Project Info
This project did not submit a demo video on Devpost.
Inspiration
UCSC's campus is quite hilly and the changes in elevation can be tedious for some people to walk across, especially if they have underlying healthy issues.
What it does
It looks for the smoothest path from the starting point to the destination with the least changes in elevation based on the topographical map.
How we built it
We used VS Code to create a Python program. We used the Live Share extension plugin from the VS Code marketplace so multiple people could work in the same IDE on the same Python file at once.
Challenges we ran into
We ran into challenges with the path sometimes blocking itself in and creating bunches on the way to the end point. Sometimes, instead of the finding the elevation it kept bouncing between two neighboring pixels and couldn't successfully create a path.
Accomplishments we're proud of
We were able to make a path that goes from the start point to the end point. We were able to smooth it out so that it had the least changes in elevation as possible.
What we learned
We learned there are more elevation problems than we thought. It took us a while to get the path to form correctly, but once we did it was quite useful. This was the first hackathon for each of us, and it was a pretty fun and constructive experience.
Smooth-Mapping
Code Execution
We have uploaded 3 maps which are map1.png, map2.png, and map3.png to show working of our idea. -m command line option requires you to pass the file path.
# Execute the mapping.py file
python3 mapping.py -m map1.png
Inspiration
UCSC's campus is quite hilly and the changes in elevation can be tedious for some people to walk across, especially if they have underlying healthy issues.
What it does
It looks for the smoothest path from the starting point to the destination with the least changes in elevation based on the topographical map.
How we built it
We used VS Code to create a Python program. We used the Live Share extension plugin from the VS Code marketplace so multiple people could work in the same IDE on the same Python file at once.
Challenges we ran into
We ran into challenges with the path sometimes blocking itself in and creating bunches on the way to the end point. Sometimes, instead of the finding the elevation it kept bouncing between two neighboring pixels and couldn't successfully create a path.
Accomplishments that we're proud of
We were able to make a path that goes from the start point to the end point. We were able to smooth it out so that it had the least changes in elevation as possible.
What we learned
We learned there are more elevation problems than we thought. It took us a while to get the path to form correctly, but once we did it was quite useful. This was the first hackathon for each of us, and it was a pretty fun and constructive experience.
Analysis
View
Metric
- 4
- 2
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
- PythonIn code
1 of 1 appear in the indexed code.
AI coding agents
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Codebase size
Source size
7.7 KB
Source files
2
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
WilliamDemarest/Smooth-Mapping
8 files · 632 KB · @ f1fbc2f
Structure
Application logic
1 file · 13%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- Python79%
- Markdown21%
Share of indexed source by file size. Binary and vendored files are excluded.
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