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Shapes cARd game's itch.io pageDemo video link (Youtube or Vimeo)
https://youtu.be/k02cKqsJiys
Which NEW Lightship template(s) did you use?
Image Detection
How is your project related to the theme? (Optional)
We made a new way to play card games using Lightship's new features of Image Detection, allowing us to take the Card Games experience to a new level.
How have you innovated on this product? (Optional)
Lightship's Image detection only allowed for a single image and model, we improved it by allowing it to recognize multiple images, and mapping a specific model for each image. We made a new way to play TCGs allowing players to take real life cards and bring them into the game with Augmented Reality, improving the experience.
How does it speak to Niantic's mission? (Optional)
We share Niantic's dream of a world where we can create the real metaverse through Augmented Reality. People often think that a videogame is there to get you out of reality, when we can actually make Augmented Reality experiences, motivating people to go out there, or in this case, play with friends using real cards, with a twist through their devices, which improves both experiences.
How complete is your project? (Optional)
The prototype is fully playable. We made three playable characters with their cards, multiple dices so that attacks can have a variety to them, and the enemies from the AI get randomly generated to bring a new challenge each time the player begins. As it is a prototype, there is no possibility for Player vs Player, but a player can enjoy as much as they want against the AI without any problem.
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Comments
Judges' Feedback
Nolen Tabner, Software Engineer:
Very solid execution on a popular AR usecase. I'd love to see more characters and movesets. Would be a great candidate for multiplayer session, either using markers for colocalization or even utilizing VPS to colocalize and using image targets for cards.
PatCat, Lightship Leader:
The concept here is something I've heard a lot of developers consider building - so it's nice to see a group that actually took the time to explore this further. I like that they worked around limitations they found with the image recognition to be able to recognise more images, and I like that they have a whole battle system already built in that is pretty clear to understand despite doing this all in one mini-jam. Quite impressive!