Build-A-Caifan is an imaginary online caifan stall which digitally replicates the experience of picking out dishes at a stall through clicking on food emojis.
The dishes selected are reflected real-time as illustrations on a plate before being digitally "cooked" using machine learning to present a final, realistic-looking plate of piping-hot, ready-to-eat caifan.
👀 Experience The Work Here
(Requires iOS 15 and above for Apple devices.)
🥡 [CLOSED] Feelers Build-A-Caifan Challenge
You are invited to use our caifan builder to create as many delicious plates of caifan as you can imagine. As good food is meant to be shared, we are happy to pay forward a meal on your behalf for every completed challenge. Simply follow the steps below to participate in the challenge and be a part of a sharing community with meals for everyone.
1️⃣ Use the builder to generate a plate of caifan. Right click to save the image.
2️⃣ Go to your local caifan stall and try to get a plate of caifan as close to the image as possible.
3️⃣ Post a picture/story on Instagram of both the generated caifan image and the actual caifan for comparison.
4️⃣ Follow and tag us @feelers_feelers
on your post/story. Make sure your account is not private so we can see your post/story.
5️⃣ EXTRA: To submit another entry, join our Feelers Discord
. Post your entry in #submissions.
And congratulations! You have completed the challenge and we will pay forward one meal to Food From The Heart per entry. If you are interested in our receipts and the status of this challenge, please join our Feelers Discord
🍽️ About Food From The Heart
Food From The Heart
a non-profit organisation that works towards combating food insecurity and alleviating hunger by providing reliable, consistent, and sustainable food support to the less-fortunate through food distribution programmes. The specific programme we are supporting is Project Belanja!
– an initiative which provides those in need with freshly-cooked meals that are redeemable at designated hawker stalls within proximity of the activity zones of the beneficiaries. Find out more about the campaign here
Machine learning model trained on dataset which consists of images from @caipng2.50