Update app.py

app.py

@@ -6,7 +6,7 @@ from shapely.geometry import box as shapely_box, Polygon
 from shapely.ops import unary_union
 import mediapipe as mp
 from collections import defaultdict
-from concurrent.futures import ThreadPoolExecutor, as_completed
+from concurrent.futures import ThreadPoolExecutor, as_completed, TimeoutError
 
 # -------------------- CONFIG --------------------
 model_paths = {
@@ -160,54 +160,60 @@ def analyze():
 
         img_h, img_w = img.shape[:2]
 
-        # -------------------- FACE DETECTION --------------------
-        rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-        result = face_mesh.process(rgb_img)
-
-        face_polygon = None
-        face_area = 0
-        if result.multi_face_landmarks:
-            for landmarks in result.multi_face_landmarks:
-                points = np.array([
-                    [int(lm.x * img_w), int(lm.y * img_h)]
-                    for lm in landmarks.landmark
-                ])
-                hull = cv2.convexHull(points)
-                face_area = cv2.contourArea(hull)
-                face_polygon = Polygon(hull.reshape(-1, 2))
-                break
-        else:
-            return jsonify({"success": False, "analysis": [], "error": "No face detected."}), 400
-
-        # -------------------- RUN MODELS --------------------
-        combined_percentages = {}
-        with ThreadPoolExecutor() as executor:
-            futures = {
-                executor.submit(run_model, model_name, model, img, face_polygon, face_area): model_name
-                for model_name, model in models.items()
-            }
-            for future in as_completed(futures):
-                skin_percentages = future.result()
-                combined_percentages.update(skin_percentages)
-
-        final_percentages = normalize_and_merge(combined_percentages)
-
-        # ✅ Merge wrinkles + forehead
-        wrinkle_value = final_percentages.get("wrinkles", 0.0) + final_percentages.get("forehead", 0.0)
-        final_percentages["wrinkles"] = round(wrinkle_value, 2)
-        if "forehead" in final_percentages:
-            final_percentages.pop("forehead")
-
-        # -------------------- ADD SKIN TYPE --------------------
-        skin_type_result = detect_skin_type_from_image(img)
-
-        # -------------------- FORMAT RESPONSE --------------------
-        analysis_list = [
-            f"{cls_name.upper()}: {value}%" for cls_name, value in final_percentages.items()
-        ]
-        analysis_list.append(f"SKIN TYPE: {skin_type_result}")
-
-        return jsonify({"success": True, "analysis": ["\n".join(analysis_list)]})
+        # -------------------- TIME-LIMITED ANALYSIS --------------------
+        def full_analysis():
+            # FACE DETECTION
+            rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+            result = face_mesh.process(rgb_img)
+
+            face_polygon = None
+            face_area = 0
+            if result.multi_face_landmarks:
+                for landmarks in result.multi_face_landmarks:
+                    points = np.array([[int(lm.x * img_w), int(lm.y * img_h)] for lm in landmarks.landmark])
+                    hull = cv2.convexHull(points)
+                    face_area = cv2.contourArea(hull)
+                    face_polygon = Polygon(hull.reshape(-1, 2))
+                    break
+            else:
+                raise ValueError("No face detected.")
+
+            # RUN MODELS
+            combined_percentages = {}
+            with ThreadPoolExecutor() as executor:
+                futures = {
+                    executor.submit(run_model, model_name, model, img, face_polygon, face_area): model_name
+                    for model_name, model in models.items()
+                }
+                for future in as_completed(futures):
+                    skin_percentages = future.result()
+                    combined_percentages.update(skin_percentages)
+
+            final_percentages = normalize_and_merge(combined_percentages)
+
+            # MERGE WRINKLES + FOREHEAD
+            wrinkle_value = final_percentages.get("wrinkles", 0.0) + final_percentages.get("forehead", 0.0)
+            final_percentages["wrinkles"] = round(wrinkle_value, 2)
+            if "forehead" in final_percentages:
+                final_percentages.pop("forehead")
+
+            # SKIN TYPE
+            skin_type_result = detect_skin_type_from_image(img)
+
+            # FORMAT RESPONSE
+            analysis_list = [f"{cls_name.upper()}: {value}%" for cls_name, value in final_percentages.items()]
+            analysis_list.append(f"SKIN TYPE: {skin_type_result}")
+
+            return {"success": True, "analysis": ["\n".join(analysis_list)]}
+
+        # -------------------- RUN WITH 60 SEC TIMEOUT --------------------
+        with ThreadPoolExecutor(max_workers=1) as executor:
+            future = executor.submit(full_analysis)
+            try:
+                result = future.result(timeout=60)  # 60-second limit
+                return jsonify(result)
+            except TimeoutError:
+                return jsonify({"success": False, "analysis": [], "error": "Processing timeout (60 sec)."}), 504
 
     except Exception as e:
         return jsonify({"success": False, "analysis": [], "error": str(e)}), 500