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

[PABITRA34]

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) : Web Application for Anti Spoofing Project https://github.com/abhisheks008/DL-Simplified/issues/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 📃

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).

2. 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.

3. 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.

4. 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.

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

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

   Type of change ☑️

What sort of change have you made:

• [☑️ ] New feature addition
• [☑️ ] Built Web Application for Anti Spoofing Project model using Flask , HTML, CSS
• [☑️ ] Followed the specified Project structure
• [ ☑️] Code style update (formatting, local variables)

How Has This Been Tested? ⚙️

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

Checklist: ☑️

• [☑️ ] New feature (non-breaking change which adds functionality)
• [ ☑️] 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]]

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

[PABITRA34]

@abhisheks008 hello sir , ok sir, let me try