Have you ever seen a sunset and wished you knew what color it was? Or walked by a house painted the exact color you want to paint your walls? Color Pal-it allows users to find the hex code of the most prominent colors in an image. Like “Shazam” for colors, users can identify and save colors they see in real life by uploading photos.

What it does

Color Pal-it scans pictures uploaded by users to find the most dominant color as well as two accent colors and returns their hex codes. It can also be used as a reverse image search because it returns words most associated with the image. Users can search for previously uploaded images using these words.

How I built it

We implemented the frontend using HTML, CSS, and the Bootstrap framework. We also used Adobe Illustrator to create the logo, a painter’s palette in the shape of a cube. We created a Flask webapp using the Google Cloud Vision, Storage, and Datastore APIs. Cloud Vision API: Identifying dominant colors, image subjects Storage and Datastore APIs: Storing user palettes and images in the cloud

Challenges I ran into

We had trouble deploying the application within the time limit of CalHacks, where we built the application. We also found it challenging to implement a pleasing UI for all the pages within the time limit.

Accomplishments that I'm proud of

We were proud of the dominant color algorithm and the search function. We were also happy with the logo design.

What I learned

We learned more about using HTML and CSS, as well as how to use the Google Cloud Vision, Storage, and Store APIS. We also learned how to work better under a time limit.

What's next for Color Pal-it

We want to enable multiple user accounts in the future. Eventually, we want to develop a mobile application instead of a web application that can use pictures taken directly by a phone camera.

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