Watch advertisement video on youtube -https://youtu.be/lDfpMA_m7WE

Inspiration

While online shopping is becoming the most convenient and popular mode of purchasing, traditional in-store shopping still has the benefit of being able to see how the product looks on you. We were thus inspired by the struggle and hassle of needing to return or refund clothes when they do not fit or is not suitable to your style, because you were not able to see.

What it does

Our app lets users set up a profile, create a fully customizable avatar, search for products (by type, style, price, trends and popularity, distance from user, color or keywords) that they want to try out, and test them out on their avatar before deciding whether they want to buy it or not. We also have a loyalty point system where points are rewarded to users if they upload images of a product from a participating retailer, where the product is not yet on our app, or when they purchase from small/local businesses. There’s also a leader board where the top contributor will receive a free gift (monthly basis). We have other fun features like a search that supports small or locally owned businesses, friend list, favorited items, wishlist and push notifications if something from your customized preferences goes on sale.

How we built it

-Our virtual avatar room is created with UnityHub

-Our avatars and avatar customization would be made in collaboration with LoomAi

-Clothing models from the following formats obtained from cgtrader through API's(max,obj,3ds,stl,c4d,blend,ma and mb)

-Base models not found on cgtrader will be generated by us utilizing c++

-Texture transferred from clothing images to 3D/mesh models using a texture mapping tool created by us. We would be mapping images to their textures maps which is used to create textures avatars. To obtain data we would align garments meshes with clothing images, using these fits we would collect out dataset, then we get a mapping that predicts the location in the input image for each point of the target data map. We sample texture using these correspondences to produce final texture maps.

Challenges we ran into

We recognise the scale of this project, and so to scale it down, we can only provide a limited number of customization options in the beginning.

Most stores already have online components so we have to find a way to get them on board to participate in our app.

Fast fashion is a social issue attached to clothing retail that we would like to address and expand on in the future, but our current plan tries to put focus on supporting local/small businesses.

Accomplishments that we're proud of

We both worked very hard on the project, and we're proud that we could see it to this point of completion. We’re excited to introduce our ideas.

What we learned

As two people with limited experience in coding and app development, we self-taught a lot of new skills in the course of creating this project, which would definitely be of use in the future.

What's next for #LevelUpSocietyHack - Better Retail

We'd like to see how our ideas are received from retailers and the general public as our app has lots of potential and room for future growth. This is the retail experienced gamified – fun, useful, and convenient, all at once, bringing us closer to the future.