diff --git a/extensions-builtin/sd_forge_controlnet/scripts/controlnet.py b/extensions-builtin/sd_forge_controlnet/scripts/controlnet.py
index 91a18112..97bcd8d8 100644
--- a/extensions-builtin/sd_forge_controlnet/scripts/controlnet.py
+++ b/extensions-builtin/sd_forge_controlnet/scripts/controlnet.py
@@ -404,11 +404,10 @@ class ControlNetForForgeOfficial(scripts.Script):
         Infotext.write_infotext(enabled_units, p)
         return enabled_units
 
-    @staticmethod
     def choose_input_image(
+            self,
             p: processing.StableDiffusionProcessing,
             unit: external_code.ControlNetUnit,
-            idx: int
         ) -> Tuple[np.ndarray, external_code.ResizeMode]:
         """ Choose input image from following sources with descending priority:
          - p.image_control: [Deprecated] Lagacy way to pass image to controlnet.
@@ -444,25 +443,12 @@ class ControlNetForForgeOfficial(scripts.Script):
                 return img
 
         # 4 input image sources.
-        p_image_control = getattr(p, "image_control", None)
-        p_input_image = Script.get_remote_call(p, "control_net_input_image", None, idx)
         image = parse_unit_image(unit)
         a1111_image = getattr(p, "init_images", [None])[0]
 
         resize_mode = external_code.resize_mode_from_value(unit.resize_mode)
 
-        if p_image_control is not None:
-            logger.warning("Warn: Using legacy field 'p.image_control'.")
-            input_image = HWC3(np.asarray(p_image_control))
-        elif p_input_image is not None:
-            logger.warning("Warn: Using legacy field 'p.controlnet_input_image'")
-            if isinstance(p_input_image, dict) and "mask" in p_input_image and "image" in p_input_image:
-                color = HWC3(np.asarray(p_input_image['image']))
-                alpha = np.asarray(p_input_image['mask'])[..., None]
-                input_image = np.concatenate([color, alpha], axis=2)
-            else:
-                input_image = HWC3(np.asarray(p_input_image))
-        elif image:
+        if image is not None:
             if isinstance(image, list):
                 # Add mask logic if later there is a processor that accepts mask
                 # on multiple inputs.
@@ -645,41 +631,6 @@ class ControlNetForForgeOfficial(scripts.Script):
 
     def controlnet_main_entry(self, p):
         for idx, unit in enumerate(self.enabled_units):
-            Script.bound_check_params(unit)
-            Script.check_sd_version_compatible(unit)
-            if (
-                "ip-adapter" in unit.module and
-                not global_state.ip_adapter_pairing_model[unit.module](unit.model)
-            ):
-                logger.error(f"Invalid pair of IP-Adapter preprocessor({unit.module}) and model({unit.model}).\n"
-                             "Please follow following pairing logic:\n"
-                             + global_state.ip_adapter_pairing_logic_text)
-                continue
-
-            if (
-                'inpaint_only' == unit.module and
-                issubclass(type(p), StableDiffusionProcessingImg2Img) and
-                p.image_mask is not None
-            ):
-                logger.warning('A1111 inpaint and ControlNet inpaint duplicated. Falls back to inpaint_global_harmonious.')
-                unit.module = 'inpaint'
-
-            if unit.module in model_free_preprocessors:
-                model_net = None
-                if 'reference' in unit.module:
-                    control_model_type = ControlModelType.AttentionInjection
-                elif 'revision' in unit.module:
-                    control_model_type = ControlModelType.ReVision
-                else:
-                    raise Exception("Unable to determine control_model_type.")
-            else:
-                model_net, control_model_type = Script.load_control_model(p, unet, unit.model)
-                model_net.reset()
-
-                if control_model_type == ControlModelType.ControlLoRA:
-                    control_lora = model_net.control_model
-                    bind_control_lora(unet, control_lora)
-                    p.controlnet_control_loras.append(control_lora)
 
             input_image, resize_mode = Script.choose_input_image(p, unit, idx)
             if isinstance(input_image, list):
@@ -903,6 +854,7 @@ class ControlNetForForgeOfficial(scripts.Script):
 
     def process_unit_after_click_generate(self, p, unit, params, *args, **kwargs):
         h, w, hr_y, hr_x = self.get_target_dimensions(p)
+        input_image, resize_mode = self.choose_input_image(p, unit)
         return
 
     def process_unit_before_every_sampling(self, p, unit, params, *args, **kwargs):