We were inspired by our materials professors to use the knowledge we gained in class and apply it to the real world.

What it does

The application finds the percentage of alpha and beta grains in a given image of a microstructure and gives an average size of all the grains. This allows materials engineers to research more quickly and efficiently!

How we built it

We used python with OpenCV to read the images and upload the images.

Challenges we ran into

We wanted to use GitHub to connect everyone, but there were conflicts with .idea/ files when using JetBrain's pyCharms instead we transfer code manually.

Accomplishments that we're proud of

Being able to use OpenCV to read images, completing the final target on the material challenge, and learn a bit of front end programming.

What we learned

We learned to use OpenCV and matplotlib to plot and read images as matrix and used that data to find percentage and display our found data.

What's next for Microstructure analysis

The next step is to apply the analysis to many different types of states and being able to detect point and line defects within the microstructure and give the pixel size of it.

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