About AutoShop

Autoshop is a photo-editing tool that makes use of cutting edge deep learning techniques to add objects to and remove objects from images. The tool is innovative in the sense that there is no commercial product that can perform context-aware addition and removal of objects. The task of context-aware object addition and removal is challenging since the texture, opacity, brightness and other photographical details of the added object should match those of the background image. Currently, this process is handled by professional photoshoppers and it is quite time-consuming. Hence, Autoshop will allow people to edit their photos effortlessly.

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SIGNIFICANCE

Photoshop itself, is a demanding task. People train themselves to become good photoshoppers and spend heaps of time in front of the screen to make realistic photo edits. The departure point of our project, “Autoshop”, is to make this arduous task accessible to everyone, even the people knowing the absolute minimum of Photoshop.

WHAT IS AUTOSHOP?

AutoShop is an application for people who want to edit their photos effortlessly. Users can easily add objects on top of any picture. Tons of use cases can be found regarding photo editing. For instance, one may want to purchase some furniture for her living room, but she may be indecisive about how well the furniture will fit into the room. With the help of Autoshop; she can take the photo of the piece of furniture and the living room, combine these as if they are actually in the same place, and then decide. Also, people can add their faces on top of any photo and any person’s face, for example, their favorite rock band Queen’s poster or the famous movie Marvel Avengers’ cover photo.

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THE TEAM

Burak Yaşar

burakyasar97@gmail.com

Efe Acer

efeacer@gmail.com

T. Murathan Göktaş

murathangoktas@gmail.com

M. Mert Duman

duman.m.mert@gmail.com

Hikmet Demir

hikmet548@gmail.com

Reports

Specifications Report

Analysis Report

High Level Design Report

Low Level Design Report

Final Report

Evaluation Committee

Fazlı Can

Supervisor

Cevdet Aykanat

Jury Member

Ercüment Çiçek

Jury Member

Duygu Gözde Tümer

Innovation Expert