Merge branch 'main' into dev

README.md

@@ -53,9 +53,9 @@ This is an extensive node suite that enables ComfyUI to process 3D inputs (Mesh
 
 - **Unique3D**: [AiuniAI/Unique3D](https://github.com/AiuniAI/Unique3D)
   - Four stages pipeline: 
-    1. Single image to 4 multi-view images with resulution: 256X256
+    1. Single image to 4 multi-view images with resolution: 256X256
     2. Consistent Multi-view images Upscale to 512X512, super resolution to 2048X2048
-    3. Multi-view images to Normal maps with resulution: 512X512, super resolution to 2048X2048
+    3. Multi-view images to Normal maps with resolution: 512X512, super resolution to 2048X2048
     4. Multi-view images & Normal maps to 3D mesh with texture
   - To use the [All stage Unique3D workflow](./_Example_Workflows/Unique3D/Unique3D_All_Stages.json), Download Models:
     - [sdv1.5-pruned-emaonly](https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned-emaonly.ckpt) and put it into `Your ComfyUI root directory/ComfyUI/models/checkpoints`
@@ -68,7 +68,7 @@ This is an extensive node suite that enables ComfyUI to process 3D inputs (Mesh
   <video controls autoplay loop src="https://github.com/MrForExample/ComfyUI-3D-Pack/assets/62230687/45dd6bfc-4f2b-4b1f-baed-13a1b0722896"></video>
 
 - **Era3D MVDiffusion Model**: [pengHTYX/Era3D](https://github.com/pengHTYX/Era3D)
-  - Single image to 6 multi-view images & normal maps with resulution: 512X512
+  - Single image to 6 multi-view images & normal maps with resolution: 512X512
   - *Note: you need at least 16GB vram to run this model*
   - Model weights: https://huggingface.co/pengHTYX/MacLab-Era3D-512-6view/tree/main
 
@@ -84,7 +84,7 @@ This is an extensive node suite that enables ComfyUI to process 3D inputs (Mesh
 
 
 - **Zero123++**: [SUDO-AI-3D/zero123plus](https://github.com/SUDO-AI-3D/zero123plus)
-  - Single image to 6 view images with resulution: 320X320
+  - Single image to 6 view images with resolution: 320X320
 
 - **Convolutional Reconstruction Model**: [thu-ml/CRM](https://github.com/thu-ml/CRM)
   - Three stages pipeline: 

_Example_Workflows/CharacterGen/CharacterGen_InstantMesh.json

@@ -79,7 +79,7 @@
     },
     {
       "id": 32,
-      "type": "IMG_padder",
+      "type": "Eden_IMG_padder",
       "pos": [
         210,
         440
@@ -110,7 +110,7 @@
         }
       ],
       "properties": {
-        "Node name for S&R": "IMG_padder"
+        "Node name for S&R": "Eden_IMG_padder"
       },
       "widgets_values": [
         0.25,
@@ -317,7 +317,7 @@
     },
     {
       "id": 33,
-      "type": "IMG_padder",
+      "type": "Eden_IMG_padder",
       "pos": [
         570,
         440
@@ -348,7 +348,7 @@
         }
       ],
       "properties": {
-        "Node name for S&R": "IMG_padder"
+        "Node name for S&R": "Eden_IMG_padder"
       },
       "widgets_values": [
         0.2,

_Example_Workflows/CharacterGen/CharacterGen_to_Unique3D.json

@@ -738,7 +738,7 @@
     },
     {
       "id": 350,
-      "type": "IMG_padder",
+      "type": "Eden_IMG_padder",
       "pos": [
         -329.80954879404095,
         -427.3873149879231
@@ -769,7 +769,7 @@
         }
       ],
       "properties": {
-        "Node name for S&R": "IMG_padder"
+        "Node name for S&R": "Eden_IMG_padder"
       },
       "widgets_values": [
         0.25,
@@ -778,7 +778,7 @@
     },
     {
       "id": 351,
-      "type": "IMG_padder",
+      "type": "Eden_IMG_padder",
       "pos": [
         30.190451205959107,
         -427.3873149879231
@@ -809,7 +809,7 @@
         }
       ],
       "properties": {
-        "Node name for S&R": "IMG_padder"
+        "Node name for S&R": "Eden_IMG_padder"
       },
       "widgets_values": [
         0.2,

nodes.py

@@ -561,10 +561,11 @@ class Rotate_Normal_Maps_Horizontally:
     CATEGORY = "Comfy3D/Preprocessor"
     
     def make_image_grid(self, normal_maps, normal_masks, clockwise):
+        rotate_direction = 1 if clockwise is True else -1
         if normal_maps.shape[0] > 1:
             from Unique3D.scripts.utils import rotate_normals_torch
             pil_image_list = torch_imgs_to_pils(normal_maps, normal_masks)
-            pil_image_list = rotate_normals_torch(pil_image_list, return_types='pil', rotate_direction=int(clockwise))
+            pil_image_list = rotate_normals_torch(pil_image_list, return_types='pil', rotate_direction=rotate_direction)
             normal_maps = pils_to_torch_imgs(pil_image_list, normal_maps.dtype, normal_maps.device)
         return (normal_maps,)