Refactor code and fix formatting issues

API/database.py

@@ -1,6 +1,7 @@
-from pymongo import MongoClient
 from datetime import datetime
 
+from pymongo import MongoClient
+
 
 class Database:
     def __init__(self, uri="mongodb://localhost:27017/", db_name="ImageDB"):
@@ -13,11 +14,11 @@ def find(self, collection, query=None):
     def insert_one(self, collection, document):
         return self.db[collection].insert_one(document)
 
-    def find_one(self, collection,filter, projection=None):
-        return self.db[collection].find_one(filter=filter ,projection=projection)
-    
+    def find_one(self, collection, filter, projection=None):
+        return self.db[collection].find_one(filter=filter, projection=projection)
+
     def find_one_and_delete(self, collection, query):
         return self.db[collection].find_one_and_delete(query)
-    
+
     def update_one(self, collection, query, update):
         return self.db[collection].update_one(query, update)

API/route.py

@@ -12,6 +12,7 @@
 from PIL import Image
 from pydantic import BaseModel
 from pymongo import MongoClient
+
 from API.database import Database
 
 # Create a logger object
@@ -33,7 +34,7 @@
 # db = client["ImageDB"]
 client = Database()
 
-collection="faceEntries"
+collection = "faceEntries"
 
 
 # Models  for the data to be sent and received by the server
@@ -73,23 +74,26 @@ async def create_new_faceEntry(Employee: Employee):
         image_filename, detector_backend="mtcnn", enforce_detection=False
     )
     # Calculate the embeddings of the face image
-    plt.imsave(f"Images/Faces/{Name}.jpg", face_image_data[0]['face'])
+    plt.imsave(f"Images/Faces/{Name}.jpg", face_image_data[0]["face"])
     embeddings = DeepFace.represent(
         image_filename, model_name="Facenet", detector_backend="mtcnn"
     )
     os.remove(image_filename)
     # Store the data in the database
-    client.insert_one(collection, {
+    client.insert_one(
+        collection,
+        {
             "EmployeeCode": EmployeeCode,
             "Name": Name,
             "gender": gender,
             "Department": Department,
             "time": time,
             "embeddings": embeddings,
             "Image": encoded_image,
-        })
+        },
+    )
     # db.faceEntries.insert_one(
-        
+
     # )
     return {"message": "Face entry created successfully"}
 
@@ -116,7 +120,8 @@ async def get_employees():
 async def read_employee(EmployeeCode: int):
     try:
         # logger.info(f"Start {EmployeeCode}")
-        items = client.find_one(collection,
+        items = client.find_one(
+            collection,
             filter={"EmployeeCode": EmployeeCode},
             projection={
                 "Name": True,
@@ -146,16 +151,17 @@ async def read_employee(EmployeeCode: int):
 async def update_employees(EmployeeCode: int, Employee: UpdateEmployee):
     try:
         # logger.warning("Updating Start")
-        user_id = client.find_one(collection,
-            {"EmployeeCode": EmployeeCode}, projection={"_id": True}
+        user_id = client.find_one(
+            collection, {"EmployeeCode": EmployeeCode}, projection={"_id": True}
         )
         print(user_id)
         if not user_id:
             raise HTTPException(status_code=404, detail="Employee not found")
         Employee_data = Employee.model_dump(by_alias=True, exclude_unset=True)
         # logger.info(f"Employee data to update: {Employee_data}")
         try:
-            update_result = client.update_one(collection,
+            update_result = client.update_one(
+                collection,
                 filter={"_id": ObjectId(user_id["_id"])},
                 update={"$set": Employee_data},
             )

FaceRec/app/main/Employee.py

@@ -94,23 +94,27 @@ def submit_form():
     }
     url = "http://127.0.0.1:8000/create_new_faceEntry"
     try:
-        resp = requests.post(url=url, json={
-            "EmployeeCode": 134,
-            "Name": "Name",
-            "gender": "gender",
-            "Department": "Department",
-            "Image": "your_image",
-        })
+        resp = requests.post(
+            url=url,
+            json={
+                "EmployeeCode": 134,
+                "Name": "Name",
+                "gender": "gender",
+                "Department": "Department",
+                "Image": "your_image",
+            },
+        )
         resp.status_code
     except requests.exceptions.RequestException as e:
         print(f"Request failed: {e}")
     jsonify({"message": "Successfully executed"})
     print("Executed.")
-    if resp.status_code==200:
+    if resp.status_code == 200:
         return redirect("DisplayingEmployees")
     else:
         return jsonify({"message": "Failed to execute"})
 
+
 # To edit an employee details
 @flk_blueprint.route("/edit/<int:EmployeeCode>", methods=["POST", "GET"])
 def edit(EmployeeCode):

requirements.txt

@@ -1,44 +1,26 @@
-absl-py==2.0.0
-aiohttp==3.9.1
-aiosignal==1.3.1
-annotated-types==0.6.0
-anyio==4.2.0
-asttokens==2.4.1
-astunparse==1.6.3
-attrs==23.2.0
 absl-py==2.1.0
 annotated-types==0.6.0
 anyio==4.2.0
 astunparse==1.6.3
 beautifulsoup4==4.12.2
-black==24.2.0
 blinker==1.7.0
 cachetools==5.3.2
 certifi==2023.11.17
-cffi==1.16.0
 charset-normalizer==3.3.2
 click==8.1.7
 colorama==0.4.6
-comm==0.2.1
 contourpy==1.2.0
-coverage==7.4.3
-cryptography==41.0.7
 cycler==0.12.1
-debugpy==1.8.0
-decorator==5.1.1
 deepface==0.0.81
 Deprecated==1.2.14
 dnspython==2.4.2
-docker==7.0.0
 exceptiongroup==1.2.0
-executing==2.0.1
 fastapi==0.108.0
 filelock==3.13.1
 fire==0.5.0
 Flask==3.0.0
 flatbuffers==23.5.26
 fonttools==4.47.2
-frozenlist==1.4.1
 gast==0.5.4
 gdown==4.7.3
 google-auth==2.26.2
@@ -51,88 +33,59 @@ h5py==3.10.0
 httpcore==1.0.2
 httpx==0.26.0
 idna==3.6
+importlib-metadata==7.0.1
+importlib-resources==6.1.1
 iniconfig==2.0.0
-ipykernel==6.29.0
-ipython==8.20.0
-isort==5.13.2
 itsdangerous==2.1.2
-jedi==0.19.1
 Jinja2==3.1.3
-jupyter_client==8.6.0
-jupyter_core==5.7.1
 keras==2.15.0
 kiwisolver==1.4.5
 libclang==16.0.6
 Markdown==3.5.2
 MarkupSafe==2.1.3
 matplotlib==3.8.2
-matplotlib-inline==0.1.6
 ml-dtypes==0.2.0
 mtcnn==0.1.1
-multidict==6.0.4
-mypy-extensions==1.0.0
-nest-asyncio==1.5.9
 numpy==1.26.3
 oauthlib==3.2.2
 opencv-python==4.9.0.80
 opt-einsum==3.3.0
 packaging==23.2
 pandas==2.1.4
-parso==0.8.3
-pathspec==0.12.1
 pillow==10.2.0
-platformdirs==4.1.0
 pluggy==1.3.0
-prompt-toolkit==3.0.43
 protobuf==4.23.4
-psutil==5.9.7
-pure-eval==0.2.2
 pyasn1==0.5.1
 pyasn1-modules==0.3.0
-pycparser==2.21
 pydantic==2.5.3
 pydantic_core==2.14.6
-Pygments==2.17.2
 pymongo==4.6.1
 pyparsing==3.1.1
 PySocks==1.7.1
 pytest==7.4.4
-pytest-cov==4.1.0
 python-dateutil==2.8.2
 python-multipart==0.0.6
 pytz==2023.3.post1
-pyvespa==0.39.0
-pywin32==306
-pyzmq==25.1.2
 requests==2.31.0
 requests-oauthlib==1.3.1
 retina-face==0.0.13
 rsa==4.9
 six==1.16.0
 sniffio==1.3.0
 soupsieve==2.5
-stack-data==0.6.3
 starlette==0.32.0.post1
-tenacity==8.2.3
 tensorboard==2.15.1
 tensorboard-data-server==0.7.2
 tensorflow==2.15.0
 tensorflow-estimator==2.15.0
-tensorflow-intel==2.15.0
 tensorflow-io-gcs-filesystem==0.31.0
 termcolor==2.4.0
-tokenize-rt==5.2.0
 tomli==2.0.1
-tornado==6.4
 tqdm==4.66.1
-traitlets==5.14.1
 typing_extensions==4.9.0
 tzdata==2023.4
 urllib3==2.1.0
 uvicorn==0.25.0
-wcwidth==0.2.13
 Werkzeug==3.0.1
 wrapt==1.14.1
-yarl==1.9.4
-
 zipp==3.17.0

route/route.py

@@ -1,40 +1,44 @@
-from fastapi import FastAPI, File, UploadFile
-from fastapi.responses import FileResponse
 import os
+import uuid
 from datetime import datetime
-from pymongo import MongoClient
 from random import randint
-import uuid
+
 from deepface import DeepFace
+from fastapi import FastAPI, File, UploadFile
+from fastapi.responses import FileResponse
 from matplotlib import pyplot as plt
+from pymongo import MongoClient
 
 IMAGEDIR = "test-faces/"
 
-mongodb_uri ='mongodb://localhost:27017/'
+mongodb_uri = "mongodb://localhost:27017/"
 port = 8000
-client = MongoClient(mongodb_uri,port)
+client = MongoClient(mongodb_uri, port)
 
 db = client["ImageDB"]
 faceEntries = db["faceEntries"]
 
 app = FastAPI()
 
+
 # deprecated
 @app.post("/upload/")
 async def register_face(file: UploadFile = File(...)):
 
     file.filename = f"{uuid.uuid4()}.jpg"
     contents = await file.read()
 
-    #save the file
+    # save the file
     with open(f"{IMAGEDIR}{file.filename}", "wb") as f:
         f.write(contents)
     # db.images.insert_one({"filename": file.filename, "contents": contents})
     return {"filename": file.filename}
 
 
 @app.post("/create_new_faceEntry")
-async def create_new_faceEntry(id:int, age: int, gender: str, image: UploadFile = File(...)):
+async def create_new_faceEntry(
+    id: int, age: int, gender: str, image: UploadFile = File(...)
+):
     # Generate a unique ID
     # id = uuid.uuid4()
 
@@ -49,26 +53,35 @@ async def create_new_faceEntry(id:int, age: int, gender: str, image: UploadFile
         f.write(image_data)
 
     # Extract the face from the image
-    face_image_data = DeepFace.extract_faces(f"../Images/dbImages/{image.filename}", detector_backend="mtcnn")
+    face_image_data = DeepFace.extract_faces(
+        f"../Images/dbImages/{image.filename}", detector_backend="mtcnn"
+    )
 
     # Save the face image in a specified directory
-    plt.imsave(f"../Images/Faces/{image.filename}", face_image_data[0]['face'])
+    plt.imsave(f"../Images/Faces/{image.filename}", face_image_data[0]["face"])
 
     # Calculate the embeddings of the face image
-    embeddings = DeepFace.represent(f"../Images/dbImages/{image.filename}", model_name="Facenet", detector_backend="mtcnn")
+    embeddings = DeepFace.represent(
+        f"../Images/dbImages/{image.filename}",
+        model_name="Facenet",
+        detector_backend="mtcnn",
+    )
 
     # Store the data in the database
-    db.faceEntries.insert_one({
-        "id": id,
-        "age": age,
-        "gender": gender,
-        "time": time,
-        "embeddings": embeddings,
-        # "face-img": face_image_data,
-    })
+    db.faceEntries.insert_one(
+        {
+            "id": id,
+            "age": age,
+            "gender": gender,
+            "time": time,
+            "embeddings": embeddings,
+            # "face-img": face_image_data,
+        }
+    )
 
     return {"message": "Face entry created successfully"}
 
+
 @app.get("/show/")
 async def read_random_file():
 
@@ -77,9 +90,10 @@ async def read_random_file():
     random_index = randint(0, len(files) - 1)
 
     path = f"{IMAGEDIR}{files[random_index]}"
-    
+
     return FileResponse(path)
 
+
 @app.delete("/delete/{filename}")
 async def delete_file(filename: str):
     os.remove(f"{IMAGEDIR}/{filename}")