Event | Date |
---|---|
Project allocation | 5 November 2021 |
Project proposal submission | 9 November 2021, 11:55 PM |
Code Freeze | 29 November 2021, 11:55 PM |
Final Evaluation | 2-4 December 2021 |
Once the project is finalized, a project proposal needs to be submitted. The project proposal must include the following items (use images where possible):
- Project ID and title
- Link to GitHub repository
- Team members
- Main goal(s) of the project
- Problem definition (What is the problem? How will things be done?)
- Results of the project (What will be done? What is the expected result?)
- What are the project milestones and expected timeline?
- Is there a dataset that you require? How do you plan to get it?
We expect all members to have read the papers once, even if you did not completely understand all sections of the paper.
Deadline: 9 November 2021
Your respective TA would have a meeting with the team to give his feedback.
NOTE: Based on the contents of the proposal, your project plan may need to be modified. We will contact your team coordinator.
- We will use GitHub Classrooms for the purpose of this project. TAs will make the project repositories for you.
- The code for the project will need to be regularly updated on GitHub. Make sure to create a project and add yourselves as individual contributors to the projects. Also add your assigned TA to the repository. IMPORTANT: Add github repository link to project proposal.
- To avoid running into GitHub’s size limits, ensure you upload only code and other documents (project proposal, final report) and NOT data (images). However, make sure that you upload them in either OneDrive or Google Drive, and share the link in the README of GitHub.
- Periodically backup/update your code on GitHub. We will be checking for updates and grading based on them.
- Contributions of each member will be seen by commits to the repository, so use you own GitHub accounts to contribute.
- Also having commit clustered around a single day will look bad.
You will have 3 deliverables:
- Deliverable 1: Project Presentation (12+3=15 minutes)
- Presentation + Demo (where appropriate)
- Leave at least 3 minutes for questions from the audience.
- TAs/Instructors may ask detailed questions, so everyone in the team should be familiar with the complete project, not just the part they worked on!
- All team members must be present.
- Deliverable 2: GitHub repository
- Along with your code, add a README markdown file (markdown cheatsheet) which must contain:
- Instructions on how to run your code and replicate the results.
- Test your code on a machine different from that used during project development. Include any missing dependencies and how to resolve them in the README.
- Link to input images: Package all images used for training/input to your code into a zip file. Upload this zip file and provide a link to this zip file.
- Link to output images: Package all images obtained as output from your code into a zip file. Upload this zip file and provide a link to this zip file.
- Use a sensible format for input and output filenames (e.g. On running code on input-0001.png, output should be output-0001.png). Alternately, you can include a script which loops through all your input images.
- NOTE: Do NOT upload the input/output image zip files on your GitHub repository. Upload them elsewhere (OneDrive or Google Drive) and add their links to README.
- Your project presentation should also be present in the GitHub repo -- we will check the timestamp, so make sure you upload the pptx/pdf files within an hour of your presentation.
- Along with your code, add a README markdown file (markdown cheatsheet) which must contain:
Component | Weightage |
---|---|
Project Proposal Document | 5% |
Workload (Code), completeness and novelty | 30% |
Viva | 35% |
Presentation | 30% |
- Other instructions and guidelines for the project have been discussed in the tutorial. Slides can be found here
- In any case, if you wish to have some feedback about the triviality or difficulty of your project, please speak to TAs or Instructor.
- You may use MATLAB/C/C++/Java/Python + any packages (OpenCV,ITK, etc) for your project. But merely invoking calls to someone else's software is not substance enough. You should have your own non-trivial coding component.
- If software for the research paper you implement is already available, you should use it only for comparison sake. You will be expected to implement the paper on your own. Please discuss with TAs/instructors if you need any clarifications for your specific case