Climb GUI

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  Our application's logo.

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  Blue path pathfinding.

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  Red path pathfinding.

Inspiration

Our inspiration for the project was our interest in building something very unique using machine learning and computer vision. We are both interested in rock climbing, and love to climb, and an application like this is very useful for helping anyone.

What it does

This application analyzes a picture of a rock climbing surface, and maps out the most efficient or easy path to get from the start to the end.

How we built it

We built this application using reflex in conjunction with opencv, networkx, and matplotlib. We used the reflex framework to build our whole web application. In opencv we used many complicated functions to analyze the colors of the holds and draw lines from hold to hold, and draw paths on images. We used matplotlib to plot the images as graphs and show them to the user. We used networkx to find the most efficient path to get from the start to finish.

Challenges we ran into

It was very difficult to learn the reflex framework, as well as opencv, networkx, and matplotlib from scratch in such a short timeframe. There was a very high learning curve, and it took a lot of effort to debug.

Accomplishments that we're proud of

We are very proud of how fast we were able to learn these new frameworks and libraries. Specifically, we are very proud of our algorithms to determine the colors of the holds and map the best path from start to finish.

What we learned

We learned a lot about the iterative process of programming a full-stack application from start to finish, as well as how much time is needed to learn new libraries and frameworks.

What's next for Climb GUI

We would like to optimize our best path algorithm, and color detection so that they are applicable in many more cases. We would also like to make our GUI more interactive, and pleasant for the user navigate.

Built With

• numpy
• opencv
• python
• reflex