We’re here for you: If you ever need our help - or just want to chat - we’re there. We love seeing what you’re getting out there. Take pictures: Did you get something delicious that you want others to see? Snap a photo and share it on your favorite social media with the #toogoodtogo hashtag. We want to be better at what we do, and we can’t do it without you. And be sure to let us know if you have any feedback. Share your thoughts: Show some love to your local shops by letting them know that you love their food. It is their way of keeping track that they are handing out the right food to the right people. But in the Too Good To Go app, you need to let the shop staff swipe your receipt. Let the shop do the swiping: What you do on your Tinder profile is completely up to you. That’s the magic of it! It’s about saving what’s left at the end of the day - and if it’s not really your taste, maybe you know someone who’ll love it? You can’t always be sure what will be in your magic bag or magic box. But sometimes, a little change can be a good thing. Look forward to the surprise: We humans are creatures of habit so we like knowing what we’re going to get. If we can minimize other types of waste while saving surplus food - well, isn’t that just win-win? Some places also allow you to bring your own box for filling up from the buffet. When you’re headed to your favorite spot to save a lovely meal, be sure to bring a reusable bag to carry your savings home. Sharing is caring.īYOB: No, we’re not talking booze. If you’ve bought too much food, we would love it if you shared it with someone as well. Share with someone in need: If you have extra to share, you can donate to different charities in the app. Also, make sure to be at the shop on time - not too late so you come to a closed shop, and not too early so the staff isn’t ready to greet you. And while you’re at it, give one to your fellow food heroes in the shop. This way, the meal can go to someone else instead of ending up in the bin.īe on time - and be proud: You’re doing something good! It’s totally cool to give yourself a high five. But should it happen that you can’t make it to the specified pick-up time, be sure to cancel at least 3 hours before (you do it on the receipt in the app). Rule of thumb for cancellation: Of course you don’t want to cancel your purchase. Just give your favorite shop a heart, and you will have easy access to them when you’re ready to rescue your next meal. Keep track of your favorites: It’s super easy. You can also tell your friend where in their city to get their food rescue on. You can also specify categories (baked goods, fresh greens, restaurants etc.) - and if you only want to pick up straight after work, you can adjust the pick-up times.ĭiscovering your country: If you’re vacationing and can’t go a day without your Too Good To Go fix, jump into the map and explore. You can choose to see only shops with food left (or see it all so you know what to keep an eye out for tomorrow). We’ve gathered some hacks for you to make the most of the Too Good To Go app before, during and after rescuing your meal.įilters make your life easier: Or at least they make your Too Good To Go experience easier. But we can all use a few tips now and then. In our experiments, we have achieved above 85% accuracy when detecting 15 different kinds of foods.įood recognition mobile food recognition nutrition estimation visual food recognition.Rescuing great surplus food with Too Good To Go is easy as 1 - 2 - 3.
APP SNAP PHOTO FOOD ITEM ANDROID
We implemented this system as both an Android smartphone application and as a web service. When multiple food items appear in an image, our system can identify them and estimate their portion size simultaneously. Our system achieves automatic food detection and recognition in real-life settings containing cluttered backgrounds. Previous approaches have mostly worked with either images captured in a lab setting, or they require additional user input (eg, user crop bounding boxes). In addition, the system determines the portion size which is then used to estimate the calorific and nutrition content of the food present on the plate. We then extract features at different locations and scales and classify these regions into different kinds of foods using a linear support vector machine classifier. Hierarchical segmentation is performed to segment the image into regions. The system detects the salient region, crops its image, and subtracts the background accordingly. To identify food items, the user simply snaps a photo of the food plate. The system can recognize food and estimate the calorific and nutrition content of foods automatically without any user intervention.
We present snap-n-eat, a mobile food recognition system.
0 kommentar(er)
