tweaks

nodes/FL_ImageSelector.py

@@ -16,17 +16,30 @@ class FL_ImageSelector:
     CATEGORY = "🏵️Fill Nodes/Image"
 
     def select_images(self, images, indices):
+        # Get batch size for "last" keyword processing
+        batch_size = images.shape[0]
+        
         # Parse the indices string
         try:
-            # Split by comma and convert to integers
-            index_list = [int(idx.strip()) for idx in indices.split(',') if idx.strip()]
+            # Split by comma and process each index
+            index_parts = [idx.strip() for idx in indices.split(',') if idx.strip()]
+            index_list = []
+            
+            for idx_str in index_parts:
+                if idx_str.lower() == "last":
+                    # Replace "last" with the last index (batch_size - 1)
+                    if batch_size > 0:
+                        index_list.append(batch_size - 1)
+                else:
+                    # Convert to integer
+                    index_list.append(int(idx_str))
+                    
         except ValueError:
-            print("Error: Indices must be comma-separated integers")
+            print("Error: Indices must be comma-separated integers or 'last'")
             # Return the original batch if parsing fails
             return (images,)
 
         # Validate indices
-        batch_size = images.shape[0]
         valid_indices = [idx for idx in index_list if 0 <= idx < batch_size]
         
         if not valid_indices:

nodes/FL_Image_Randomizer.py

@@ -17,9 +17,9 @@ class FL_ImageRandomizer:
             }
         }
 
-    RETURN_TYPES = ("IMAGE", "PATH", "IMAGE")
-    RETURN_NAMES = ("image_batch", "selected_path", "image_list")
-    OUTPUT_IS_LIST = (False, False, True)
+    RETURN_TYPES = ("IMAGE", "PATH", "IMAGE", "STRING")
+    RETURN_NAMES = ("image_batch", "selected_path", "image_list", "filename")
+    OUTPUT_IS_LIST = (False, False, True, False)
     FUNCTION = "select_media"
     CATEGORY = "🏵️Fill Nodes/Image"
 
@@ -29,10 +29,12 @@ class FL_ImageRandomizer:
         
         if mode == "Image":
             image_tensor, selected_path = self.select_image_data(directory_path, seed, search_subdirectories)
-            return (image_tensor, selected_path, [image_tensor])
+            filename = os.path.basename(selected_path)
+            return (image_tensor, selected_path, [image_tensor], filename)
         else:  # Video mode
             frames_tensor, selected_path = self.select_video_data(directory_path, seed, search_subdirectories)
-            return (frames_tensor, selected_path, [frames_tensor]) # Video frames are already a batch, but we wrap in list for consistency
+            filename = os.path.basename(selected_path)
+            return (frames_tensor, selected_path, [frames_tensor], filename) # Video frames are already a batch, but we wrap in list for consistency
     
     def select_image_data(self, directory_path, seed, search_subdirectories=False):
         images = self.load_files(directory_path, search_subdirectories, file_type="image")

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui_fill-nodes"
 description = "Fill-Nodes is a versatile collection of custom nodes for ComfyUI that extends functionality across multiple domains. Features include advanced image processing (pixelation, slicing, masking), visual effects generation (glitch, halftone, pixel art), comprehensive file handling (PDF creation/extraction, Google Drive integration), AI model interfaces (GPT, DALL-E, Hugging Face), utility nodes for workflow enhancement, and specialized tools for video processing, captioning, and batch operations. The pack provides both practical workflow solutions and creative tools within a unified node collection."
-version = "1.5.9"
+version = "1.6.0"
 license = "LICENSE"
 dependencies = ["diffusers", "librosa", "sounddevice", "glitch_this", "PyOpenGL", "glfw", "scipy>=1.13.1", "requests", "aiohttp", "moviepy", "matplotlib", "reportlab", "openai", "PyPDF2", "pdf2image", "PyMuPDF", "reportlab", "PyPDF2", "ollama", "kornia", "opencv-python", "gdown", "open_clip_torch", "google-genai"]