PABITRA34 commented 4 months ago

Pull Request for DL-Simplified 💡

Issue Title : [Feature Addition]: Web Application for Anti Spoofing Project #544

Info about the related issue (Aim of the project) : [Feature Addition]: Web Application for Anti Spoofing Project #544
Name: Pabitra Kumar Bera
GitHub ID: https://github.com/PABITRA34
Email ID: pabitrabera34@gmail.com
Idenitfy yourself: (Mention in which program you are contributing in. Eg. For a JWOC 2022 participant it's, JWOC Participant) GSSOC 2024 contributor

Closes: issue number #544

Describe the add-ons or changes you've made 📃

Added Web Application to the Anti Spoofing Project using DL

Give a clear description of what have you added or modifications made 1.Setting Up the Environment Backend (Flask) : -Install Flask and dependencies: Use pip or pipenv to install Flask and any other necessary Python libraries (e.g., OpenCV, TensorFlow). -Loading and Preparing the Model -Load the pre-trained model: Use TensorFlow/Keras to load the trained anti-spoofing model. Define helper functions: Create functions to process input images/videos and make predictions using the model.

2.Developing the Backend -Flask Routes Upload route: Serve the main HTML page. Process route: Handle file uploads from the user (images or videos). Prediction route: Process the uploaded files, run them through the model, and return the results.

3.Building the Frontend HTML Templates -Main Page: Include a form for uploading images/videos and a section to display results. -Result Display: Use placeholders in the HTML to dynamically show the prediction results. CSS Styling : -Styling Elements: Style buttons, forms, and results display for better user experience.

4.Integrating Backend and Frontend -Form Handling: Ensure the form in the HTML template correctly posts data to the Flask backend.

5.Testing Local Testing: Run the Flask app locally to test all functionalities and ensure the model predictions are correct. 6.Debugging: Checked for and fixed arising issues or bugs.

Type of change ☑️

New feature addition [☑️ ] Added Web Application to the Anti Spoofing Project [☑️ ] Built Web Application for Anti Spoofing Project model using Flask , HTML, CSS [ ☑️] New feature (non-breaking change which adds functionality)

How Has This Been Tested? ⚙️

I have tested the Anti-Spoofing WebApp in running it on my local machine

Checklist: ☑️

[☑️ ] My code follows the guidelines of this project.
[☑️ ] I have performed a self-review of my own code.
[ ☑️] I have commented my code, particularly wherever it was hard to understand.
[☑️ ] I have made corresponding changes to the documentation.

github-actions[bot] commented 4 months ago

Our team will soon review your PR. Thanks @PABITRA34 :)