Project Info

A Cropping Drought

This project did not submit a demo video on Devpost.

Inspiration

Lots of water is used on front lawns annually. We wanted to try and help consumer make any easier choice by seeing their options that will save them money

What it does

This website converts thirsty lawns into fake ones.

How we built it

We built it by creating our own AI.

Challenges we ran into

The biggest challenge we ran into was not having any data or api for determining lawns so we had to create our own data.

Accomplishments we're proud of

This was two of our team member's first time using AI to solve a problem and they had a lot of fun.

What we learned

We learned a lot. We had to understand how to clean our data before training our model.

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only

PythonIn code
DjangoClaimed
FirebaseClaimed
JavaScriptClaimed
Tailwind CSSClaimed
TensorFlowClaimed

1 of 6 appear in the indexed code. 5 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

13 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.