Seasons Of Code
Facial Recognition App • Prayas Jain • Vanshika Gupta
WnCC - Seasons of Code
Seasons of Code is a programme launched by WnCC along the lines of the Google Summer of Code. It provides one with an opprtunity to learn and participate in a variety of interesting projects under the mentorship of the very best in our institute.
List of Running Projects
- Browser Based PDF manager
- Resume Script Generator
- Physicc : A Simple Physics Engine
- Image Colorization
- Language Model Based Syntax Autocompletion in a Text Editor
- Computer vision based web app
- Cribbit Cribbit (Open for PGs Only)
- Techster Texter
- Language Detection
- Book Tracker
- ResoBin - Not the bin we deserve but the bin we need!
- Moodify
- Agree to disagree
- Unscripted
- Watson (World's smartest assistant in your pocket)
- IITinder
- BriefKing
- Meta Learning - Learning to Learn
- Break free of the matrix, by building one!
- Procedurally Generated Infinite Open World
- Introduction to App Development
- PAC MAN
- Introduction to Web Development
- (Un)Clear
- Goal ICPC
- Traffic congestion modelling and rendering
- PyRated
- Tools for Data Science
- Machine Learning Based Metropolitan Air Pollution Estimation
- Audio controlled drone
- NLPlay with Transformers
- DIY FaceApp
- A Deep Dive into CNNs
- Competitive Coding
- Snake AI
- Facial Recognition App
- Gaming meets AI !!!
- R(ea)L Trader
- Computational Geometry
- Deep reinforcement learning - 2048 AI
- Reinforcement Learning to Finance
- Developing Hybrid ANN-Statistical Model for Robust Stock Market Prediction
- Si-Phy
- Astronomical Data-modelling and Interpretation
- Visual Perception for Self Driving Cars
- Convolutional Neural Networks and Applications
- Quantum Computing Algorithms
- Algorithm Visualizer
- Anime Club IITB Website using Django
- Machine Learning in Browser
Facial Recognition App
[APPLICATIONS CLOSED!!!]
Ready to make a simple app that can compete with Google Photos?
No. of mentees: 6-8
Description: You must be living under a rock if you are not familiar with Google photos and it’s capabilities. But say you wants you want to nice movie (not google photos’ simple slideshow video) of all your mother and father pictures for their anniversary, and want to scan through your personal dataset for all such pictures and cluster them, can Google photos do it for you? No. You have to upload and wait for clustering and then can’t even get an output back. That’s one of the many features we want our Facial Recognition App to do!
We aim to develop a face recognition app capable of detecting all faces included in the image, cropping the faces and extracting their features, and comparing the faces for clustering pictures with same faces. We also plan to develop a GUI that can ask the user to label the unique people identified in the images and run a model that can learn the unique feature of each face to make future predictions on new images and videos. Our app will be able to output the cluster pictures with same faces and output them folder wise to a drive. We also aim to develop many additional features (as many as we can) in our app such as fancy one-click styling picture, image-captioning and cartooning videos that could be applied to whole dataset of user pictures.
Some open-source resources having similar ideas of project - https://www.pyimagesearch.com/2018/06/18/face-recognition-with-opencv-python-and-deep-learning/ https://machinelearningmastery.com/how-to-perform-face-detection-with-classical-and-deep-learning-methods-in-python-with-keras/ https://www.sitepoint.com/keras-face-detection-recognition/ https://www.youtube.com/watch?v=D4uBrRIK1OI https://github.com/nalbert9/Image-Captioning
Tentative Project Timeline
| Week Number | Tasks to be Completed |
|---|---|
| Week 1 | Learning python basics for ML + Using and beautifying colab notebook |
| Week 2 | Reading computer vision basics + Learning how to batch download facial dataset from internet or personal drive |
| Week 3 | Extracting face features and clustering similar faces automatically in drive |
| Week 4 | Developing a user interface to ask users to name found unique faces |
| Week 5 | Testing trained model on test picture and video + Trying new features such as cartoonizing user video + One click neural style transfer for pictures |
Checkpoints:
| Checkpoint Number | Progress |
|---|---|
| 1 | Making a simple user interface in Google Colab performing simple linear regression (will confirm understanding of python + colab + basic ML concepts) |
| 2 | Able to batch download and import pictures dataset or importing a labelled personal dataset |
| 3 | Successfully extracting feature vector of a face after reading about face recognition and computer vision basics |
| 4 | Developing a user interface to ask users to name found unique faces and model to learn individual features |
| 5 | Incorporating additional features in app and testing on test pictures and videos |