Verify embedding change2

app.py

@@ -171,113 +171,17 @@ async def extract_features(file: UploadFile = File(...)):
             detail=f"Internal server error: {str(e)}"
         )
 
-# @app.post("/verify-with-embedding")
-# async def verify_with_embedding(
-#     file: UploadFile = File(..., description="New video file to verify"),
-#     stored_embedding: List[float] = Body(..., description="Stored embedding from database"),
-#     threshold: float = Body(0.8, description="Similarity threshold (0.0-1.0)")
-# ):
-#     """
-#     Verify a new video against a stored embedding from database
-    
-#     - **file**: New video file to verify
-#     - **stored_embedding**: Pre-existing embedding array from database
-#     - **threshold**: Similarity threshold (default: 0.8)
-#     - **returns**: Similarity score and verification result
-#     """
-#     try:
-#         # Validate file type
-#         if not file.content_type.startswith('video/') and not file.filename.lower().endswith(('.mp4', '.avi', '.mov', '.mkv')):
-#             raise HTTPException(
-#                 status_code=400, 
-#                 detail="Only video files are supported (mp4, avi, mov, mkv)"
-#             )
-
-#         # Validate stored embedding
-#         if not stored_embedding or len(stored_embedding) != 768:
-#             raise HTTPException(
-#                 status_code=400,
-#                 detail="Stored embedding must be a 768-dimensional array"
-#             )
-
-#         # Validate threshold
-#         if not 0.0 <= threshold <= 1.0:
-#             raise HTTPException(
-#                 status_code=400,
-#                 detail="Threshold must be between 0.0 and 1.0"
-#             )
-
-#         # Convert stored embedding to numpy array
-#         try:
-#             stored_emb = np.array(stored_embedding, dtype=np.float32)
-#         except Exception as e:
-#             raise HTTPException(
-#                 status_code=400,
-#                 detail=f"Invalid embedding format: {str(e)}"
-#             )
-
-#         # Create temporary file for new video
-#         with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as tmp:
-#             content = await file.read()
-#             if len(content) == 0:
-#                 raise HTTPException(status_code=400, detail="Video file is empty")
-#             tmp.write(content)
-#             tmp_path = tmp.name
-
-#         try:
-#             # Extract features from new video
-#             new_emb = extract_vit_features_from_video(tmp_path)
-
-#             if new_emb is None:
-#                 raise HTTPException(
-#                     status_code=400, 
-#                     detail="Could not process the video or no frames extracted"
-#                 )
-
-#             # Calculate cosine similarity
-#             similarity = calculate_cosine_similarity(stored_emb, new_emb)
-            
-#             # Determine result
-#             result = "same_person" if similarity > threshold else "different_person"
-
-#             return {
-#                 "success": True,
-#                 "similarity": round(similarity, 4),
-#                 "threshold_used": threshold,
-#                 "result": result,
-#                 "message": "Verification completed successfully",
-#                 "comparison": {
-#                     "stored_embedding_length": len(stored_emb),
-#                     "new_embedding_length": len(new_emb)
-#                 }
-#             }
-
-#         finally:
-#             # Cleanup temp file
-#             if os.path.exists(tmp_path):
-#                 os.remove(tmp_path)
-
-#     except HTTPException:
-#         raise
-#     except Exception as e:
-#         logger.error(f"Verify with embedding error: {str(e)}")
-#         raise HTTPException(
-#             status_code=500, 
-#             detail=f"Internal server error: {str(e)}"
-#         )
-
-
 @app.post("/verify-with-embedding")
 async def verify_with_embedding(
     file: UploadFile = File(..., description="New video file to verify"),
-    stored_embedding: str = Body(..., description="Stored embedding as JSON string"),
+    stored_embedding: List[float] = Body(..., description="Stored embedding from database"),
     threshold: float = Body(0.8, description="Similarity threshold (0.0-1.0)")
 ):
     """
     Verify a new video against a stored embedding from database
     
     - **file**: New video file to verify
-    - **stored_embedding**: Pre-existing embedding array as JSON string
+    - **stored_embedding**: Pre-existing embedding array from database
     - **threshold**: Similarity threshold (default: 0.8)
     - **returns**: Similarity score and verification result
     """
@@ -289,34 +193,27 @@ async def verify_with_embedding(
                 detail="Only video files are supported (mp4, avi, mov, mkv)"
             )
 
-        # Parse stored embedding from JSON string
-        try:
-            import json
-            embedding_list = json.loads(stored_embedding)
-            stored_emb = np.array(embedding_list, dtype=np.float32)
-        except json.JSONDecodeError as e:
-            raise HTTPException(
-                status_code=400,
-                detail=f"Invalid JSON format for embedding: {str(e)}"
-            )
-        except Exception as e:
+        # Validate stored embedding
+        if not stored_embedding or len(stored_embedding) != 768:
             raise HTTPException(
                 status_code=400,
-                detail=f"Invalid embedding format: {str(e)}"
+                detail="Stored embedding must be a 768-dimensional array"
             )
 
-        # Validate embedding dimensions
-        if len(stored_emb) != 768:
+        # Validate threshold
+        if not 0.0 <= threshold <= 1.0:
             raise HTTPException(
                 status_code=400,
-                detail=f"Embedding must be 768-dimensional, got {len(stored_emb)}"
+                detail="Threshold must be between 0.0 and 1.0"
             )
 
-        # Validate threshold
-        if not 0.0 <= threshold <= 1.0:
+        # Convert stored embedding to numpy array
+        try:
+            stored_emb = np.array(stored_embedding, dtype=np.float32)
+        except Exception as e:
             raise HTTPException(
                 status_code=400,
-                detail="Threshold must be between 0.0 and 1.0"
+                detail=f"Invalid embedding format: {str(e)}"
             )
 
         # Create temporary file for new video
@@ -369,10 +266,6 @@ async def verify_with_embedding(
             detail=f"Internal server error: {str(e)}"
         )
 
-
-
-
-
 @app.post("/verify-two-videos")
 async def verify_two_videos(
     file1: UploadFile = File(..., description="First video file"),