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.
- 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.
- 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
Check out our issues and try to solve them !
- 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
Fill in the Blanks, but with Images!
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.
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].
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:
Rohan Nolan Lasrado,
Atharva Gundawar
Contributors: