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You will learn to:
Create a Flask application using templates.
Integrate JavaScript with Flask to enhance the frontend.
Learn file handling for image data.
Perform server-side image processing using the scikit-learn library.
Skills
Image Manipulation
Data Science
Web Development
Prerequisites
Hands-on experience with Python
Basic understanding of image processing
Familiarity with scikit-learn library
Basic knowledge of Flask
Technologies
Flask
Python
OpenCV
Project Description
In this project, we’ll build a Flask-based web application for image forgery detection using OpenCV and MD5 hashing. This project involves building a user interface that allows users to upload two images side by side and instantly determine if either is manipulated or not. The integration of OpenCV enables the application to process images using computer vision techniques, and the application of MD5 hash ensures accurate results, offering a lightweight solution for image authenticity verification.
Project Tasks
1
Introduction
Task 0: Get Started
Task 1: Import Libraries
Task 2: Design the Frontend
2
Upload the Images
Task 3: Implement Image Upload Functionality
Task 4: Handle the Upload Request to Backend
3
Image Analysis and Forgery Detection
Task 5: Calculate Similarity of Images
Task 6: Calculate MD5 Hash
Task 7: Determine Forgery and Display Results
Congratulations!
Relevant Courses
Use the following content to review prerequisites or explore specific concepts in detail.