From ead0cce23bcd2d906a6362d99380312de7b55ccf Mon Sep 17 00:00:00 2001
From: kijai <40791699+kijai@users.noreply.github.com>
Date: Mon, 6 Oct 2025 15:07:08 +0300
Subject: [PATCH] Some fixes/adjustments

---
 nodes/image_nodes.py | 19 +++++++++++--------
 1 file changed, 11 insertions(+), 8 deletions(-)

diff --git a/nodes/image_nodes.py b/nodes/image_nodes.py
index e48be02..aebd49d 100644
--- a/nodes/image_nodes.py
+++ b/nodes/image_nodes.py
@@ -2476,7 +2476,7 @@ class ImageResizeKJv2:
             "optional" : {
                 "mask": ("MASK",),
                 "device": (["cpu", "gpu"],),
-                "per_batch": ("INT", { "default": 16, "min": 0, "max": 4096, "step": 1, "tooltip": "Process images in sub-batches to reduce memory usage. 0 disables sub-batching."}),
+                "per_batch": ("INT", { "default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1, "tooltip": "Process images in sub-batches to reduce memory usage. 0 disables sub-batching."}),
             },
              "hidden": {
                 "unique_id": "UNIQUE_ID",
@@ -2495,7 +2495,7 @@ Keep proportions keeps the aspect ratio of the image, by
 highest dimension.  
 """
 
-    def resize(self, image, width, height, keep_proportion, upscale_method, divisible_by, pad_color, crop_position, unique_id, device="cpu", mask=None, per_batch=16):
+    def resize(self, image, width, height, keep_proportion, upscale_method, divisible_by, pad_color, crop_position, unique_id, device="cpu", mask=None, per_batch=0):
         B, H, W, C = image.shape
 
         if device == "gpu":
@@ -2511,6 +2511,10 @@ highest dimension.
             height = H
 
         pillarbox_blur = keep_proportion == "pillarbox_blur"
+        
+        # Initialize padding variables
+        pad_left = pad_right = pad_top = pad_bottom = 0
+        
         if keep_proportion == "resize" or keep_proportion.startswith("pad") or pillarbox_blur:
             # If one of the dimensions is zero, calculate it to maintain the aspect ratio
             if width == 0 and height != 0:
@@ -2529,7 +2533,6 @@ highest dimension.
                 new_width = width
                 new_height = height
 
-            pad_left = pad_right = pad_top = pad_bottom = 0
             if keep_proportion.startswith("pad") or pillarbox_blur:
                 # Calculate padding based on position
                 if crop_position == "center":
@@ -2566,7 +2569,7 @@ highest dimension.
             height = height - (height % divisible_by)
 
         # Preflight estimate (log-only when batching is active)
-        if per_batch and B > per_batch:
+        if per_batch != 0 and B > per_batch:
             try:
                 bytes_per_elem = image.element_size()  # typically 4 for float32
                 est_total_bytes = B * height * width * C * bytes_per_elem
@@ -2582,7 +2585,7 @@ highest dimension.
             except:
                 pass
 
-        def _process_subbatch(in_image, in_mask):
+        def _process_subbatch(in_image, in_mask, pad_left, pad_right, pad_top, pad_bottom):
             # Avoid unnecessary clones; only move if needed
             out_image = in_image if in_image.device == device else in_image.to(device)
             out_mask = None if in_mask is None else (in_mask if in_mask.device == device else in_mask.to(device))
@@ -2650,8 +2653,8 @@ highest dimension.
             return out_image, out_mask
 
         # If batching disabled (per_batch==0) or batch fits, process whole batch
-        if per_batch is None or per_batch == 0 or B <= per_batch:
-            out_image, out_mask = _process_subbatch(image, mask)
+        if per_batch == 0 or B <= per_batch:
+            out_image, out_mask = _process_subbatch(image, mask, pad_left, pad_right, pad_top, pad_bottom)
         else:
             chunks = []
             mask_chunks = [] if mask is not None else None
@@ -2662,7 +2665,7 @@ highest dimension.
                 end_idx = min(start_idx + per_batch, B)
                 sub_img = image[start_idx:end_idx]
                 sub_mask = mask[start_idx:end_idx] if mask is not None else None
-                sub_out_img, sub_out_mask = _process_subbatch(sub_img, sub_mask)
+                sub_out_img, sub_out_mask = _process_subbatch(sub_img, sub_mask, pad_left, pad_right, pad_top, pad_bottom)
                 chunks.append(sub_out_img.cpu())
                 if mask is not None:
                     mask_chunks.append(sub_out_mask.cpu() if sub_out_mask is not None else None)