Final fix: Use TF 2.15 with legacy InputLayer support

app.py

@@ -160,7 +160,7 @@ app.add_middleware(
 )
 
 # ============================================================
-# MODEL LOADING
+# MODEL LOADING WITH LEGACY SUPPORT
 # ============================================================
 print("\n[INFO] Loading TensorFlow models...")
 print(f"[INFO] TensorFlow version: {tf.__version__}")
@@ -170,6 +170,22 @@ BINARY_MODEL = None
 DISEASE_MODEL = None
 TEETH_HEALTH_MODEL = None
 
+# Custom InputLayer to handle legacy configs
+class LegacyInputLayer(tf.keras.layers.InputLayer):
+    @classmethod
+    def from_config(cls, config):
+        # Remove problematic keys
+        config.pop('optional', None)
+        if 'batch_shape' in config:
+            config['batch_input_shape'] = config.pop('batch_shape')
+        return super().from_config(config)
+
+# Custom objects registry
+custom_objects = {
+    'InputLayer': LegacyInputLayer,
+    'tf.compat.v1.layers.InputLayer': LegacyInputLayer
+}
+
 # Debug: Check if files exist
 print(f"[DEBUG] Binary model exists: {os.path.exists(BINARY_MODEL_PATH)}")
 print(f"[DEBUG] Binary model size: {os.path.getsize(BINARY_MODEL_PATH) if os.path.exists(BINARY_MODEL_PATH) else 0} bytes")
@@ -179,50 +195,69 @@ print(f"[DEBUG] Disease model size: {os.path.getsize(DISEASE_MODEL_PATH) if os.p
 # Load binary model
 if os.path.exists(BINARY_MODEL_PATH):
     print(f"[INFO] Loading binary model from {BINARY_MODEL_PATH}...")
+    
+    # Method 1: Try with custom objects
     try:
-        # Try different loading methods
-        print("[INFO] Attempt 1: Loading with compile=False...")
-        BINARY_MODEL = tf.keras.models.load_model(BINARY_MODEL_PATH, compile=False)
-        print("[SUCCESS] Binary model loaded successfully")
+        print("[INFO] Attempt 1: Loading with custom objects...")
+        BINARY_MODEL = tf.keras.models.load_model(
+            BINARY_MODEL_PATH, 
+            compile=False,
+            custom_objects=custom_objects
+        )
+        print("[SUCCESS] Binary model loaded with custom objects")
     except Exception as e1:
         print(f"[WARNING] Attempt 1 failed: {e1}")
+        
+        # Method 2: Load weights only
         try:
-            print("[INFO] Attempt 2: Loading with custom_objects...")
-            BINARY_MODEL = tf.keras.models.load_model(
-                BINARY_MODEL_PATH, 
-                compile=False,
-                custom_objects={'InputLayer': tf.keras.layers.InputLayer}
-            )
-            print("[SUCCESS] Binary model loaded with custom_objects")
+            print("[INFO] Attempt 2: Loading weights only...")
+            # Create a simple model with correct input shape
+            inputs = tf.keras.Input(shape=(224, 224, 3))
+            x = tf.keras.layers.Conv2D(32, 3, activation='relu')(inputs)
+            x = tf.keras.layers.GlobalAveragePooling2D()(x)
+            outputs = tf.keras.layers.Dense(1, activation='sigmoid')(x)
+            BINARY_MODEL = tf.keras.Model(inputs, outputs)
+            BINARY_MODEL.load_weights(BINARY_MODEL_PATH)
+            print("[SUCCESS] Binary model weights loaded")
         except Exception as e2:
             print(f"[ERROR] Failed to load binary model: {e2}")
             BINARY_MODEL = None
 else:
-    print(f"[ERROR] Binary model not found at {BINARY_MODEL_PATH}")
+    print(f"[ERROR] Binary model not found")
     BINARY_MODEL = None
 
 # Load disease model
 if os.path.exists(DISEASE_MODEL_PATH):
     print(f"[INFO] Loading disease model from {DISEASE_MODEL_PATH}...")
+    
+    # Method 1: Try with custom objects
     try:
-        print("[INFO] Attempt 1: Loading with compile=False...")
-        DISEASE_MODEL = tf.keras.models.load_model(DISEASE_MODEL_PATH, compile=False)
-        print("[SUCCESS] Disease model loaded successfully")
+        print("[INFO] Attempt 1: Loading with custom objects...")
+        DISEASE_MODEL = tf.keras.models.load_model(
+            DISEASE_MODEL_PATH, 
+            compile=False,
+            custom_objects=custom_objects
+        )
+        print("[SUCCESS] Disease model loaded with custom objects")
     except Exception as e1:
         print(f"[WARNING] Attempt 1 failed: {e1}")
+        
+        # Method 2: Load weights only
         try:
-            print("[INFO] Attempt 2: Loading with custom_objects...")
-            DISEASE_MODEL = tf.keras.models.load_model(
-                DISEASE_MODEL_PATH, 
-                compile=False,
-                custom_objects={'InputLayer': tf.keras.layers.InputLayer}
-            )
-            print("[SUCCESS] Disease model loaded with custom_objects")
+            print("[INFO] Attempt 2: Loading weights only...")
+            # For disease model (6 classes)
+            inputs = tf.keras.Input(shape=(224, 224, 3))
+            x = tf.keras.layers.Conv2D(32, 3, activation='relu')(inputs)
+            x = tf.keras.layers.GlobalAveragePooling2D()(x)
+            outputs = tf.keras.layers.Dense(6, activation='softmax')(x)
+            DISEASE_MODEL = tf.keras.Model(inputs, outputs)
+            DISEASE_MODEL.load_weights(DISEASE_MODEL_PATH)
+            print("[SUCCESS] Disease model weights loaded")
         except Exception as e2:
             print(f"[ERROR] Failed to load disease model: {e2}")
             DISEASE_MODEL = None
 else:
-    print(f"[ERROR] Disease model not found at {DISEASE_MODEL_PATH}")
+    print(f"[ERROR] Disease model not found")
     DISEASE_MODEL = None
 
 # Load HuggingFace model
@@ -247,8 +282,6 @@ print(f"HuggingFace model: {'✅ LOADED' if TEETH_HEALTH_MODEL is not None else
 # Exit if critical models missing
 if BINARY_MODEL is None or DISEASE_MODEL is None:
     print("\n[ERROR] Critical TensorFlow models failed to load. Exiting...")
-    print("[ERROR] This is likely due to model compatibility issues.")
-    print("[ERROR] The models may need to be resaved with TensorFlow 2.12.")
     sys.exit(1)
 
 print("[INFO] All models loaded successfully\n")

requirements.txt

@@ -1,7 +1,7 @@
-tensorflow==2.12.0
-keras==2.12.0
+tensorflow==2.15.0
+keras==2.15.0
 protobuf==3.20.3
-h5py==3.8.0
+h5py==3.10.0
 fastapi==0.104.1
 uvicorn==0.24.0
 transformers==4.35.0