feat: Add Frontend Support for vector search function and improve face recognition

[Devasy23]

This pull request adds a new vector_search function to the database.py file, which performs a pipeline aggregation vector search on the MongoDB Atlas database. It also improves the face recognition code by refactoring it to use the Facenet512 model for better accuracy. Additionally, error handling has been added for cases where no match is found in face recognition. The pull request also includes code for the recognize_face API.

[senior-dev-bot]

Feedback from Senior Dev Bot

[senior-dev-bot]

CODE REVIEW

The vector_search function lacks input validation and error handling, and the function name could be more descriptive. Consider validating the inputs and handling potential exceptions.

def search_by_embedding(self, collection, embedding):
    if not collection or not embedding:
        raise ValueError("Collection and embedding are required.")
    # rest of the code...

[senior-dev-bot]

CODE REVIEW

The code changes are functional, but they lack readability. It's better to remove the excessive empty lines. Also, consider using arrow functions for brevity and consistency. Ensure error handling is consistent throughout the codebase.

$(document).ready(() => {
    $("#captureButton1").on("click", () => {
        $.ajax({
            type: "POST",
            url: "/capturing",
            success: (response) => {
                console.log(response);
                updateImage();
                enableImage();
            },
            error: (error) => {
                console.error(error);
            }
        });
    });
});

function updateImage() {
    var img = document.getElementById('Image');
}

[senior-dev-bot]

CODE REVIEW

The use of inline styles is not ideal. It's better to separate the CSS from the HTML for maintainability. Also, the use of classes like "dropdown-item" appears to be Bootstrap specific, but it's being used in a select element. Consider using appropriate classes or styles for the select element.

<style>
  .select-wrapper {
    padding-top: 10px;
  }
</style>

<div class="select-wrapper">
  <select id="Gender" name="Gender" class="form-select form-select-lg mb-3 bg-primary.bg-gradient" aria-label=".form-select-lg example" value="{{employee_data.gender}}" required>
    <option value="Male">Male</option>
    <option value="Female">Female</option>
    <option value="Other">Other</option>
  </select>
</div>

[senior-dev-bot]

CODE REVIEW

The code could be improved by using modern JavaScript conventions such as const and addEventListener for event handling. Additionally, consistent spacing and indentation will improve readability.

const uploadElement = document.getElementById('Upload');
uploadElement.removeAttribute('hidden');

myButton.addEventListener('click', () => {
  myPopup.classList.add('show');
});

[senior-dev-bot]

CODE REVIEW

The changes look good, but let's separate the styling from the HTML. Also, let's ensure proper indentation and follow accessibility best practices by providing labels for the select element.

<div style="padding-top: 10px;">
  <label for="Department">Department:</label>
  <select id="Department" name="Department" class="form-select form-select-lg mb-3 bg-primary.bg-gradient" aria-label=".form-select-lg example" value={{employee_data.Department}} required>
    <option value="Software" class="dropdown-item">Software</option>
    <option value="BPO/KPO" class="dropdown-item">BPO/KPO</option>
    <option value="Other" class="dropdown-item">Other</option>
  </select>
</div>

[senior-dev-bot]

CODE REVIEW

It's important to handle exceptions and errors properly. Consider logging the exception instead of printing it and returning a generic 500 status code.

except requests.exceptions.RequestException as e:
    logger.error(f"Request failed: {e}")
    return render_template("error.html"), 500

Also, the file upload handling logic seems incorrect. It's better to reorganize the condition and return the response for the missing file error outside the file existence check.

if "File" not in request.files:
    return jsonify({"message": "No file part"}), 400

if request.files["File"]:
    # handle file upload

[senior-dev-bot]

CODE REVIEW

In the first block, the commented-out code for making a POST request should be removed entirely. Besides, the second block uses 'url.status_code' instead of 'requests.put' for making a PUT request. Avoid unnecessary comments and handle exceptions appropriately. Also, consider using the response directly rather than calling 'response.json()' and 'jsonify(response.json())'.

# Remove commented-out code

# Replace 'url.status_code' with requests.put
resp = requests.put(
    f"http://127.0.0.1:8000/update/{EmployeeCode}", json=payload
)

# Use response directly
return jsonify(response.json())

[senior-dev-bot]

CODE REVIEW

The code changes look good. Consider refactoring the code for better readability and modularity. Also, it's a good practice to handle potential errors when saving the face image and inserting into the database.

# Refactored code for better readability and error handling
save_face_image(f"Images/Faces/{Name}.jpg", face_image_data[0]["face"])
log_info(f"Face saved {Name}")
embedding = create_embedding(image_filename)
embeddings.append(embedding)
log_info(f"Embedding created for {Name}")
delete_temp_image(image_filename)
log_debug(f"About to insert Embeddings: {embeddings}")
client2.insert_one(collection2, {"EmployeeCode": EmployeeCode, "Name": Name, ...})

[senior-dev-bot]

CODE REVIEW

The addition of the dotenv package and loading environment variables is a good practice. However, it's important to handle the import of the os package. Also, using descriptive names for variables is essential for readability.

import os
from dotenv import load_dotenv

load_dotenv()

MONGO_URI = os.getenv("MONGO_URL1")
client = Database()
second_client = Database("mongodb+srv://devansh:[email protected]/?retryWrites=true&w=majority&appName=Devasy23", "FaceRec")

[senior-dev-bot]

CODE REVIEW

The recognize_face function should be refactored to improve readability and maintainability. Consider breaking down the logic into smaller functions, using descriptive variable names, and applying error handling for file removal. Also, consider using context managers for file operations.

async def recognize_face(Face: UploadFile = File(...)):
    """
    Recognize a face from the provided image.
    Args:
        Face (UploadFile): The image file to be recognized.
    Returns:
        Response: A response object containing the recognized employee information in JSON format.
    Raises:
        HTTPException: If an internal server error occurs.
    """
    try:
        temp_image_path = "temp.png"
        await save_uploaded_image(Face, temp_image_path)
        embedding = extract_embedding(temp_image_path)
        result = search_for_matching_vector(embedding)
        remove_temp_image(temp_image_path)
        handle_matching_result(result)
    except Exception as e:
        handle_recognition_error(e)


async def save_uploaded_image(file: UploadFile, file_path: str) -> None:
    async with aiofiles.open(file_path, "wb") as temp_image:
        data = await file.read()
        await temp_image.write(data)

def extract_embedding(image_path: str):
    with open(image_path, "rb") as image_file:
        embedding = DeepFace.represent(img_path=image_path, model_name="Facenet512", detector_backend="mtcnn")
    return embedding


def search_for_matching_vector(embedding):
    result = client2.vector_search(collection2, embedding[0]['embedding'])
    return result

def remove_temp_image(file_path: str):
    os.remove(file_path)

def handle_matching_result(result):
    if result[0]['score'] < 0.5:
        return Response(status_code=404, content=json.dumps({"message": "No match found"}))

def handle_recognition_error(error):
    remove_temp_image("temp.png")
    raise HTTPException(status_code=500, detail="Internal server error")

[gitguardian]

⚠️ GitGuardian has uncovered 2 secrets following the scan of your pull request.

Please consider investigating the findings and remediating the incidents. Failure to do so may lead to compromising the associated services or software components.

🔎 Detected hardcoded secrets in your pull request

GitGuardian id	GitGuardian status	Secret	Commit	Filename
11383748	Triggered	MongoDB Credentials	096aba7	API/route.py	View secret
11383748	Triggered	MongoDB Credentials	1362215	API/route.py	View secret

🛠 Guidelines to remediate hardcoded secrets

1. Understand the implications of revoking this secret by investigating where it is used in your code.
2. Replace and store your secrets safely. Learn here the best practices.
3. Revoke and rotate these secrets.
4. If possible, rewrite git history. Rewriting git history is not a trivial act. You might completely break other contributing developers' workflow and you risk accidentally deleting legitimate data.

To avoid such incidents in the future consider

• following these best practices for managing and storing secrets including API keys and other credentials
• install secret detection on pre-commit to catch secret before it leaves your machine and ease remediation.

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[sonarcloud]

Quality Gate failed

Failed conditions
7 Security Hotspots
0.0% Coverage on New Code (required ≥ 80%)
6.2% Duplication on New Code (required ≤ 3%)
C Reliability Rating on New Code (required ≥ A)

See analysis details on SonarCloud

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