None:
-        super().__init__()
-        self.latest_network = None
-        self.input_image = None
-        self.latest_model_hash = ""
-        self.enabled_units = []
-        self.detected_map = []
-        self.post_processors = []
-        self.noise_modifier = None
-        self.ui_batch_option_state = [external_code.BatchOption.DEFAULT.value, False]
-
+class ControlNetForForgeOfficial(scripts.Script):
     def title(self):
         return "ControlNet"
 
@@ -205,45 +190,6 @@ class Script(scripts.Script, metaclass=(
         )
         return group, group.render(tabname, elem_id_tabname)
 
-    def ui_batch_options(self, is_img2img: bool, elem_id_tabname: str):
-        batch_option = gr.Radio(
-            choices=[e.value for e in external_code.BatchOption],
-            value=external_code.BatchOption.DEFAULT.value,
-            label="Batch Option",
-            elem_id=f"{elem_id_tabname}_controlnet_batch_option_radio",
-            elem_classes="controlnet_batch_option_radio",
-        )
-        use_batch_style_align = gr.Checkbox(
-            label='[StyleAlign] Align image style in the batch.'
-        )
-
-        unit_args = [batch_option, use_batch_style_align]
-
-        def update_ui_batch_options(*args):
-            self.ui_batch_option_state = args
-            return
-
-        for comp in unit_args:
-            event_subscribers = []
-            if hasattr(comp, "edit"):
-                event_subscribers.append(comp.edit)
-            elif hasattr(comp, "click"):
-                event_subscribers.append(comp.click)
-            elif isinstance(comp, gr.Slider) and hasattr(comp, "release"):
-                event_subscribers.append(comp.release)
-            elif hasattr(comp, "change"):
-                event_subscribers.append(comp.change)
-
-            if hasattr(comp, "clear"):
-                event_subscribers.append(comp.clear)
-
-            for event_subscriber in event_subscribers:
-                event_subscriber(
-                    fn=update_ui_batch_options, inputs=unit_args
-                )
-
-        return
-
     def ui(self, is_img2img):
         """this function should create gradio UI elements. See https://gradio.app/docs/#components
         The return value should be an array of all components that are used in processing.
@@ -1012,49 +958,18 @@ class Script(scripts.Script, metaclass=(
         return
 
     def process(self, p, *args, **kwargs):
-        for unit in Script.get_enabled_units(p):
+        for unit in self.get_enabled_units(p):
             self.process_unit_after_click_generate(p, unit, *args, **kwargs)
         return
 
     def process_before_every_sampling(self, p, *args, **kwargs):
-        for unit in Script.get_enabled_units(p):
+        for unit in self.get_enabled_units(p):
             self.process_unit_before_every_sampling(p, unit, *args, **kwargs)
         return
 
     def postprocess(self, p, processed, *args):
         return
 
-    def batch_tab_process(self, p, batches, *args, **kwargs):
-        self.enabled_units = Script.get_enabled_units(p)
-        for unit_i, unit in enumerate(self.enabled_units):
-            unit.batch_images = iter([batch[unit_i] for batch in batches])
-
-    def batch_tab_process_each(self, p, *args, **kwargs):
-        for unit_i, unit in enumerate(self.enabled_units):
-            if getattr(unit, 'loopback', False):
-                continue
-
-            unit.image = next(unit.batch_images)
-
-    def batch_tab_postprocess_each(self, p, processed, *args, **kwargs):
-        for unit_i, unit in enumerate(self.enabled_units):
-            if getattr(unit, 'loopback', False):
-                output_images = getattr(processed, 'images', [])[processed.index_of_first_image:]
-                if output_images:
-                    unit.image = np.array(output_images[0])
-                else:
-                    logger.warning(f'Warning: No loopback image found for controlnet unit {unit_i}. '
-                                   f'Using control map from last batch iteration instead')
-
-    def batch_tab_postprocess(self, p, *args, **kwargs):
-        self.enabled_units.clear()
-        self.input_image = None
-        if self.latest_network is None: return
-
-        self.latest_network.restore()
-        self.latest_network = None
-        self.detected_map.clear()
-
 
 def on_ui_settings():
     section = ('control_net', "ControlNet")