From 646cf6600a6633f511deb871135ad058a297d257 Mon Sep 17 00:00:00 2001
From: Mihail Karaev <karaevmihail@gmail.com>
Date: Tue, 13 Jan 2026 12:53:27 +0000
Subject: [PATCH] Fix resize in I2I Node

---
 comfy_extras/nodes_kandinsky5.py | 38 +++++---------------------------
 1 file changed, 5 insertions(+), 33 deletions(-)

diff --git a/comfy_extras/nodes_kandinsky5.py b/comfy_extras/nodes_kandinsky5.py
index 3ac1238ab..22edeb3f7 100644
--- a/comfy_extras/nodes_kandinsky5.py
+++ b/comfy_extras/nodes_kandinsky5.py
@@ -64,29 +64,27 @@ class Kandinsky5ImageToImage(io.ComfyNode):
             node_id="Kandinsky5ImageToImage",
             category="image",
             inputs=[
-                io.Conditioning.Input("positive"),
-                io.Conditioning.Input("negative"),
                 io.Vae.Input("vae"),
                 io.Int.Input("batch_size", default=1, min=1, max=4096),
                 io.Image.Input("start_image"),
             ],
             outputs=[
-                io.Conditioning.Output(display_name="positive"),
-                io.Conditioning.Output(display_name="negative"),
                 io.Latent.Output(display_name="latent", tooltip="Empty video latent"),
+                io.Image.Output("resized_image"),
             ],
         )
 
     @classmethod
-    def execute(cls, positive, negative, vae, batch_size, start_image) -> io.NodeOutput:
+    def execute(cls, vae, batch_size, start_image) -> io.NodeOutput:
         height, width = start_image.shape[1:-1]
-        
         available_res = [(1024, 1024), (640, 1408), (1408, 640), (768, 1280), (1280, 768), (896, 1152), (1152, 896)]
         nearest_index = torch.argmin(torch.Tensor([abs((w / h) - (width / height))for (w, h) in available_res]))
         nw, nh = available_res[nearest_index]
         scale_factor = min(height / nh, width / nw)
         start_image = start_image.permute(0,3,1,2)
         start_image = F.resize(start_image, (int(height / scale_factor), int(width / scale_factor)))
+
+        height, width = start_image.shape[-2:]
         start_image = F.crop(
             start_image,
             (height - nh) // 2,
@@ -94,11 +92,10 @@ class Kandinsky5ImageToImage(io.ComfyNode):
             nh,
             nw,
         )
-        print(start_image.shape)
         start_image = start_image.permute(0,2,3,1)
         encoded = vae.encode(start_image[:, :, :, :3])
         out_latent = {"samples": encoded.repeat(batch_size, 1, 1, 1)}
-        return io.NodeOutput(positive, negative, out_latent)
+        return io.NodeOutput(out_latent, start_image)
     
 
 def adaptive_mean_std_normalization(source, reference, clump_mean_low=0.3, clump_mean_high=0.35, clump_std_low=0.35, clump_std_high=0.5):
@@ -147,35 +144,11 @@ class NormalizeVideoLatentStart(io.ComfyNode):
         s["samples"] = samples
         return io.NodeOutput(s)
 
-
 class CLIPTextEncodeKandinsky5(io.ComfyNode):
     @classmethod
     def define_schema(cls):
         return io.Schema(
             node_id="CLIPTextEncodeKandinsky5",
-            category="advanced/conditioning/kandinsky5",
-            inputs=[
-                io.Clip.Input("clip"),
-                io.String.Input("clip_l", multiline=True, dynamic_prompts=True),
-                io.String.Input("qwen25_7b", multiline=True, dynamic_prompts=True),
-            ],
-            outputs=[
-                io.Conditioning.Output(),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, clip, clip_l, qwen25_7b) -> io.NodeOutput:
-        tokens = clip.tokenize(clip_l)
-        tokens["qwen25_7b"] = clip.tokenize(qwen25_7b)["qwen25_7b"]
-
-        return io.NodeOutput(clip.encode_from_tokens_scheduled(tokens))
-
-class TextEncodeQwenKandinskyI2I(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="TextEncodeQwenKandinskyI2I",
             category="advanced/conditioning",
             inputs=[
                 io.Clip.Input("clip"),
@@ -200,7 +173,6 @@ class Kandinsky5Extension(ComfyExtension):
             Kandinsky5ImageToImage,
             NormalizeVideoLatentStart,
             CLIPTextEncodeKandinsky5,
-            TextEncodeQwenKandinskyI2I,
         ]
 
 async def comfy_entrypoint() -> Kandinsky5Extension: