Update app.py

app.py

@@ -9,6 +9,12 @@ import tensorflow as tf
 from tensorflow.keras.models import load_model
 from tensorflow.keras.preprocessing.image import load_img, img_to_array
 
+# Import all layers used in EfficientNet and our custom head to patch them
+from tensorflow.keras.layers import (
+    Dense, GlobalAveragePooling2D, Dropout, Conv2D, BatchNormalization, 
+    Activation, DepthwiseConv2D, Rescaling, ZeroPadding2D, Add, Multiply, InputLayer
+)
+
 app = Flask(__name__)
 
 # -------------------- CONFIG --------------------
@@ -21,6 +27,35 @@ os.makedirs(UPLOAD_FOLDER, exist_ok=True)
 MODEL = None
 LOAD_ERROR = None  # Store the specific reason for failure
 
+# -------------------- COMPATIBILITY FIX --------------------
+# This function dynamically creates a fixed version of any Keras layer
+# that ignores the Keras 3 specific arguments (like quantization_config)
+# allowing models saved in new versions to load in older environments.
+def fix_layer_config(cls):
+    class FixedLayer(cls):
+        def __init__(self, *args, **kwargs):
+            # Remove Keras 3 arguments not supported in Keras 2
+            kwargs.pop('quantization_config', None)
+            kwargs.pop('glitch_filter', None) 
+            super().__init__(*args, **kwargs)
+    return FixedLayer
+
+# Apply the fix to all layers likely to appear in EfficientNet
+CUSTOM_OBJECTS = {
+    'Dense': fix_layer_config(Dense),
+    'Dropout': fix_layer_config(Dropout),
+    'GlobalAveragePooling2D': fix_layer_config(GlobalAveragePooling2D),
+    'Conv2D': fix_layer_config(Conv2D),
+    'BatchNormalization': fix_layer_config(BatchNormalization),
+    'Activation': fix_layer_config(Activation),
+    'DepthwiseConv2D': fix_layer_config(DepthwiseConv2D),
+    'Rescaling': fix_layer_config(Rescaling),
+    'ZeroPadding2D': fix_layer_config(ZeroPadding2D),
+    'Add': fix_layer_config(Add),
+    'Multiply': fix_layer_config(Multiply),
+    'InputLayer': fix_layer_config(InputLayer)
+}
+
 # -------------------- LOAD MODEL --------------------
 def init_model():
     global MODEL, LOAD_ERROR
@@ -30,7 +65,8 @@ def init_model():
     if os.path.exists(MODEL_FILE):
         print(f"[INIT] Model found: {MODEL_FILE}")
         try:
-            MODEL = load_model(MODEL_FILE)
+            # We pass the custom_objects dictionary to handle the version mismatch
+            MODEL = load_model(MODEL_FILE, custom_objects=CUSTOM_OBJECTS)
             print("[INIT] Model loaded successfully.")
         except Exception as e:
             print(f"[ERROR] Failed to load model: {e}")