Our generation is supposedly notorious for being inseparable from our phones. Specifically, we are the generation of social media. So, what happens when the pizza delivery person rings the doorbell right when we find the perfect lighting for our selfie? Is it worth leaving the app and actually using a calculator to determine how much to tip the deliverer? With our project, there is no need to choose! You can simultaneously be a hospitable community member while still posing for that selfie. Enter the total cost and use our filter to help you thank your pizza person for their hard work.
How it works
First, when the filter is opened, there is a box over the user's forehead with the label "How much should I tip?". There is also text at the bottom of the screen that says "enter amount here". The user clicks on the text at the bottom and enters the monetary value of a meal they are going to pay for. They then click on the box on their forehead as it randomly cycles through the 6 possible options for 6 seconds. Then, it will stop on one of these percentages. Once the user clicks the box one more time, the amount the user should tip will show up on the box, and the total cost (meal price + tip) will show up on the bottom of the screen.
What it does
This filter allows the user to input the monetary value of a meal. Then, the program randomly selects between 5 possible percent options (15%-20%) for the user to tip. Once a percentage is chosen, the program will calculate how much should be tipped, as well as the total cost of the meal.
How we built it
Challenges we ran into
Since Spark AR is a fairly new platform (only released in August 2018), there is not a lot of information out there from users on how to best manipulate data. Other than some tutorials from Facebook, we had to figure out a lot of the software through trial and error. One of our main challenges was sending data between the patch editor (drag&drop programming area) and the script.
Accomplishments that we're proud of
Considering that this technology is very new, we were very proud of ourselves for being able to comprehend and work with this software, without getting too frustrated. Even with trial and error, we were able to figure out how most things worked by using logic and analytical thinking.
What we learned
First and foremost, we learned so much about the world of AR. Whether it be 3D object placement or learning how to change certain features using script, we learned a great deal about AR that we never knew existed, especially considering how often we use these types of filters on a daily basis. Furthermore, we learned how to use the limited resources we had. Since SparkAR is a fairly new platform, we had to work together and debug our issues without the help of online resources to guide us along the way. Finally, we realized how much there is still to be learned about the world of AR, and we hope that one day we will be able to help create even larger-scale projects using AR.
What's next for Tip Calculator Filter
Unfortunately, text user input is an unsupported operation for Instagram filters. Our first goal is to find a way to make our filter Instagram compatible. We could potentially achieve this by having the user selected an amount rounded to the nearest whole so no text from the user is required. Furthermore, an interesting feature to add could be using data of the average tip amount for each restaurant (if that information is available) and suggesting what the most appropriate tip amount is based on previous tippers.