Update README.md

README.md

@@ -66,4 +66,36 @@ This workflow uses controlled sigma shaping, Res-2 samplers, and phased refineme
 
     CFG-induced harshness
 
-The result is clean, high-contrast outputs that scale well across portraits, fashion, cinematic scenes, and hard-surface material tests.
+The result is clean, high-contrast outputs that scale well across portraits, fashion, cinematic scenes, and hard-surface material tests.
+
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+Auto IMG Batch Caption workflow automatically generates clean, structured image captions by combining WD14 tagging, Florence-style natural language descriptions, and a custom trigger token for training consistency. The idea behind this workflow is to deliver proven results for easily (one-click) captioning datasets for training. I have made many high quality LORA from the datasets this workflow outputs.
+
+    Uses WD14 to extract high-quality tag metadata
+
+    Uses Florence to generate a natural-language image description
+
+    Injects a custom trigger token at the start of every caption
+
+    Outputs both tags + descriptive text in a single caption block
+
+    Saves captions to a user-defined folder inside ComfyUI/output
+
+
+Important Setup Note (VERY IMPORTANT)
+
+You must create a folder inside:
+
+ComfyUI/input/
+
+Example:
+
+ComfyUI/input/Captions
+
+Then select that folder in the caption loader node. 
+
+Captions follow this format:
+
+TRIGGER, wd14_tags_here,
+florence_generated_description_here