diff --git a/README.MD b/README.MD
index de7f833..2567eac 100644
--- a/README.MD
+++ b/README.MD
@@ -1,6 +1,8 @@
 # ComfyUI Layer Style
 A set of nodes for ComfyUI that can composite layer and mask to achieve Photoshop like functionality.
 
+It migrate some basic functions of PhotoShop to ComfyUI, aiming to centralize the workflow and reduce the frequency of software switching.
+
 ![image](image/title.png)
 
 Nodes are divided into 5 groups according to their functions: LayerStyle, LayerColor, LayerMask, LayerUtility and LayerFilter.
diff --git a/README_CN.MD b/README_CN.MD
index b2dffc7..995d149 100644
--- a/README_CN.MD
+++ b/README_CN.MD
@@ -1,5 +1,5 @@
 # ComfyUI Layer Style
-一组为ComfyUI设计的节点，可以合成图层达到类似Photoshop的功能。
+一组为ComfyUI设计的节点，可以合成图层达到类似Photoshop的功能。这些节点将PhotoShop的一部分基本功能迁移到ComfyUI，旨在集中工作流程，减少软件切换的频率。
 
 ![image](image/title.png)
 节点按照功能分为5组：LayerStyle, LayerColor, LayerMask, LayerUtility和LayerFilter。
diff --git a/py/channel_shake.py b/py/channel_shake.py
index a294aaa..c39fe17 100644
--- a/py/channel_shake.py
+++ b/py/channel_shake.py
@@ -53,7 +53,7 @@ class ChannelShake:
             ret_image = Image.merge('RGB', [R, G, B])
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_adapter.py b/py/color_adapter.py
index 70d1077..fe58a61 100644
--- a/py/color_adapter.py
+++ b/py/color_adapter.py
@@ -47,7 +47,7 @@ class ColorAdapter:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_correct_HSV.py b/py/color_correct_HSV.py
index f7793af..42f3394 100644
--- a/py/color_correct_HSV.py
+++ b/py/color_correct_HSV.py
@@ -44,7 +44,7 @@ class ColorCorrectHSV:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_correct_LAB.py b/py/color_correct_LAB.py
index 347560b..d87ff31 100644
--- a/py/color_correct_LAB.py
+++ b/py/color_correct_LAB.py
@@ -44,7 +44,7 @@ class ColorCorrectLAB:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_correct_LUTapply.py b/py/color_correct_LUTapply.py
index d793915..756e63f 100644
--- a/py/color_correct_LUTapply.py
+++ b/py/color_correct_LUTapply.py
@@ -34,7 +34,7 @@ class ColorCorrectLUTapply:
             ret_image = lut_apply(_image, lut_file)
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_correct_RGB.py b/py/color_correct_RGB.py
index 7bbd207..9f2368a 100644
--- a/py/color_correct_RGB.py
+++ b/py/color_correct_RGB.py
@@ -44,7 +44,7 @@ class ColorCorrectRGB:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_correct_YUV.py b/py/color_correct_YUV.py
index f52678a..63c0a16 100644
--- a/py/color_correct_YUV.py
+++ b/py/color_correct_YUV.py
@@ -44,7 +44,7 @@ class ColorCorrectYUV:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_correct_brightness&contrast.py b/py/color_correct_brightness&contrast.py
index a89c4c0..7c63ed5 100644
--- a/py/color_correct_brightness&contrast.py
+++ b/py/color_correct_brightness&contrast.py
@@ -46,7 +46,7 @@ class ColorCorrectBrightnessAndContrast:
                 _image = color_image.enhance(factor=saturation)
             ret_images.append(pil2tensor(_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_correct_exposure.py b/py/color_correct_exposure.py
index 53c3460..ba7bc59 100644
--- a/py/color_correct_exposure.py
+++ b/py/color_correct_exposure.py
@@ -40,7 +40,7 @@ class ColorCorrectExposure:
                 t = np.clip((t - bp) * scale, 0.0, 1.0)
             ret_images.append(torch.from_numpy(t))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 
diff --git a/py/color_correct_gamma.py b/py/color_correct_gamma.py
index 5075183..c2c70d5 100644
--- a/py/color_correct_gamma.py
+++ b/py/color_correct_gamma.py
@@ -35,7 +35,7 @@ class ColorCorrectGamma:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_map.py b/py/color_map.py
index 686f07c..dab1575 100644
--- a/py/color_map.py
+++ b/py/color_map.py
@@ -44,7 +44,7 @@ class ColorMap:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/color_overlay.py b/py/color_overlay.py
index 0f4085b..c779fa5 100644
--- a/py/color_overlay.py
+++ b/py/color_overlay.py
@@ -77,7 +77,7 @@ class ColorOverlay:
 
             ret_images.append(pil2tensor(_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/crop_by_mask.py b/py/crop_by_mask.py
index 4f25bb3..0a5bc93 100644
--- a/py/crop_by_mask.py
+++ b/py/crop_by_mask.py
@@ -85,7 +85,7 @@ class CropByMask:
             ret_images.append(pil2tensor(_canvas.crop(crop_box)))
             ret_masks.append(image2mask(_mask.crop(crop_box)))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), list(crop_box), pil2tensor(preview_image),)
 
 
diff --git a/py/drop_shadow.py b/py/drop_shadow.py
index 620fd9b..cd19ddd 100644
--- a/py/drop_shadow.py
+++ b/py/drop_shadow.py
@@ -93,7 +93,7 @@ class DropShadow:
 
             ret_images.append(pil2tensor(_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 
diff --git a/py/extand_canvas.py b/py/extand_canvas.py
index 2cbb15c..a792d48 100644
--- a/py/extand_canvas.py
+++ b/py/extand_canvas.py
@@ -76,7 +76,7 @@ class ExtendCanvas:
             ret_images.append(pil2tensor(_canvas))
             ret_masks.append(image2mask(_mask_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
 
 
diff --git a/py/gaussian_blur.py b/py/gaussian_blur.py
index fcf77f1..7bd76c9 100644
--- a/py/gaussian_blur.py
+++ b/py/gaussian_blur.py
@@ -34,7 +34,7 @@ class GaussianBlur:
 
             ret_images.append(pil2tensor(gaussian_blur(_canvas, blur)))
 
-        log(f'GaussianBlur Processed {len(ret_images)} image(s).')
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/gradient_overlay.py b/py/gradient_overlay.py
index cb64bee..302c5a6 100644
--- a/py/gradient_overlay.py
+++ b/py/gradient_overlay.py
@@ -89,7 +89,7 @@ class GradientOverlay:
 
             ret_images.append(pil2tensor(_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/image_blend.py b/py/image_blend.py
index c015262..52e1491 100644
--- a/py/image_blend.py
+++ b/py/image_blend.py
@@ -73,7 +73,7 @@ class ImageBlend:
             _canvas.paste(_comp, mask=_mask)
 
             ret_images.append(pil2tensor(_canvas))
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/image_blend_advance.py b/py/image_blend_advance.py
index 7f7f0e3..def9456 100644
--- a/py/image_blend_advance.py
+++ b/py/image_blend_advance.py
@@ -121,7 +121,7 @@ class ImageBlendAdvance:
             ret_images.append(pil2tensor(_canvas))
             ret_masks.append(image2mask(_compmask))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/image_channel_merge.py b/py/image_channel_merge.py
index 0152f5e..963a444 100644
--- a/py/image_channel_merge.py
+++ b/py/image_channel_merge.py
@@ -59,7 +59,7 @@ class ImageChannelMerge:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/image_channel_split.py b/py/image_channel_split.py
index 47f4a38..161fb94 100644
--- a/py/image_channel_split.py
+++ b/py/image_channel_split.py
@@ -41,7 +41,7 @@ class ImageChannelSplit:
             c3_images.append(pil2tensor(channel3))
             c4_images.append(pil2tensor(channel4))
 
-        log(f"{NODE_NAME} Processed {len(c1_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(c1_images)} image(s).", message_type='finish')
         return (torch.cat(c1_images, dim=0), torch.cat(c2_images, dim=0), torch.cat(c3_images, dim=0), torch.cat(c4_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/image_mask_scale_as.py b/py/image_mask_scale_as.py
index e606bd7..8bb142f 100644
--- a/py/image_mask_scale_as.py
+++ b/py/image_mask_scale_as.py
@@ -77,13 +77,13 @@ class ImageMaskScaleAs:
                 _mask = fit_resize_image(_mask, target_width, target_height, fit, resize_sampler).convert('L')
                 ret_masks.append(image2mask(_mask))
         if len(ret_images) > 0 and len(ret_masks) >0:
-            log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+            log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
             return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
         elif len(ret_images) > 0 and len(ret_masks) == 0:
-            log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+            log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
             return (torch.cat(ret_images, dim=0), None,)
         elif len(ret_images) == 0 and len(ret_masks) > 0:
-            log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).")
+            log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).", message_type='finish')
             return (None, torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
         else:
             log(f"Error: {NODE_NAME} skipped, because the available image or mask is not found.", message_type='error')
diff --git a/py/image_opacity.py b/py/image_opacity.py
index 349a55d..8919e0c 100644
--- a/py/image_opacity.py
+++ b/py/image_opacity.py
@@ -74,7 +74,7 @@ class ImageOpacity:
             ret_images.append(pil2tensor(ret_image))
             ret_masks.append(image2mask(ret_mask))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/image_scale_restore.py b/py/image_scale_restore.py
index e109e66..b0f06c1 100644
--- a/py/image_scale_restore.py
+++ b/py/image_scale_restore.py
@@ -98,7 +98,7 @@ class ImageScaleRestore:
             ret_images.append(pil2tensor(ret_image))
             ret_masks.append(image2mask(ret_mask))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), [orig_width, orig_height],)
 
 
diff --git a/py/image_shift.py b/py/image_shift.py
index c367b40..9dd1d5c 100644
--- a/py/image_shift.py
+++ b/py/image_shift.py
@@ -78,7 +78,7 @@ class ImageShift:
             ret_masks.append(image2mask(_mask))
             ret_border_masks.append(image2mask(_border))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0), torch.cat(ret_border_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/imagefunc.py b/py/imagefunc.py
index de81ff8..75ef235 100644
--- a/py/imagefunc.py
+++ b/py/imagefunc.py
@@ -26,9 +26,11 @@ def log(message:str, message_type:str='info'):
     name = 'LayerStyle'
 
     if message_type == 'error':
-        message = '\033[1;31m' + message + '\033[m'
+        message = '\033[1;41m' + message + '\033[m'
     elif message_type == 'warning':
-        message = '\033[1;35m' + message + '\033[m'
+        message = '\033[1;31m' + message + '\033[m'
+    elif message_type == 'finish':
+        message = '\033[1;32m' + message + '\033[m'
     else:
         message = '\033[1;33m' + message + '\033[m'
     print(f"# 馃樅dzNodes: {name} -> {message}")
diff --git a/py/inner_glow.py b/py/inner_glow.py
index 2186668..d1a73b7 100644
--- a/py/inner_glow.py
+++ b/py/inner_glow.py
@@ -94,7 +94,7 @@ class InnerGlow:
             _layer.paste(_canvas, mask=ImageChops.invert(_mask))
             ret_images.append(pil2tensor(_layer))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 
diff --git a/py/inner_shadow.py b/py/inner_shadow.py
index b271238..6045a8e 100644
--- a/py/inner_shadow.py
+++ b/py/inner_shadow.py
@@ -90,7 +90,7 @@ class InnerShadow:
 
             ret_images.append(pil2tensor(_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/mask_box_detect.py b/py/mask_box_detect.py
index 5456dd8..b8593cc 100644
--- a/py/mask_box_detect.py
+++ b/py/mask_box_detect.py
@@ -62,7 +62,7 @@ class MaskBoxDetect:
         preview_image = tensor2pil(mask).convert('RGB')
         preview_image = draw_rect(preview_image, x - x_adjust, y - y_adjust, width, height, line_color="#F00000", line_width=int(preview_image.height / 60))
         preview_image = draw_rect(preview_image, x, y, width, height, line_color="#00F000", line_width=int(preview_image.height / 40))
-        log(f"{NODE_NAME} Processed.")
+        log(f"{NODE_NAME} Processed.", message_type='finish')
         return ( pil2tensor(preview_image), round(x_percent, 2), round(y_percent, 2), _width, _height, x, y,)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/mask_by_different.py b/py/mask_by_different.py
index 2901e61..b20ed39 100644
--- a/py/mask_by_different.py
+++ b/py/mask_by_different.py
@@ -66,7 +66,7 @@ class MaskByDifferent:
 
             ret_masks.append(image2mask(_mask))
 
-        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).")
+        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).", message_type='finish')
         return (torch.cat(ret_masks, dim=0),)
 
 
diff --git a/py/mask_edge_shrink.py b/py/mask_edge_shrink.py
index 4e139c5..fca81bf 100644
--- a/py/mask_edge_shrink.py
+++ b/py/mask_edge_shrink.py
@@ -67,7 +67,7 @@ class MaskEdgeShrink:
 
             ret_masks.append(image2mask(_layer))
 
-        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).")
+        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).", message_type='finish')
         return (torch.cat(ret_masks, dim=0),)
 
 
diff --git a/py/mask_edge_ultrl_detail.py b/py/mask_edge_ultrl_detail.py
index 3d0d614..6311864 100644
--- a/py/mask_edge_ultrl_detail.py
+++ b/py/mask_edge_ultrl_detail.py
@@ -65,7 +65,7 @@ class MaskEdgeUltraDetail:
             ret_images.append(pil2tensor(ret_image))
             ret_masks.append(image2mask(_mask))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/mask_gradient.py b/py/mask_gradient.py
index 5c21b69..00698a6 100644
--- a/py/mask_gradient.py
+++ b/py/mask_gradient.py
@@ -136,7 +136,7 @@ class MaskGradient:
                 _canvas = chop_image(_mask, _canvas, 'normal', opacity)
             ret_masks.append(image2mask(_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).")
+        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).", message_type='finish')
         return (torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/mask_grow.py b/py/mask_grow.py
index e90c3ee..b41d515 100644
--- a/py/mask_grow.py
+++ b/py/mask_grow.py
@@ -45,7 +45,7 @@ class MaskGrow:
             _mask = l_masks[i]
             ret_masks.append(expand_mask(image2mask(_mask), grow, blur) )
 
-        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).")
+        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).", message_type='finish')
         return (torch.cat(ret_masks, dim=0),)
 
 
diff --git a/py/mask_invert.py b/py/mask_invert.py
index ba4c918..72c2ab7 100644
--- a/py/mask_invert.py
+++ b/py/mask_invert.py
@@ -37,7 +37,6 @@ class MaskInvert:
             _mask = l_masks[i]
             ret_masks.append(mask_invert(image2mask(_mask)))
 
-        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).")
         return (torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/mask_motion_blur.py b/py/mask_motion_blur.py
index fdd381b..d602aba 100644
--- a/py/mask_motion_blur.py
+++ b/py/mask_motion_blur.py
@@ -45,7 +45,7 @@ class MaskMotionBlur:
             _blurimage = motion_blur(_mask, angle, blur)
             ret_masks.append(image2mask(_blurimage))
 
-        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).")
+        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).", message_type='finish')
         return (torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/mask_stroke.py b/py/mask_stroke.py
index c2da4f1..75d474e 100644
--- a/py/mask_stroke.py
+++ b/py/mask_stroke.py
@@ -51,7 +51,7 @@ class MaskStroke:
             stroke_mask = subtract_mask(outer_mask, inner_mask)
             ret_masks.append(stroke_mask)
 
-        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).")
+        log(f"{NODE_NAME} Processed {len(ret_masks)} mask(s).", message_type='finish')
         return (torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/motion_blur.py b/py/motion_blur.py
index b27caeb..2396c50 100644
--- a/py/motion_blur.py
+++ b/py/motion_blur.py
@@ -36,7 +36,7 @@ class MotionBlur:
 
             ret_images.append(pil2tensor(motion_blur(_canvas, angle, blur)))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/outer_glow.py b/py/outer_glow.py
index 750fd1b..4f6d543 100644
--- a/py/outer_glow.py
+++ b/py/outer_glow.py
@@ -93,7 +93,7 @@ class OuterGlow:
 
             ret_images.append(pil2tensor(_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 
diff --git a/py/pixel_spread.py b/py/pixel_spread.py
index 8ec59c2..9d44cc6 100644
--- a/py/pixel_spread.py
+++ b/py/pixel_spread.py
@@ -71,7 +71,7 @@ class PixelSpread:
 
             ret_images.append(torch.from_numpy(fg.astype(np.float32)))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/rembg_ultra.py b/py/rembg_ultra.py
index ad651df..cb697f2 100644
--- a/py/rembg_ultra.py
+++ b/py/rembg_ultra.py
@@ -40,7 +40,7 @@ class RemBgUltra:
             ret_images.append(pil2tensor(ret_image))
             ret_masks.append(image2mask(_mask))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/restore_crop_box.py b/py/restore_crop_box.py
index 26278bd..bd5edc3 100644
--- a/py/restore_crop_box.py
+++ b/py/restore_crop_box.py
@@ -70,7 +70,7 @@ class RestoreCropBox:
             ret_images.append(pil2tensor(_canvas))
             ret_masks.append(image2mask(ret_mask))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
 
 
diff --git a/py/segment_anything_ultra.py b/py/segment_anything_ultra.py
index ce6f53d..3a39218 100644
--- a/py/segment_anything_ultra.py
+++ b/py/segment_anything_ultra.py
@@ -61,7 +61,7 @@ class SegmentAnythingUltra:
             empty_mask = torch.zeros((1, height, width), dtype=torch.uint8, device="cpu")
             return (empty_mask, empty_mask)
 
-        log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_masks)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/sharp&soft.py b/py/sharp&soft.py
index f7197bb..edfa0d6 100644
--- a/py/sharp&soft.py
+++ b/py/sharp&soft.py
@@ -60,7 +60,7 @@ class SharpAndSoft:
             details = (imgB / imgG - 1) * detail_mult + 1
             dup[index] = np.clip(details * imgG - imgB + image, 0, 1)
 
-        log(f"{NODE_NAME} Processed {dup.shape[0]} image(s).")
+        log(f"{NODE_NAME} Processed {dup.shape[0]} image(s).", message_type='finish')
         return (torch.from_numpy(dup),)
 
 
diff --git a/py/skin_beauty.py b/py/skin_beauty.py
index 8d777ac..d1ccb69 100644
--- a/py/skin_beauty.py
+++ b/py/skin_beauty.py
@@ -50,7 +50,7 @@ class SkinBeauty:
             ret_images.append(pil2tensor(_canvas))
             ret_masks.append(image2mask(light_mask))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
 
 
diff --git a/py/soft_light.py b/py/soft_light.py
index a6e1c18..44ce95e 100644
--- a/py/soft_light.py
+++ b/py/soft_light.py
@@ -49,7 +49,7 @@ class SoftLight:
 
             ret_images.append(pil2tensor(_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/stroke.py b/py/stroke.py
index 97d38a2..c4c725c 100644
--- a/py/stroke.py
+++ b/py/stroke.py
@@ -90,7 +90,7 @@ class Stroke:
 
             ret_images.append(pil2tensor(_canvas))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/text_image.py b/py/text_image.py
index ec522d1..3a894b6 100644
--- a/py/text_image.py
+++ b/py/text_image.py
@@ -125,7 +125,7 @@ class TextImage:
         _color = Image.new('RGB', size=(width, height), color=text_color)
         _canvas.paste(_color, mask=_mask.convert('L'))
         _canvas = RGB2RGBA(_canvas, _mask)
-        log(f"{NODE_NAME} Processed.")
+        log(f"{NODE_NAME} Processed.", message_type='finish')
         return (pil2tensor(_canvas), image2mask(_mask),)
 
 NODE_CLASS_MAPPINGS = {
diff --git a/py/water_color.py b/py/water_color.py
index 1cfe058..9b5e6ca 100644
--- a/py/water_color.py
+++ b/py/water_color.py
@@ -39,7 +39,7 @@ class WaterColor:
 
             ret_images.append(pil2tensor(ret_image))
 
-        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).")
+        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
         return (torch.cat(ret_images, dim=0),)
 
 NODE_CLASS_MAPPINGS = {