fix

api_routes.py

@@ -63,6 +63,47 @@ if DEEPFACE_AVAILABLE:
     try:
         from deepface import DeepFace
         deepface_module = DeepFace
+        try:
+            from deepface.models import FacialRecognition as df_facial_recognition
+            DeepFaceModel = getattr(df_facial_recognition, "Model", None)
+            _original_forward = df_facial_recognition.FacialRecognition.forward
+
+            def _patched_forward(self, img):
+                """
+                兼容Keras 3 / tf_keras 返回SymbolicTensor的情况，必要时退回predict。
+                """
+                if DeepFaceModel is None or not isinstance(self.model, DeepFaceModel):
+                    return _original_forward(self, img)
+
+                if img.ndim == 3:
+                    img = np.expand_dims(img, axis=0)
+
+                if img.ndim == 4 and img.shape[0] == 1:
+                    try:
+                        outputs = self.model(img, training=False)
+                        embeddings = outputs.numpy()
+                    except Exception:
+                        # Keras 3 调用 self.model(...) 可能返回SymbolicTensor，退回 predict
+                        embeddings = self.model.predict(img, verbose=0)
+                elif img.ndim == 4 and img.shape[0] > 1:
+                    embeddings = self.model.predict_on_batch(img)
+                else:
+                    raise ValueError(
+                        f"Input image must be (1, X, X, 3) shaped but it is {img.shape}"
+                    )
+
+                embeddings = np.asarray(embeddings)
+                if embeddings.ndim == 0:
+                    raise ValueError("Embeddings output is empty.")
+
+                if embeddings.shape[0] == 1:
+                    return embeddings[0].tolist()
+                return embeddings.tolist()
+
+            df_facial_recognition.FacialRecognition.forward = _patched_forward
+            logger.info("Patched DeepFace FacialRecognition.forward for SymbolicTensor compatibility")
+        except Exception as patch_exc:
+            logger.warning(f"Failed to patch DeepFace forward method: {patch_exc}")
         logger.info("DeepFace module imported successfully")
     except ImportError as e:
         logger.error(f"Failed to import DeepFace: {e}")