add SEGSToImageList

bugfix: ImageReceiver/LatentReceiver crash on VALIDATE_INPUT
bugfix: ImageSender/LatentSender doesn't work occasionally

README.md

@@ -37,6 +37,8 @@ This custom node helps to conveniently enhance images through Detector, Detailer
 * SEGSPaste - Pastes the results of SEGS onto the original image.
 * SEGSPreview - Provides a preview of SEGS.
    * This option is used to preview the improved image through ```SEGSDetailer``` before merging it into the original. Prior to going through ```SEGSDetailer```, SEGS only contains mask information without image information. If fallback_image_opt is connected to the original image, SEGS without image information will generate a preview using the original image. However, if SEGS already contains image information, fallback_image_opt will be ignored. 
+* SEGSToImageList - Convert SEGS To Image List
+  * If SEGS is not present, the application will stop with an error unless [PR 731](https://github.com/comfyanonymous/ComfyUI/pull/731) from is applied.
 
 * Pipe nodes
    * ToDetailerPipe, FromDetailerPipe - These nodes are used to bundle multiple inputs used in the detailer, such as models and vae, ..., into a single DETAILER_PIPE or extract the elements that are bundled in the DETAILER_PIPE.

__init__.py

@@ -156,6 +156,7 @@ NODE_CLASS_MAPPINGS = {
     "SEGSDetailer": SEGSDetailer,
     "SEGSPaste": SEGSPaste,
     "SEGSPreview": SEGSPreview,
+    "SEGSToImageList": SEGSToImageList,
 
     "MaskPainter": impact.legacy_nodes.MaskPainter,
     "MMDetLoader": impact.legacy_nodes.MMDetLoader,

js/impact-pack.js

@@ -144,36 +144,18 @@ function latentSendHandler(event) {
 	}
 }
 
-var progressEventRegistered = false;
-var imgSendEventRegistered = false;
-var latentSendEventRegistered = false;
 const impactProgressBadge = new ImpactProgressBadge();
 
+api.addEventListener("img-send", imgSendHandler);
+api.addEventListener("latent-send", latentSendHandler);
+api.addEventListener("executed", progressExecuteHandler);
+
 app.registerExtension({
 	name: "Comfy.Impack",
 	loadedGraphNode(node, app) {
 		if (node.comfyClass == "PreviewBridge" || node.comfyClass == "MaskPainter") {
-			if (!progressEventRegistered) {
-				api.addEventListener("executed", progressExecuteHandler);
-				progressEventRegistered = true;
-			}
-
 			input_dirty[node.id + ""] = true;
 		}
-
-		if (node.comfyClass == "ImageSender") {
-			if (!imgSendEventRegistered) {
-				api.addEventListener("img-send", imgSendHandler);
-				imgSendEventRegistered = true;
-			}
-		}
-
-		if (node.comfyClass == "LatentSender") {
-			if (!latentSendEventRegistered) {
-				api.addEventListener("latent-send", latentSendHandler);
-				latentSendEventRegistered = true;
-			}
-		}
 	},
 
 	async beforeRegisterNodeDef(nodeType, nodeData, app) {

modules/impact/config.py

@@ -1,7 +1,7 @@
 import configparser
 import os
 
-version = "V2.16.3"
+version = "V2.16.4"
 
 dependency_version = 1
 

modules/impact/impact_pack.py

@@ -259,7 +259,7 @@ class SEGSPreview:
     RETURN_TYPES = ()
     FUNCTION = "doit"
 
-    CATEGORY = "ImpactPack/Detailer"
+    CATEGORY = "ImpactPack/Util"
 
     OUTPUT_NODE = True
 
@@ -291,6 +291,41 @@ class SEGSPreview:
         return {"ui": {"images": results}}
 
 
+class SEGSToImageList:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                     "segs": ("SEGS", ),
+                     },
+                "optional": {
+                     "fallback_image_opt": ("IMAGE", ),
+                    }
+                }
+
+    RETURN_TYPES = ("IMAGE",)
+    OUTPUT_IS_LIST = (True,)
+    FUNCTION = "doit"
+
+    CATEGORY = "ImpactPack/Util"
+
+    OUTPUT_NODE = True
+
+    def doit(self, segs, fallback_image_opt):
+        results = list()
+
+        for seg in segs[1]:
+            if seg.cropped_image is not None:
+                cropped_image = seg.cropped_image
+            elif fallback_image_opt is not None:
+                # take from original image
+                cropped_image = crop_image(fallback_image_opt, seg.crop_region)
+
+            cropped_image = torch.from_numpy(cropped_image)
+            results.append(cropped_image)
+
+        return (results,)
+
+
 class DetailerForEach:
     @classmethod
     def INPUT_TYPES(s):
@@ -1559,7 +1594,7 @@ class ImageReceiver(nodes.LoadImage):
 
     @classmethod
     def VALIDATE_INPUTS(s, image, link_id):
-        if not folder_paths.exists_annotated_filepath(image) or image.startswith("/") or image.contains(".."):
+        if not folder_paths.exists_annotated_filepath(image) or image.startswith("/") or ".." in image:
             return "Invalid image file: {}".format(image)
 
         return True
@@ -1670,7 +1705,7 @@ class LatentReceiver:
 
     @classmethod
     def VALIDATE_INPUTS(s, latent, link_id):
-        if not folder_paths.exists_annotated_filepath(latent) or latent.startswith("/") or latent.contains(".."):
+        if not folder_paths.exists_annotated_filepath(latent) or latent.startswith("/") or ".." in latent.contains:
             return "Invalid latent file: {}".format(latent)
         return True