Inspiration
The inspiration from this project came from the idea to really help create an easy way for patient to to indoors to identify problems with patients using AI
What it does
Our project uses AI recognition(image processing) to help determine the picture uploaded what type of skin condition it is.
How we built it
Our project uses AI recognition(image processing) to help determine the picture uploaded what type of skin condition it is.
Challenges we ran into
Some of the challenges we ran into was the environment that we were using and licking them together, as well as giving up on one language to pursue another so the the fluidity of the project could be successful.
Accomplishments that we're proud of
Something that we are, proud of is the experience we made in the Driver competition that pushed us to go further.
What we learned
During the experience, we learn teamwork and how to persevere and not give up when all hope seemed lost.
What's next for SkinSense
Find better and more inclusive data sets for skin types and skin color as well as developing a better data set. Improve the user interface. Have a feature to compare and differentiate different images.
Built With
- canva
- figma
- git
- google-cloud
- google-colab
- python
- streamlit
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