Seasons Of Code
Image Colorization • Valay Bundele
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
Image Colorization
Don’t like black and white images? No worries. This project involves building a machine learning model which will do this image colorization for you!
Description:
Colorizing black and white images is one of the most exciting applications of deep learning. Out of the many available techniques, Generative Adversarial Networks(GANs) based methods have shown excellent results on this task. Referring to GANs, Facebook’s AI research director Yann LeCun called adversarial training “the most interesting idea in the last 10 years in ML”. GANs are really the biggest breakthrough in the history of AI.
Image-to-image translation involves translating an image from one domain to another. It includes synthesizing photos from label maps, reconstructing objects from edge maps, and colorizing images. Pix2Pix GAN is a conditional image-to-image translation architecture which has produced really great results. This project will involve the implementation of this paper for image colorization. We can also try the other translation tasks given in the paper(if time permits).
The link to the paper : https://arxiv.org/pdf/1611.07004.pdf
You can take up this project even if you’re new to ML, you will just need to devote more time to it then.
No. of mentees: 4
Proposal:
Include the following points in your proposal :
- Your motivation for taking this project
- Experience with Python, ML/DL and various libraries(if any)
Tentative Project Timeline
| Week Number | Tasks to be Completed |
|---|---|
| Week 1-2 | Read about the basic ML techniques like linear/logistic regression and neural networks, learn python |
| Week 3 | Learn about Convolutional Neural Networks(CNNs), various deep learning architectures and PyTorch/TensorFlow |
| Week 4 | Understand the working of GANs and the main paper |
| Week 5-6 | Work on the implementation of the paper |
| Week 7 | Project documentation + Buffer |
Checkpoints:
| Checkpoint Number | Progress |
|---|---|
| 1 | Knowledge of basic ML techniques(Till week 5 of Machine Learning, Courses 1 and 2 of Deep Learning Specialisation) |
| 2 | CNNs (Course 4 of DL Specialisation) |
| 3 | Understanding of GANs and the paper |
| 4 | Implementation of the network architecture |
| 5 | Completing the model and training |