feat: PreviewBridge - add block mode based on PR2666

modules/impact/bridge_nodes.py

@@ -19,6 +19,9 @@ class PreviewBridge:
                     "images": ("IMAGE",),
                     "image": ("STRING", {"default": ""}),
                     },
+                "optional": {
+                    "block": ("BOOLEAN", {"default": True, "label_on": "if_empty_mask", "label_off": "never", "tooltip": "is_empty_mask: If the mask is empty, the execution is stopped.\nnever: The execution is never stopped."})
+                    },
                 "hidden": {"unique_id": "UNIQUE_ID", "extra_pnginfo": "EXTRA_PNGINFO"},
                 }
 
@@ -30,6 +33,8 @@ class PreviewBridge:
 
     CATEGORY = "ImpactPack/Util"
 
+    DESCRIPTION = "This is a feature that allows you to edit and send a Mask over a image.\nIf the block is set to 'is_empty_mask', the execution is stopped when the mask is empty."
+
     def __init__(self):
         super().__init__()
         self.output_dir = folder_paths.get_temp_directory()
@@ -70,7 +75,7 @@ class PreviewBridge:
 
         return image, mask.unsqueeze(0), ui_item
 
-    def doit(self, images, image, unique_id, prompt=None, extra_pnginfo=None):
+    def doit(self, images, image, unique_id, block=False, prompt=None, extra_pnginfo=None):
         need_refresh = False
 
         if unique_id not in core.preview_bridge_cache:
@@ -96,9 +101,20 @@ class PreviewBridge:
 
             image = image2
 
+        is_empty_mask = torch.all(mask == 0)
+
+        if block and is_empty_mask and core.is_execution_model_version_supported:
+            from comfy_execution.graph import ExecutionBlocker
+            result = ExecutionBlocker(None), ExecutionBlocker(None)
+        elif block and is_empty_mask:
+            print(f"[Impact Pack] PreviewBridge: ComfyUI is outdated - blocking feature is disabled.")
+            result = pixels, mask
+        else:
+            result = pixels, mask
+
         return {
             "ui": {"images": image},
-            "result": (pixels, mask, ),
+            "result": result,
         }
 
 
@@ -179,7 +195,8 @@ class PreviewBridgeLatent:
                                         "TAEF1", "TAESDXL", "TAESD15", "TAESD3"],),
                     },
                 "optional": {
-                    "vae_opt": ("VAE", )
+                    "vae_opt": ("VAE", ),
+                    "block": ("BOOLEAN", {"default": True, "label_on": "if_empty_mask", "label_off": "never", "tooltip": "is_empty_mask: If the mask is empty, the execution is stopped.\nnever: The execution is never stopped. Instead, it returns a white mask."})
                 },
                 "hidden": {"unique_id": "UNIQUE_ID", "prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
                 }
@@ -192,6 +209,8 @@ class PreviewBridgeLatent:
 
     CATEGORY = "ImpactPack/Util"
 
+    DESCRIPTION = "This is a feature that allows you to edit and send a Mask over a latent image.\nIf the block is set to 'is_empty_mask', the execution is stopped when the mask is empty."
+
     def __init__(self):
         super().__init__()
         self.output_dir = folder_paths.get_temp_directory()
@@ -233,7 +252,7 @@ class PreviewBridgeLatent:
 
         return image, mask, ui_item
 
-    def doit(self, latent, image, preview_method, vae_opt=None, unique_id=None, prompt=None, extra_pnginfo=None):
+    def doit(self, latent, image, preview_method, vae_opt=None, block=False, unique_id=None, prompt=None, extra_pnginfo=None):
         latent_channels = latent['samples'].shape[1]
         preview_method_channels = 16 if 'SD3' in preview_method or 'SC-Prior' in preview_method or 'FLUX.1' in preview_method or 'TAEF1' == preview_method else 4
 
@@ -262,10 +281,14 @@ class PreviewBridgeLatent:
                     del res_latent['noise_mask']
                 else:
                     res_latent = latent
+
+                is_empty_mask = True
             else:
                 res_latent = latent.copy()
                 res_latent['noise_mask'] = mask
 
+                is_empty_mask = torch.all(mask == 1)
+
             res_image = [path_item]
         else:
             decoded_image = decode_latent(latent, preview_method, vae_opt)
@@ -287,11 +310,15 @@ class PreviewBridgeLatent:
                                 'subfolder': 'PreviewBridge',
                                 'type': 'temp',
                             }]
+
+                is_empty_mask = torch.all(mask == 1)
             else:
                 mask = torch.ones(latent['samples'].shape[2:], dtype=torch.float32, device="cpu").unsqueeze(0)
                 res = nodes.PreviewImage().save_images(decoded_image, filename_prefix="PreviewBridge/PBL-", prompt=prompt, extra_pnginfo=extra_pnginfo)
                 res_image = res['ui']['images']
 
+                is_empty_mask = True
+
             path = os.path.join(folder_paths.get_temp_directory(), 'PreviewBridge', res_image[0]['filename'])
             core.set_previewbridge_image(unique_id, path, res_image[0])
             core.preview_bridge_image_id_map[image] = (path, res_image[0])
@@ -300,7 +327,16 @@ class PreviewBridgeLatent:
 
             res_latent = latent
 
+        if block and is_empty_mask and core.is_execution_model_version_supported:
+            from comfy_execution.graph import ExecutionBlocker
+            result = ExecutionBlocker(None), ExecutionBlocker(None)
+        elif block and is_empty_mask:
+            print(f"[Impact Pack] PreviewBridgeLatent: ComfyUI is outdated - blocking feature is disabled.")
+            result = res_latent, mask
+        else:
+            result = res_latent, mask
+
         return {
             "ui": {"images": res_image},
-            "result": (res_latent, mask, ),
+            "result": result,
         }

modules/impact/config.py

@@ -1,7 +1,7 @@
 import configparser
 import os
 
-version_code = [7, 3, 2]
+version_code = [7, 4]
 version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
 
 dependency_version = 22

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-impact-pack"
 description = "This extension offers various detector nodes and detailer nodes that allow you to configure a workflow that automatically enhances facial details. And provide iterative upscaler."
-version = "7.3.2"
+version = "7.4"
 license = { file = "LICENSE.txt" }
 dependencies = ["segment-anything", "scikit-image", "piexif", "transformers", "opencv-python-headless", "GitPython", "scipy>=1.11.4"]