Converting a Static Map image to an Interactive Floorplan - PyCon SG 2019

Published on: Monday, 11 November 2019

- Chinab Chugh, CTO, Jublia
- Fahmi Fauzi, Team Lead, Jublia

Attending an event is fun until you get lost between exhibitor booths and are unable to find your way around. In my work, we have worked with over 1500 B2B Events and we generally see the use of static floorplans (images or PDFs being the most common). The reason behind this is building Interactive Floorplans can be a time-consuming and expensive task. First, you need a high DPI base image. To make it interactive, you then need to use an SVG creator tool to map each booth as a polygon manually. What if you had 1600 booths over a 8-halls venue? And the booths get allocated and change till the very last day. So we decided to SAAS-ify interactive floorplans by automating the creation of the SVG layer and repetitive tasks of booths linkage. We developed a two stages booth detection model with proposal stage using OpenCV and classification stage using a trained TensorFlow network. This covers cases like rotated booths, different-shaped polygons and more. We then used Google’s Tesseract-OCR Engine (through pytesseract) to detect the text inside the polygon, which represents the booth number and/or the company name, and we use that to link the booth to the exhibitor itself. Finally, the processed data is rendered using the Google Map API. This opens up many possibilities as the events we work with, big or small, can effectively use our engine for attendees to find their way in those tight venue spaces. We will also briefly share about routing capabilities across single and multiple halls in a venue.
About the speaker:

Chinab is the co-founder and CTO of Jublia which specialises in Smart Matchmaking at events. Apart from leading the development team, Chinab runs several web projects on the side and is fascinated by new technology research.

Fahmi is a passionate tech junkie. love to research and learn new tech. Currently, the Team Lead at Jublia. PS: He Loves Python.

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