Use single-eye

app/visualization.py

@@ -274,7 +274,7 @@ def format_view_weights_html(analysis: ViewAnalysis) -> str:
     view_info = {
         "whole": ("Whole Image", "#4CAF50"),  # green
         "face": ("Face", "#2196F3"),  # blue
-        "eyes": ("Eyes", "#FF9800"),  # orange
+        "eyes": ("Eye", "#FF9800"),  # orange (single-eye crop)
     }
 
     html_parts = ['<div style="font-family: sans-serif; padding: 10px;">']

webui_gradio.py

@@ -253,7 +253,7 @@ def load_all(ckpt_path: str, proto_path: str, device: str) -> str:
     APP_STATE.db = db
     APP_STATE.proto_path = proto_path
 
-    # initialize view extractor (whole -> face/eyes) with defaults
+    # initialize view extractor (whole -> face/eye) with defaults
     try:
         cfg = ExtractorCfg(
             yolo_dir=ROOT / "yolov5_anime",
@@ -298,7 +298,7 @@ def classify_and_analyze(
         return ("❌ Provide a whole image.",) + empty_result[1:]
 
     try:
-        # Extract face and eyes
+        # Extract face and eye
         face_pil = None
         eye_pil = None
         if ex is not None:
@@ -434,7 +434,7 @@ def add_prototype(
     k_prototypes = max(1, int(k_prototypes))
     n_triplets = max(1, int(n_triplets))
 
-    # Step 1: Extract whole/face/eyes from all uploaded images
+    # Step 1: Extract whole/face/eye from all uploaded images
     wholes: List[Image.Image] = []
     faces: List[Image.Image] = []
     eyes_list: List[Image.Image] = []
@@ -449,7 +449,7 @@ def add_prototype(
 
             wholes.append(im)
 
-            # Extract face and eyes
+            # Extract face and eye
             if ex is not None:
                 rgb = np.array(im.convert("RGB"))
                 face_rgb, eyes_rgb = ex.extract(rgb)
@@ -552,13 +552,13 @@ def build_ui() -> gr.Blocks:
             with gr.Row():
                 gcam_whole = gr.Image(label="Whole Image", type="pil")
                 gcam_face = gr.Image(label="Face", type="pil")
-                gcam_eye = gr.Image(label="Eyes", type="pil")
+                gcam_eye = gr.Image(label="Eye", type="pil")
 
             # Extracted views
             gr.Markdown("### 👁️ Auto-Extracted Views")
             with gr.Row():
                 face_prev = gr.Image(label="Detected Face", type="pil")
-                eye_prev = gr.Image(label="Detected Eyes", type="pil")
+                eye_prev = gr.Image(label="Detected Eye", type="pil")
 
             run_btn.click(
                 classify_and_analyze,
@@ -571,8 +571,8 @@ def build_ui() -> gr.Blocks:
                 "### ⚠️ Temporary Prototypes Only\n"
                 "Add prototypes using random triplet combinations and K-means clustering (same as eval process).\n"
                 "1. Upload multiple whole images\n"
-                "2. Face and eyes are auto-extracted from each\n"
-                "3. Random triplets (whole + face + eyes) are created\n"
+                "2. Face and eye are auto-extracted from each\n"
+                "3. Random triplets (whole + face + eye) are created\n"
                 "4. K-means clustering creates K prototype centers\n\n"
                 "**These prototypes are session-only** — lost when the Space restarts."
             )