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+# ignore mac configuration files
+.DS_Store
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-# BHacks-2023
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+# BHacks-2023
+
+# Failed Idea: ML Color Style Image Recognition Mobile App
+
+- Our app would have the user take a picture of themselves in their outfit, and then the app would use machine learning to determine the color scheme of the outfit to tell them if the color matches
+
+## Research
+
+-After reasearch many apis to see if they could determine the color of the outfit of a person in an image, we found that they either had signifcant paywalls such as [Imagga](https://imagga.com/solutions/color-api) and [folio](https://www.folio3.ai/prebuilt-models/apparel-detection/#:~:text=Clothing%20Detection%20Solution%20Accurately%20detect,recognize%20apparel%20types%20in%20images), or that they simply failed to work like [Farba's color extractor for apparrel](https://rapidapi.com/farba/api/color-extractor-for-apparel-2/)
+-We found a outfit compatibility predictor to determine whether the color schemes of outfit, but the dependencies were outdated
+-After more research, we found three main models to determine the color scheme and its stylishness of an outfit
+    1. GAN (Generative Adversarial Network) to remove the background and skin of the image as done in this [article](https://towardsdatascience.com/clothes-and-color-extraction-with-generative-adversarial-network-80ba117e17e6)
+    2. CNN (Convolutional Neural Network) to determine the color scheme of the outfit as done in this [article](https://towardsdatascience.com/color-identification-in-images-machine-learning-application-b26e770c4c71) OR implement KMeans clustering algorithm to determine the color scheme of the outfit using the elbow method as well
+    3. Ask ChatGPT to help us write a program to determine if the color scheme found is stylish by color theory as done in this [article](https://www.canva.com/colors/color-wheel/)
+- Ultimately, these models were too complex to implement in the time frame of the hackathon, so we decided to pivot to a new idea
+
+# Pivot Point: Student Link GCal Exporter Chrome Extension
+
+## User Stories
+
+1. Downloads chrome extension
+2. Clicks on extension icon
+3. Prompted to sign in via Google OAuth
+4. Signs in via Google OAuth
+5. Create a mesasage that says we need to be able to access your calendar
+6. Sign in is successful; if not -- prompt to sign in again
+7. Give step by step instructions on how to navigate to the course schedule apge on student link
+8. When on the course schedule page, present button to export course schedule to Google Calendar
+9. Export to Google Calendar successfully!
+
+
+Features to add:
+-Chrome extension should light up red when on a page that has a student link calendar
+-Button to export should only appear when on correct student link course schedule page
+
+## Timeline
+
+1. Figure out how to develop Chrome extensions
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