[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

.github/workflows/changelog-ci.yml

@@ -36,4 +36,3 @@ jobs:
     #         release_name: Release ${{ github.run_number }}
     #         draft: false
     #         prerelease: false
-

.gitignore

@@ -143,4 +143,4 @@ __pyc
 FaceRec/static/Images/uploads/*
 Images/dbImages/*
 Images/Faces/*
-Images/
+Images/

API/route.py

@@ -8,7 +8,8 @@
 from datetime import datetime
 from io import BytesIO
 from typing import List
-from tensorflow.keras.models import load_model
+
+import numpy as np
 from bson import ObjectId
 from deepface import DeepFace
 from dotenv import load_dotenv
@@ -17,11 +18,11 @@
 from fastapi import HTTPException
 from fastapi import Response
 from fastapi import UploadFile
+from keras.preprocessing import image
 from matplotlib import pyplot as plt
 from PIL import Image
 from pydantic import BaseModel
-import numpy as np
-from keras.preprocessing import image
+from tensorflow.keras.models import load_model
 
 from API.database import Database
 from API.utils import init_logging_config
@@ -41,6 +42,8 @@
 collection3 = 'VectorDB'
 
 # Models  for the data to be sent and received by the server
+
+
 class Employee(BaseModel):
     EmployeeCode: int
     Name: str
@@ -55,42 +58,44 @@ class UpdateEmployee(BaseModel):
     Department: str
     Images: list[str]
 
+
 def load_and_preprocess_image(img_path, target_size=(160, 160)):
-    
+
     img = image.load_img(img_path, target_size=target_size)
     img_array = image.img_to_array(img)
     img_array = np.expand_dims(img_array, axis=0)
     img_array /= 255.0
     return img_array
 
+
 def calculate_embeddings(image_filename):
-
     """
     Calculate embeddings for the provided image.
-    
+
     Args:
         image_filename (str): The path to the image file.
-        
+
     Returns:
         list: A list of embeddings for the image.
     """
-    
+
     face_image_data = DeepFace.extract_faces(
         image_filename, enforce_detection=False,
     )
     new_image_path = f'Images/Faces/tmp.jpg'
-    
+
     if face_image_data[0]['face'] is not None:
         plt.imsave(new_image_path, face_image_data[0]['face'])
-        
+
         img_array = load_and_preprocess_image(new_image_path)
-        model=load_model('Model/embedding_trial3.h5')
+        model = load_model('Model/embedding_trial3.h5')
         embedding = model.predict(img_array)[0]
         embedding_list = embedding.tolist()
         logging.info(f'Embedding created')
-        
+
         return embedding_list
 
+
 @router.post('/recalculate_embeddings')
 async def recalculate_embeddings():
     """
@@ -107,15 +112,15 @@ async def recalculate_embeddings():
     for employee in employees_mongo:
         print(employee, type(employee))
         embeddings = []
-        
+
         # In the initial version, the images were stored in the 'Image' field
         if 'Images' in employee:
             images = employee['Images']
         else:
             images = [employee['Image']]
-        
+
         for encoded_image in images:
-            
+
             pil_image = Image.open(BytesIO(base64.b64decode(encoded_image)))
             image_filename = f'{employee["Name"]}.png'
             pil_image.save(image_filename)
@@ -172,7 +177,7 @@ async def create_new_faceEntry(Employee: Employee):
         # embedding = DeepFace.represent(
         #     image_filename, model_name='Facenet512', detector_backend='mtcnn',
         # )
-        
+
         embeddings.append(calculate_embeddings(image_filename))
         # os.remove(image_filename)
 
@@ -305,11 +310,11 @@ async def update_employees(EmployeeCode: int, Employee: UpdateEmployee):
             image_filename = f'{Employee.Name}.png'
             pil_image.save(image_filename)
             logging.debug(f'Image saved {Employee.Name}')
-            
+
             # embedding = DeepFace.represent(
             #     image_filename, model_name='Facenet', detector_backend='mtcnn',
             # )
-            
+
             embeddings.append(calculate_embeddings(image_filename))
             # os.remove(image_filename)
 
@@ -382,28 +387,29 @@ async def recognize_face(Face: UploadFile = File(...)):
     logging.info('Recognizing Face')
     try:
         # Code to calculate embeddings via Original Facenet model
-        
+
         img_data = await Face.read()
         image_filename = 'temp.png'
         with open(image_filename, 'wb') as f:
             f.write(img_data)
         # embedding = DeepFace.represent(
         #     img_path='temp.png', model_name='Facenet512', detector_backend='mtcnn',
         # )
-        
+
         # Code to calculate embeddings via Finetuned Facenet model
         face_image_data = DeepFace.extract_faces(
             image_filename, detector_backend='mtcnn', enforce_detection=False,
         )
-        
+
         if face_image_data and face_image_data[0]['face'] is not None:
-            
+
             plt.imsave(f'Images/Faces/tmp.jpg', face_image_data[0]['face'])
             face_image_path = f'Images/Faces/tmp.jpg'
             img_array = load_and_preprocess_image(face_image_path)
-            
+
             model = load_model('Model/embedding_trial3.h5')
-            embedding_list = model.predict(img_array)[0]  # Get the first prediction
+            embedding_list = model.predict(
+                img_array)[0]  # Get the first prediction
             print(embedding_list, type(embedding_list))
             embedding = embedding_list.tolist()
             result = client2.vector_search(collection3, embedding)

FaceRec/app/main/Edit.py

@@ -1,87 +1,94 @@
+from __future__ import annotations
+
 import base64
 import io
 import json
 import os
+
 import cv2
+import requests
 from flask import Blueprint
+from flask import redirect
+from flask import render_template
+from flask import request
 from flask import Response as flask_response
-from flask import redirect, render_template, request
 from PIL import Image
-import requests
-
+
 from FaceRec.config import Config
- 
+
 Edit_blueprint = Blueprint(
-    "Edit_blueprint",
+    'Edit_blueprint',
     __name__,
-    template_folder="../../templates/",
-    static_folder="../../static/",
+    template_folder='../../templates/',
+    static_folder='../../static/',
 )
- 
+
 cap = cv2.VideoCapture(0)
- 
- 
+
+
 # function for displaying live video
 def display_live_video():
     while True:
         success, frame = cap.read()  # Read a frame from the camera
         if not success:
             break
         frame = cv2.flip(frame, 1)
-        ret, buffer = cv2.imencode(".jpg", frame)
+        ret, buffer = cv2.imencode('.jpg', frame)
         frame = buffer.tobytes
         if not ret:
             break
         yield (
-            b"--frame\r\n"
-            b"Content-Type: image/jpeg\r\n\r\n" + bytearray(buffer) + b"\r\n\r\n"
+            b'--frame\r\n'
+            b'Content-Type: image/jpeg\r\n\r\n' +
+            bytearray(buffer) + b'\r\n\r\n'
         )
- 
- 
+
+
 # Route for displaying video
-@Edit_blueprint.route("/video_feed")
+@Edit_blueprint.route('/video_feed')
 def video_feed():
     return flask_response(
-        display_live_video(), mimetype="multipart/x-mixed-replace;boundary=frame"
+        display_live_video(), mimetype='multipart/x-mixed-replace;boundary=frame',
     )
- 
- 
+
+
 # Route for capturing image from video
-@Edit_blueprint.route("/capture", methods=["GET", "POST"])
+@Edit_blueprint.route('/capture', methods=['GET', 'POST'])
 def capture():
     global EmployeeCode
     global Name
     global gender
     global Dept
     global encoded_image
-    EmployeeCode = request.form.get("EmployeeCode", "")
-    Name = request.form.get("Name", "")
-    gender = request.form.get("gender", "")
-    Dept = request.form.get("Department", "")
+    EmployeeCode = request.form.get('EmployeeCode', '')
+    Name = request.form.get('Name', '')
+    gender = request.form.get('gender', '')
+    Dept = request.form.get('Department', '')
     ret, frame = cap.read(True)
     frame = cv2.flip(frame, 1)
-    _, buffer = cv2.imencode(".jpg", frame)
-    encoded_image = base64.b64encode(buffer).decode("utf-8")
-    with open(Config.image_data_file, "w") as file:
-        json.dump({"base64_image": encoded_image}, file)
-    return redirect("Image")
- 
- 
+    _, buffer = cv2.imencode('.jpg', frame)
+    encoded_image = base64.b64encode(buffer).decode('utf-8')
+    with open(Config.image_data_file, 'w') as file:
+        json.dump({'base64_image': encoded_image}, file)
+    return redirect('Image')
+
+
 # Route to display captured image
-@Edit_blueprint.route("/Image", methods=["GET"])
+@Edit_blueprint.route('/Image', methods=['GET'])
 def display_image():
     if os.path.exists(Config.image_data_file):
-        with open(Config.image_data_file, "r") as file:
+        with open(Config.image_data_file) as file:
             image_data = json.load(file)
-        encoded_image = image_data.get("base64_image", "")
+        encoded_image = image_data.get('base64_image', '')
         decoded_image_data = base64.b64decode(encoded_image)
         image = Image.open(io.BytesIO(decoded_image_data))
-        filename = "final.png"
-        image.save(os.path.join(Config.upload_image_path[0], filename), quality=100)
+        filename = 'final.png'
+        image.save(os.path.join(
+            Config.upload_image_path[0], filename), quality=100)
         image = sorted(
             os.listdir(Config.upload_image_path[0]),
             key=lambda x: os.path.getatime(
-                os.path.join(Config.upload_image_path[0], x)
+                os.path.join(Config.upload_image_path[0], x),
             ),
             reverse=True,
         )
@@ -91,42 +98,42 @@ def display_image():
     else:
         recent_image = None
     image_path = os.path.join(Config.upload_image_path[0], recent_image)
-    print("done")
-    return render_template("index.html", image_path=image_path)
-
-@Edit_blueprint.route("/edit/<int:EmployeeCode>", methods=["POST", "GET"])
+    print('done')
+    return render_template('index.html', image_path=image_path)
+
+
+@Edit_blueprint.route('/edit/<int:EmployeeCode>', methods=['POST', 'GET'])
 def edit(EmployeeCode):
-    if request.method == "POST":
-        Name = request.form["Name"]
-        gender = request.form["Gender"]
-        Department = request.form["Department"]
-        with open(Config.image_data_file, "r") as file:
+    if request.method == 'POST':
+        Name = request.form['Name']
+        gender = request.form['Gender']
+        Department = request.form['Department']
+        with open(Config.image_data_file) as file:
             image_data = json.load(file)
-        encoded_image = image_data.get("base64_image", "")
+        encoded_image = image_data.get('base64_image', '')
         payload = {
-            "Name": Name,
-            "gender": gender,
-            "Department": Department,
-            "Image": encoded_image,
+            'Name': Name,
+            'gender': gender,
+            'Department': Department,
+            'Image': encoded_image,
         }
         # logger.info(payload)
         try:
             url = requests.put(
-                f"http://127.0.0.1:8000/update/{EmployeeCode}", json=payload
+                f"http://127.0.0.1:8000/update/{EmployeeCode}", json=payload,
             )
             url.status_code
             # logger.info(url.json())
- 
-            return redirect("/")
- 
+
+            return redirect('/')
+
         except requests.exceptions.RequestException as e:
             print(f"Request failed: {e}")
     response = requests.get(f"http://127.0.0.1:8000/read/{EmployeeCode}")
     # logger.info(response.status_code)
     # logger.info(response.json())
     if response.status_code == 200:
         employee_data = response.json()
-        return render_template("edit.html", employee_data=employee_data)
+        return render_template('edit.html', employee_data=employee_data)
     else:
         return f"Error {response.status_code}: Failed to retrieve employee data."
-