Kicking Off Hacktoberfest with ACM-VIT!

Fill in the Blanks

You’ve lost random parts of your images. You need some mechanism to make your image set presentable again. Use your skill in Machine Learning to achieve this.

Submitting a Pull Request

Fork the repository by clicking the fork button on top right corner of the page
Clone the target repository. To clone, click on the clone button and copy the https address. Then run
```
git clone [HTTPS-ADDRESS]
```
- Go to the cloned directory by running
```
cd [NAME-OF-REPO]
```
- Create a new branch. Use
```
 git checkout -b [YOUR-BRANCH-NAME]
```
- Make your changes to the code. Add changes to your branch by using
```
git add .
```
- Commit the chanes by executing
```
git commit -m "your msg"
```
- Push to remote. To do this, run
```
git push origin [YOUR-BRANCH-NAME]
```
- Create a pull request. Go to the target repository and click on the “Compare & pull request” button. Make sure your PR description mentions which issues you’re solving.
- Wait for your request to be accepted.

Guidelines for Pull Request

Avoid pull requests that :
- are automated or scripted
- that are plagarized from someone else’s branch
Do not spam
Project maintainer’s decision on validity of PR is final.

For additional guidelines, refer to participation rules

What counts as a PR?

Check out our issues and try to solve them !

Interacting with Issues

There are helper issues that detail all you have to do to complete the project.
- Read the helper issues and work on the corresponding code in your fork of the repo.
- If you have some doubt regarding the ‘help’ given, comment below the issue.
- If you have some doubt not related to any ‘helper issue/s’ open, Open up a new issue, select doubt and fill in the template.
If you want to provide some extra help to fellow participants, open up a new helper issue. Don’t include any solution/code!
Do not spam

Overview

Idea

Fill in the Blanks, but with Images!

Explanation

The aim is to build a deep learning model, that takes as input an image with a missing rectangular portion and a boolean mask indicating its location, and imagines the missing content. The basic set of packages can be found in requirements.txt and can be installed using the pip command from usage section. The suggested dataset consists of images of various indoor scenes. Use the provided code to create the blanks in the images.

Dataset

Indoor Scenes [2.4GB tar]

You may use the provided funtion to create the blanks

import random_rect
new_img, bool_mask = random_rect(img, area)

Where img, new_img and bool_mask are NumPy or TensorFlow arrays,
area is a valid fraction in [0, 1].

Usage

Packages to be used are TensorFlow for creating and training the model, NumPy for handling arrays, MatPlotLib for image output.
Run the following command to install all the required packages for this project

pip install requirements.txt

Lets get started!

git remote add
git fetch
git merge

Authors

Authors:
Rohan Nolan Lasrado,
Atharva Gundawar

Contributors: