Update app.py (#1)

- Update app.py (2b097d385d623014870a7ecb8a9e148084e000a5)


Co-authored-by: Syeda Reja <syeda-Rija20@users.noreply.huggingface.co>

app.py

@@ -425,11 +425,49 @@ def load_text_model():
     return tokenizer, model
 
 
+# @st.cache_resource(show_spinner=False)
+# def load_image_model():
+#     import os
+#     import keras  # Keras 3 explicit import
+
+#     filenames_to_try = [
+#         "image_detector_v2.keras",
+#         "image_detector_v2.h5",
+#     ]
+
+#     path = None
+#     for fname in filenames_to_try:
+#         try:
+#             path = hf_hub_download(
+#                 repo_id="syeda-Rija20/image-detector",
+#                 filename=fname
+#             )
+#             break
+#         except Exception:
+#             continue
+
+    # if path is None:
+    #     raise RuntimeError(
+    #         "Could not download image model from HuggingFace Hub. "
+    #         "Check that 'syeda-Rija20/image-detector' is public and the file exists."
+    #     )
+
+    # # Try keras 3 native load first, then tf.keras fallback
+    # try:
+    #     model = keras.saving.load_model(path, compile=False)
+    # except Exception:
+    #     try:
+    #         model = tf.keras.models.load_model(path, compile=False)
+    #     except Exception as e:
+    #         raise RuntimeError(f"Failed to load image model: {e}")
+
+    # return model
 @st.cache_resource(show_spinner=False)
 def load_image_model():
     import os
-    import keras  # Keras 3 explicit import
+    import tempfile
 
+    # Download the weights file
     filenames_to_try = [
         "image_detector_v2.keras",
         "image_detector_v2.h5",
@@ -448,20 +486,58 @@ def load_image_model():
 
     if path is None:
         raise RuntimeError(
-            "Could not download image model from HuggingFace Hub. "
-            "Check that 'syeda-Rija20/image-detector' is public and the file exists."
+            "Could not download image model from HuggingFace Hub."
         )
 
-    # Try keras 3 native load first, then tf.keras fallback
+    # ── Rebuild EfficientNetB3 architecture manually ──
+    # This bypasses the Keras version mismatch on RandomFlip data_format
     try:
-        model = keras.saving.load_model(path, compile=False)
-    except Exception:
+        import keras
+        from keras import layers
+
+        # Build the same architecture the model was trained with,
+        # WITHOUT the augmentation Sequential (not needed at inference)
+        base = keras.applications.EfficientNetB3(
+            include_top=False,
+            weights=None,           # no pretrained weights; we load them below
+            input_shape=(224, 224, 3),
+        )
+        base.trainable = True
+
+        inputs = keras.Input(shape=(224, 224, 3))
+        x = base(inputs, training=False)
+        x = layers.GlobalAveragePooling2D()(x)
+        x = layers.BatchNormalization(momentum=0.99, epsilon=0.001)(x)
+        x = layers.Dense(256, activation="relu")(x)
+        x = layers.Dropout(0.4)(x, training=False)
+        outputs = layers.Dense(1, activation="sigmoid")(x)
+
+        model = keras.Model(inputs, outputs)
+        model.load_weights(path)
+        return model
+
+    except Exception as e_rebuild:
+        # ── Last resort: patch RandomFlip then load ──
         try:
-            model = tf.keras.models.load_model(path, compile=False)
-        except Exception as e:
-            raise RuntimeError(f"Failed to load image model: {e}")
+            import keras
+            from keras.layers import RandomFlip as _RF
+
+            _orig_init = _RF.__init__
+
+            def _patched_init(self, mode="horizontal", seed=None, **kwargs):
+                kwargs.pop("data_format", None)   # strip unsupported kwarg
+                _orig_init(self, mode=mode, seed=seed, **kwargs)
+
+            _RF.__init__ = _patched_init
 
-    return model
+            model = keras.saving.load_model(path, compile=False)
+            return model
+        except Exception as e_patch:
+            raise RuntimeError(
+                f"Failed to load image model.\n"
+                f"Rebuild attempt: {e_rebuild}\n"
+                f"Patch attempt: {e_patch}"
+            )    
 
 
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