Creating your own Snapchat filter using OpenCV

Sarvesh Shroff (~sarvesh77)


132

Votes

Description:

Have you ever wondered how snapchat filters work? In this talk we will give you a thorough explanation and demo of the famous face swap filter using OpenCV, dlib and NumPy.

Talk Summary:

We will do a line-by-line walkthrough of our code to extract facial landmarks of both images using methods like convex hull and delaunay triangulation. We then swap faces of the two input face images and blend them using the seamlessclone method. We will also go through various computer vision concepts required to understand the underlying mathematics.

Outcome:

After this talk you would be able to learn how to do the above mentioned tasks and some insights into a few OpenCV methods and we will also go over a little bit of numpy basics.

Agenda:

Introduction and live demo [5 min]

Explanation of facial landmark detection methods [5 min]

Overview of functions used in our code [5 min]

Line by line walkthrough of the code [10 min]

Questions from the audience [5 min]

Prerequisites:

Love for Python, Familiarity with Python3 syntax

Content URLs:

Example of one of our outputs:

enter image description here

Speaker Info:

Sarvesh Shroff:

I am currently a sophomore at SRM University AP and a Researcher at Next Tech Lab, A QS Reimagine Award-winning student-run innovation lab. I have won a national level robotics championship held at IIT-R.

Miran Junaidi:

I am MTH Junaidi, sophomore at SRM University AP and a Researcher at Next Tech Lab, A QS Reimagine Award-winning student-run innovation lab. Also gave a lightning talk at PyCon Taiwan 2018

Speaker Links:

Sarvesh Shroff:

GitHub

LinkedIn

Miran Junaidi:

GitHub

LinkedIn

Section: Others
Type: Talks
Target Audience: Beginner
Last Updated:

Sarvesh Great going Keep up Lokesh Aurangabad

Dhruv Bhartiya (~dhruv64)

Keep it up Sarvesh. All the best

shraddha shah (~shraddha84)

Be yourself to work on this kind of technology. In the coming days, this kind of innovation is going to come very well. Best of luck...! keep going ...!

Manish Gujrathi (~manish53)

Great going keep it up

Keshav Shah (~keshav24)

Great going keep it up

Keshav Shah (~keshav24)

Great going keep it up

Keshav Shah (~keshav24)

Great going keep it up

Keshav Shah (~keshav24)

Keep it up Sarvesh and all the best for your bright future

DineshChandrashah

All the best Sarvesh

Chhaya

The talk comes under the category of Data Science and not Others. I suggest the speakers to change the category.

Sourav Singh (~sourav)

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