feat: Mask TO SEGS For AnimateDiff

fix: Mask To SEGS - crash when batch mask

README.md

@@ -57,6 +57,7 @@ This custom node helps to conveniently enhance images through Detector, Detailer
   * DetailerDebug (SEGS) - Refines the image based on SEGS. Additionally, it provides the ability to monitor the cropped image and the refined image of the cropped image.
     * To prevent regeneration caused by the seed that does not change every time when using 'external_seed', please disable the 'seed random generate' option in the 'Detailer...' node.
   * MASK to SEGS - Generates SEGS based on the mask.
+    * MASK to SEGS For AnimateDiff - Generates SEGS based on the mask for AnimateDiff.
   * MediaPipe FaceMesh to SEGS - Separate each landmark from the mediapipe facemesh image to create labeled SEGS.
     * Usually, the size of images created through the MediaPipe facemesh preprocessor is downscaled. It resizes the MediaPipe facemesh image to the original size given as reference_image_opt for matching sizes during processing. 
   * ToBinaryMask - Separates the mask generated with alpha values between 0 and 255 into 0 and 255. The non-zero parts are always set to 255.

__init__.py

@@ -173,6 +173,7 @@ NODE_CLASS_MAPPINGS = {
 
     "MediaPipeFaceMeshToSEGS": MediaPipeFaceMeshToSEGS,
     "MaskToSEGS": MaskToSEGS,
+    "MaskToSEGS_for_AnimateDiff": MaskToSEGS_for_AnimateDiff,
     "ToBinaryMask": ToBinaryMask,
     "MasksToMaskList": MasksToMaskList,
     "MaskListToMaskBatch": MaskListToMaskBatch,
@@ -295,6 +296,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "SegsToCombinedMask": "SEGS to MASK (combined)",
     "MediaPipeFaceMeshToSEGS": "MediaPipe FaceMesh to SEGS",
     "MaskToSEGS": "MASK to SEGS",
+    "MaskToSEGS_for_AnimateDiff": "MASK to SEGS for AnimateDiff",
     "BitwiseAndMaskForEach": "Bitwise(SEGS & SEGS)",
     "SubtractMaskForEach": "Bitwise(SEGS - SEGS)",
     "ImpactSegsAndMask": "Bitwise(SEGS & MASK)",

modules/impact/config.py

@@ -2,7 +2,7 @@ import configparser
 import os
 
 
-version = "V4.34.2"
+version = "V4.35"
 
 dependency_version = 19
 

modules/impact/core.py

@@ -915,8 +915,6 @@ def mask_to_segs(mask, combined, crop_factor, bbox_fill, drop_size=1, label='A',
 
     if len(mask.shape) == 2:
         mask = np.expand_dims(mask, axis=0)
-    else:
-        mask = np.squeeze(mask, axis=1)
 
     for i in range(mask.shape[0]):
         mask_i = mask[i]

modules/impact/segs_nodes.py

@@ -11,6 +11,7 @@ from nodes import MAX_RESOLUTION
 from impact.utils import *
 import impact.core as core
 from impact.core import SEG
+import impact.utils as utils
 
 class SEGSDetailer:
     @classmethod
@@ -926,6 +927,40 @@ class MaskToSEGS:
         return (result, )
 
 
+class MaskToSEGS_for_AnimateDiff:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                                "mask": ("MASK",),
+                                "combined": ("BOOLEAN", {"default": False, "label_on": "True", "label_off": "False"}),
+                                "crop_factor": ("FLOAT", {"default": 3.0, "min": 1.0, "max": 100, "step": 0.1}),
+                                "bbox_fill": ("BOOLEAN", {"default": False, "label_on": "enabled", "label_off": "disabled"}),
+                                "drop_size": ("INT", {"min": 1, "max": MAX_RESOLUTION, "step": 1, "default": 10}),
+                             }
+                }
+
+    RETURN_TYPES = ("SEGS",)
+    FUNCTION = "doit"
+
+    CATEGORY = "ImpactPack/Operation"
+
+    def doit(self, mask, combined, crop_factor, bbox_fill, drop_size):
+        if len(mask.shape) == 3:
+            mask = mask.squeeze(0)
+
+        segs = core.mask_to_segs(mask, combined, crop_factor, bbox_fill, drop_size)
+
+        all_masks = SEGSToMaskList().doit(segs)[0]
+
+        result_mask = all_masks[0]
+        for mask in all_masks[1:]:
+            result_mask += mask
+
+        result_mask = utils.to_binary_mask(result_mask, 0.1)
+
+        return MaskToSEGS().doit(result_mask, False, crop_factor, False, drop_size)
+
+
 class ControlNetApplySEGS:
     @classmethod
     def INPUT_TYPES(s):