Add more commenting for header and sections

app.py

@@ -1,3 +1,19 @@
+# ==============================================================================
+# Josh Guimond
+# Unit 8 Assignment: End-to-End AI Solution Implementation
+# ARIN 460
+# 12/03/2025
+
+# Description: This script implements a multimodal AI web app using Gradio to
+# run two image captioning models, a text “vibe” classifier, and NLP metrics on
+# uploaded images, allowing direct comparison of model captions to ground-truth 
+# descriptions.
+# ==============================================================================
+
+# ==============================================================================
+# SECTION 1: SETUP & INSTALLATIONS
+# ==============================================================================
+# Install libraries
 import gradio as gr
 from transformers import pipeline, AutoTokenizer, AutoModelForImageTextToText
 from sentence_transformers import SentenceTransformer, util
@@ -5,12 +21,16 @@ import evaluate
 import warnings
 import logging
 
-# --- 0. Setup & Warning Suppression ---
 # Filter out the "FutureWarning" and "UserWarning" to keep the console clean
 warnings.filterwarnings("ignore", category=FutureWarning)
 warnings.filterwarnings("ignore", category=UserWarning)
 logging.getLogger("transformers").setLevel(logging.ERROR)
 
+
+# ==============================================================================
+# SECTION 2: LOAD MODELS
+# ==============================================================================
+
 # --- 1. Load Image Captioning Models ---
 
 # Model 1: BLIP (Base)
@@ -42,7 +62,11 @@ rouge = evaluate.load("rouge")
 # These cover: Peaceful dog, Sad funeral, Happy kids, Angry man, Scared people, Fighting tigers
 VIBE_LABELS = ["Peaceful/Calm", "Happy/Joy", "Sad/Sorrow", "Angry/Upset", "Fear/Scared", "Action/Violence"]
 
-# --- 3. Analysis Function ---
+# ==============================================================================
+# SECTION 3: ANALYSIS FUNCTIONS
+# ==============================================================================
+
+# --- Analysis Function ---
 def analyze_image(image, ground_truth):
     
     # -- A. Generate Captions --
@@ -112,7 +136,9 @@ def analyze_image(image, ground_truth):
     
     return out1, out2, stats
 
-# --- 4. Interface ---
+# ==============================================================================
+# SECTION 4: GRADIO INTERFACE
+# ==============================================================================
 
 # Define Inputs
 image_input = gr.Image(type="pil", label="Upload Image")