This organisation contains the imperial third year group project work under the supervision of Dr Nicolas Wu and constitued by:
- Jordan Hall
- Bartłomiej Cieślar
- Robbie Buxton
- Ethan Range
- Charlie Lidbury
- Oliver Killane
- Auto Labelling is a crucial part of supervised machine learning.
- FusedEffects provides the ability to embed domain specific languages within Haskell
- The ProbFX library is a DSL for probabilistic programming, developed using FusedEffects
To use and if necessary extend ProbFX to generate basic auto labelling for features such as road markings.
- Image Manipulation library (using FusedEffects).
- Model creation using ProbFX to demonstrate its potential.
- Model refinement using MCMC and othet techniques.
- To develop an mvp for lane labelling using the above.
A library to enable embedded DSL creation within Haskell.
A probabilistic programming DSL embedded within haskell as a library.
GitHub - Pytorch Implementation | Paper
Details a similar approach to that which we are taking.
Our first report detailing how we intend to work, basic plan for the project and potential risks.
prefix/branch-name-here| Prefix | Description |
|---|---|
| enh | An enhancement (e.g new feature, or improving an existing feature) |
| ref | Refactor - should not change behaviour |
| fix | Fixing a bug, the jira ticket should be included - branch name can be generated from jira |
| doc | Adding or amending documentation |
| msc | Miscellaneous, any other change |
This pull request template is used for all repos.
- Description
- Goals of PR (for reviewer to compare with the achieved)
- Current changes and intended changes (in case of draft PR)
