feat: support conditioning mask for other detailers

modules/impact/animatediff_nodes.py

@@ -66,9 +66,27 @@ class SEGSDetailerForAnimateDiff:
                     cropped_image_frames = torch.concat((cropped_image_frames, cropped_image), dim=0)
 
             cropped_image_frames = cropped_image_frames.cpu().numpy()
+
+            # It is assumed that AnimateDiff does not support conditioning masks based on test results, but it will be added for future consideration.
+            cropped_positive = [
+                [condition, {
+                    k: core.crop_condition_mask(v, cropped_image_frames, seg.crop_region) if k == "mask" else v
+                    for k, v in details.items()
+                }]
+                for condition, details in positive
+            ]
+
+            cropped_negative = [
+                [condition, {
+                    k: core.crop_condition_mask(v, cropped_image_frames, seg.crop_region) if k == "mask" else v
+                    for k, v in details.items()
+                }]
+                for condition, details in negative
+            ]
+
             enhanced_image_tensor, cnet_images = core.enhance_detail_for_animatediff(cropped_image_frames, model, clip, vae, guide_size, guide_size_for, max_size,
                                                                                      seg.bbox, seed, steps, cfg, sampler_name, scheduler,
-                                                                                     positive, negative, denoise, seg.cropped_mask,
+                                                                                     cropped_positive, cropped_negative, denoise, seg.cropped_mask,
                                                                                      refiner_ratio=refiner_ratio, refiner_model=refiner_model,
                                                                                      refiner_clip=refiner_clip, refiner_positive=refiner_positive,
                                                                                      refiner_negative=refiner_negative, control_net_wrapper=seg.control_net_wrapper,

modules/impact/config.py

@@ -2,7 +2,7 @@ import configparser
 import os
 
 
-version_code = [4, 85, 2]
+version_code = [4, 86]
 version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
 
 dependency_version = 20

modules/impact/core.py

@@ -1892,6 +1892,12 @@ def adaptive_mask_paste(dest_mask, src_mask, bbox):
     dest_mask[y1:y2, x1:x2] = bbox_mask
 
 
+def crop_condition_mask(mask, image, crop_region):
+    cond_scale = (mask.shape[1] / image.shape[1], mask.shape[2] / image.shape[2])
+    mask_region = [round(v * cond_scale[i % 2]) for i, v in enumerate(crop_region)]
+    return crop_ndarray3(mask, mask_region)
+
+
 class SafeToGPU:
     def __init__(self, size):
         self.size = size

modules/impact/impact_pack.py

@@ -246,9 +246,25 @@ class DetailerForEach:
 
             seg_seed = seed + i if seg_seed is None else seg_seed
 
+            cropped_positive = [
+                [condition, {
+                    k: core.crop_condition_mask(v, image, seg.crop_region) if k == "mask" else v
+                    for k, v in details.items()
+                }]
+                for condition, details in positive
+            ]
+
+            cropped_negative = [
+                [condition, {
+                    k: core.crop_condition_mask(v, image, seg.crop_region) if k == "mask" else v
+                    for k, v in details.items()
+                }]
+                for condition, details in negative
+            ]
+
             enhanced_image, cnet_pils = core.enhance_detail(cropped_image, model, clip, vae, guide_size, guide_size_for_bbox, max_size,
                                                             seg.bbox, seg_seed, steps, cfg, sampler_name, scheduler,
-                                                            positive, negative, denoise, cropped_mask, force_inpaint,
+                                                            cropped_positive, cropped_negative, denoise, cropped_mask, force_inpaint,
                                                             wildcard_opt=wildcard_item, wildcard_opt_concat_mode=wildcard_concat_mode,
                                                             detailer_hook=detailer_hook,
                                                             refiner_ratio=refiner_ratio, refiner_model=refiner_model,

modules/impact/segs_nodes.py

@@ -12,12 +12,6 @@ from . import defs
 from . import segs_upscaler
 import math
 
-def crop_condition_mask(mask, image, crop_region):
-    cond_scale = (mask.shape[1] / image.shape[1], mask.shape[2] / image.shape[2])
-    mask_region = [round(v * cond_scale[i % 2]) for i, v in enumerate(crop_region)]
-    return crop_ndarray3(mask, mask_region)
-
-
 class SEGSDetailer:
     @classmethod
     def INPUT_TYPES(s):
@@ -92,7 +86,7 @@ class SEGSDetailer:
 
                 cropped_positive = [
                     [condition, {
-                        k: crop_condition_mask(v, image, seg.crop_region) if k == "mask" else v
+                        k: core.crop_condition_mask(v, image, seg.crop_region) if k == "mask" else v
                         for k, v in details.items()
                     }]
                     for condition, details in positive
@@ -100,7 +94,7 @@ class SEGSDetailer:
 
                 cropped_negative = [
                     [condition, {
-                        k: crop_condition_mask(v, image, seg.crop_region) if k == "mask" else v
+                        k: core.crop_condition_mask(v, image, seg.crop_region) if k == "mask" else v
                         for k, v in details.items()
                     }]
                     for condition, details in negative