Update app.py

app.py

@@ -27,28 +27,31 @@ def get_models():
     return model_swelling, model_redness, model_bleeding
 
 
-# --- Helpers ---
+# =========================================================
+# Helper functions
+# =========================================================
 def preprocess(image):
+    """Resize, fix orientation, improve contrast."""
     if isinstance(image, np.ndarray):
         image = Image.fromarray(image)
 
     image = ImageOps.exif_transpose(image).convert("RGB")
 
-    # Resize if needed
+    # Resize if too large
     w, h = image.size
     max_dim = max(w, h)
     if max_dim > 1024:
         scale = 1024 / max_dim
         image = image.resize((int(w * scale), int(h * scale)), Image.LANCZOS)
 
-    # Light contrast boost
+    # Slight contrast enhancement
     image = ImageEnhance.Contrast(image).enhance(1.05)
 
     return image
 
 
 def np_to_base64(img_np, format="JPEG"):
-    """Convert numpy RGB image to Base64 string."""
+    """Convert numpy RGB image to Base64."""
     pil_img = Image.fromarray(img_np)
     buffer = io.BytesIO()
     pil_img.save(buffer, format=format)
@@ -56,11 +59,13 @@ def np_to_base64(img_np, format="JPEG"):
 
 
 def base64_to_pil(b64_str):
-    """Convert Base64 string back to PIL image (for Gradio display)."""
+    """Convert Base64 string to PIL image."""
     return Image.open(io.BytesIO(base64.b64decode(b64_str)))
 
 
-# --- Main detection ---
+# =========================================================
+# Main detection function
+# =========================================================
 def detect_gingivitis(image, conf=0.25, iou=0.5):
     try:
         if image is None:
@@ -69,7 +74,7 @@ def detect_gingivitis(image, conf=0.25, iou=0.5):
         # Load models (only once)
         sw_model, rd_model, bl_model = get_models()
 
-        # Preprocess image
+        # Preprocess
         image = preprocess(image)
 
         # Run detections
@@ -77,7 +82,7 @@ def detect_gingivitis(image, conf=0.25, iou=0.5):
         rd_res = rd_model.predict(image, conf=conf, iou=iou)
         bl_res = bl_model.predict(image, conf=conf, iou=iou)
 
-        # Convert to images
+        # Convert YOLO output → numpy → PIL
         img_sw = sw_res[0].plot(labels=False)[:, :, ::-1]
         img_rd = rd_res[0].plot(labels=False)[:, :, ::-1]
         img_bl = bl_res[0].plot(labels=False)[:, :, ::-1]
@@ -86,7 +91,7 @@ def detect_gingivitis(image, conf=0.25, iou=0.5):
         rd_pil = base64_to_pil(np_to_base64(img_rd))
         bl_pil = base64_to_pil(np_to_base64(img_bl))
 
-        # Determine diagnosis
+        # Diagnosis logic
         has_sw = len(sw_res[0].boxes) > 0
         has_rd = len(rd_res[0].boxes) > 0
         has_bl = len(bl_res[0].boxes) > 0
@@ -103,12 +108,12 @@ def detect_gingivitis(image, conf=0.25, iou=0.5):
         return [sw_pil, rd_pil, bl_pil, diagnosis]
 
     except Exception as e:
-        # Catch all errors and return a friendly message
         return [None, None, None, f"❌ Error during processing: {str(e)}"]
 
 
-
-# --- Gradio Interface ---
+# =========================================================
+# Gradio Interface
+# =========================================================
 interface = gr.Interface(
     fn=detect_gingivitis,
     inputs=[
@@ -125,6 +130,7 @@ interface = gr.Interface(
     title="Gingivitis Detection"
 )
 
+
 # =========================================================
 # Warm-start: preload models on startup
 # =========================================================
@@ -132,6 +138,9 @@ print("🔥 Preloading models to reduce Render cold start...")
 get_models()
 print("✅ Gingivitis models ready")
 
-# interface.launch()
+
+# =========================================================
+# Start server
+# =========================================================
 if __name__ == "__main__":
-    interface.launch(server_name="0.0.0.0", server_port=7860, show_error=True)
+    interface.launch(server_name="0.0.0.0", server_port=7860, show_error=True)