Posters catch your eye like nothing else does. Whether you are wandering in the streets, lost in your thoughts or rushing into the subway ; posters can always stop you. Sometimes it makes you remember that you really wanted to see that exhibition everyone told you about and which is ending very soon ; sometimes you just stop to admire them and take a snap ; sometimes they are so beautiful and inspiring you decide seeing the exhibition will not wait and you run to it.

This "Poster Entry" app would boost the efforts made by graphists, creatives to attract people by the art of posters and at the same time boost people's envy to go see the exhibition. It would create a virtuous circle by promoting culture, by boosting museums' bookings, by pushing the creatives to keep doing better and better. It can be very interesting in terms of data too.

Poster Entry is named after my desire to make people go to an exhibition because of a great poster : posters would be a way to get your exhibition ticket. The app would be in partnership with for instance "Fnac Spectacles" to get the access to the exhibition box office and book your visit.

You just have to get the app, let it access to your phone camera and whenever you see an exhibition poster just scan it and Poster Entry will get you to the box office page on Fnac Spectacles to book your ticket. For as soon as possible or later.

This is possible thanks to the deep learning : artificial intelligence can "read" images you scan. It detects shapes but also letters, words etc. The images will be part of a database after complete identification. Our database is connected to the Fnac Spectacles database, with whom we are in a partnership and share those images so our technology can identify the exhibition and redirect you to the correct exhibition booking page.

Poster Entry would be using assets from the ml5.js library to function : the ImageClassifier method to read the images and make it identify the exhibition the poster is about and redirect you directly to the Fnac page to book your ticket.

You can see how the ml5.ImageClassifier() method works right here. If you want to help us grow our database you can train your computer identify posters here.