Adding an RS Image node to Latent (simplified)

Rayko_Image_to_Latent_(simplified).py

@@ -0,0 +1,101 @@
+# SPDX-License-Identifier: Apache-2.0
+# Copyright 2025-2026 Raykosan (RaykoStudio)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import torch
+import math
+import comfy.utils
+
+class RS_ImageToLatent_Simplified:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE", {"tooltip": "Input image to convert to latent"}),
+                "vae": ("VAE", {"tooltip": "VAE model for encoding"}),
+                "batch_size": (
+                    "INT", {
+                        "default": 1, 
+                        "min": 1, 
+                        "max": 64, 
+                        "step": 1,
+                        "tooltip": "Number of identical latents in batch"
+                    }
+                ),
+            }
+        }
+    
+    RETURN_TYPES = ("LATENT", "INT", "INT")
+    RETURN_NAMES = ("latent", "width_px", "height_px")
+    FUNCTION = "convert"
+    CATEGORY = "🦊 RaykoStudio"
+    DESCRIPTION = "Simplified version: converts image to latent with automatic size optimization"
+    
+    def _get_divisibility_from_vae(self, vae):
+        if not hasattr(self, '_cached_divisibility'):
+            try:
+                with torch.no_grad():
+                    test = torch.zeros(1, 64, 64, 3)
+                    latent = vae.encode(test)
+                    latent_h = latent["samples"].shape[2]
+                    self._cached_divisibility = 64 // latent_h
+            except:
+                self._cached_divisibility = 16
+        return self._cached_divisibility
+    
+    def _apply_divisibility(self, value, divisor):
+        return round(value / divisor) * divisor
+    
+    def convert(self, image, vae, batch_size):
+        divisibility = self._get_divisibility_from_vae(vae)
+        
+        _, img_h, img_w, _ = image.shape
+        
+        target_w = self._apply_divisibility(img_w, divisibility)
+        target_h = self._apply_divisibility(img_h, divisibility)
+        
+        target_w = max(divisibility, target_w)
+        target_h = max(divisibility, target_h)
+        
+        if (img_w, img_h) != (target_w, target_h):
+            image = image.movedim(-1, 1)
+            image = comfy.utils.common_upscale(image, target_w, target_h, "lanczos", "disabled")
+            image = image.movedim(1, -1)
+        
+        if image.shape[-1] == 4:
+            image = image[..., :3]
+
+        if len(image.shape) == 3:
+            image = image.unsqueeze(0)
+
+        latent_output = vae.encode(image)
+
+        if isinstance(latent_output, dict) and "samples" in latent_output:
+            latent = latent_output["samples"]
+        else:
+            latent = latent_output
+
+        if batch_size > 1 and latent.shape[0] == 1:
+            latent = latent.repeat(batch_size, 1, 1, 1)
+
+        return ({"samples": latent}, target_w, target_h)
+
+
+NODE_CLASS_MAPPINGS = {
+    "RS_ImageToLatent_Simplified": RS_ImageToLatent_Simplified,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "RS_ImageToLatent_Simplified": "🦊 RS Image to Latent (simplified)",
+}

__init__.py

@@ -29,7 +29,7 @@ IGNORED_MODULES: Set[str] = {'__init__.py'}
 REQUIRED_MODULES: Set[str] = set()
 
 PACKAGE_DISPLAY_NAME = "ComfyUI_RaykoStudio"
-__version__ = "0.23.0"
+__version__ = "0.23.1"
 
 def load_modules():
     print(f"🦊 {PACKAGE_DISPLAY_NAME}: Version: {__version__}")

package.json

@@ -1,6 +1,6 @@
 {
   "name": "ComfyUI_RaykoStudio",
-  "version": "0.23.0",
+  "version": "0.23.1",
   "description": "Set of custom nodes for ComfyUI providing additional image processing capabilities",
   "author": "Raykosan",
   "license": "Apache License 2.0",

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "ComfyUI_RaykoStudio"
 description = "Set of custom nodes for ComfyUI providing additional image processing capabilities"
-version = "0.23.0"
+version = "0.23.1"
 license = { file = "LICENSE" }
 dependencies = ["torch>=1.7.0", "numpy>=1.19.0", "Pillow>=8.0.0", "freetype-py>=2.5.1"]