Create register_face.py

register_face.py

@@ -0,0 +1,26 @@
+from fastapi import FastAPI, File, UploadFile, Form
+from deepface import DeepFace
+from pymongo import MongoClient
+from pydantic import BaseModel
+
+app = FastAPI()
+client = MongoClient('mongodb://localhost:27017/')
+db = client['face_recognition']
+users_collection = db['users']
+
+@app.post("/register/")
+async def register_face(image: UploadFile = File(...), name: str = Form(...)):
+    # Perform face recognition and get face embedding
+    try:
+        face_embedding = DeepFace.represent(img_path=image.file, model_name='Facenet')
+
+        # Store face embedding and metadata in MongoDB
+        user_data = {
+            "name": name,
+            "face_embedding": face_embedding
+        }
+        users_collection.insert_one(user_data)
+
+        return {"message": "Face registered successfully"}
+    except Exception as e:
+        return {"error": str(e)}, 500