Use one counter across full save path

__init__.py

@@ -1,7 +1,7 @@
 from .dumas_image_nodes import (
     NODE_CLASS_MAPPINGS as IMAGE_NODE_CLASS_MAPPINGS,
     NODE_DISPLAY_NAME_MAPPINGS as IMAGE_NODE_DISPLAY_NAME_MAPPINGS,
-    _next_counter,
+    _next_counter_for_relative_path,
     resolve_serve_token,
 )
 from .dumas_json_nodes import (
@@ -102,10 +102,10 @@ try:
             parts = [part for part in name.replace("\\", "/").split("/") if part]
             if not parts:
                 return 1, ""
-            frame_dir = os.path.join(base, *parts[:-1])
+            relative_template = "/".join(parts)
-            counter = _next_counter(frame_dir, parts[-1])
+            counter = _next_counter_for_relative_path(base, relative_template)
-            resolved_name = parts[-1].replace("%counter%", str(counter).zfill(digits))
+            resolved_relative = relative_template.replace("%counter%", str(counter).zfill(digits))
-            return counter, "/".join(parts[:-1] + [resolved_name])
+            return counter, resolved_relative
 
         try:
             loop = asyncio.get_running_loop()

dumas_image_nodes.py

@@ -136,6 +136,20 @@ def _next_counter(directory, filename_template):
     return highest + 1
 
 
+def _next_counter_for_relative_path(base_directory, relative_template):
+    os.makedirs(base_directory, exist_ok=True)
+    if "%counter%" not in relative_template:
+        return 1
+
+    counter = 1
+    while True:
+        candidate = relative_template.replace("%counter%", str(counter).zfill(3))
+        full_path = os.path.join(base_directory, *[part for part in candidate.split("/") if part])
+        if not os.path.exists(full_path):
+            return counter
+        counter += 1
+
+
 def _build_pnginfo(prompt=None, extra_pnginfo=None):
     try:
         pnginfo = Image.PngImagePlugin.PngInfo()
@@ -362,11 +376,13 @@ class DumasSaveImageNode:
         for batch_index in range(images.shape[0]):
             frame_pattern = resolved_pattern.replace("%batch_num%", str(batch_index))
             frame_parts = [part for part in frame_pattern.split("/") if part]
-            sub_dirs = frame_parts[:-1]
+            relative_template = "/".join(frame_parts[:-1] + [((frame_parts[-1] if frame_parts else "image_%counter%") + extension)])
-            filename_template = (frame_parts[-1] if frame_parts else "image_%counter%") + extension
+            counter = _next_counter_for_relative_path(target_dir, relative_template)
+            resolved_relative = relative_template.replace("%counter%", str(counter).zfill(3))
+            resolved_parts = [part for part in resolved_relative.split("/") if part]
+            sub_dirs = resolved_parts[:-1]
+            filename = resolved_parts[-1] if resolved_parts else f"image_{str(counter).zfill(3)}{extension}"
             frame_dir = os.path.join(target_dir, *sub_dirs)
-            counter = _next_counter(frame_dir, filename_template)
-            filename = filename_template.replace("%counter%", str(counter).zfill(3))
             image = _tensor_image_to_pil_image(images[batch_index : batch_index + 1])
             full_path = os.path.join(frame_dir, filename)
 

tests/test_dumas_image_nodes.py

@@ -204,6 +204,23 @@ class DumasImageNodeTests(unittest.TestCase):
         saved_names = [os.path.basename(path) for path, _args, _kwargs in FakePILImage.saved_paths]
         self.assertEqual(saved_names, ["counter_001.png", "counter_002.png"])
 
+    def test_save_image_uses_same_counter_for_folder_and_filename(self):
+        node = self.image_nodes.DumasSaveImageNode()
+        image = FakeTensorBatch()
+
+        node.save_images(
+            images=image,
+            folder=self.temp_dir,
+            pattern="Char%counter%/Char%counter%",
+            format="png",
+            quality=100,
+            embed_workflow=False,
+            save_on_run=True,
+        )
+
+        saved_path = FakePILImage.saved_paths[0][0].replace("\\", "/")
+        self.assertTrue(saved_path.endswith("/Char001/Char001.png"))
+
     def test_save_image_returns_ui_entries_for_output_folder(self):
         node = self.image_nodes.DumasSaveImageNode()
         image = FakeTensorBatch()