nomad86

Thx! Downloading all the photos took the most time. Object detection process took only several days.

At TripOffice, we use simple and widely-used tools: Python, NextJS, and MySQL.

It reminded me of how, a long time ago, FPGAs were used in Bitcoin mining.

I haven't checked it, but such data should be easy to get from our database.

We manually labeled almost 1,000 chairs in various photos to train the model.

At first I wanted to use Google's Vertex AI for this purpose, but the costs were too high.

Besides, in this case, we would also have to upload 40 million photos to the cloud for Google to evaluate what’s on them.

YOLO is the best for such tasks; it works locally and is really fast.

This is not scraping. Many hotel sites share photos with their partners, we work with Lexyl (HotelPlanner).

All major booking sites share hotel photos with their partners.

We are in several partner programs, but now we mainly work with HotelPlanner.

I tried to detect models of specific chairs, but it's very difficult. To train the AI model, you need many photos of the same type of chair, and on the internet, you can usually find only one stock photo of each chair.

I created an app similar to Tinder that facilitates manual verification. Around 60 photos can be verified in one minute. The whole process took about a week and didn't cost much.

I don't know, I assigned this task to trusted specialists from India.

In our hotel photo database, we have everything: rooms, lobbies, bathrooms, pools, exterior shots of buildings, etc.

I trained an AI to recognize ergonomic chairs, but sometimes there were errors. For example, a chair in a hotel's SPA was always identified as an ergonomic chair. That's why we manually reviewed all 50k photos to verify them.

I'm building a hotel reservation system on tripoffice.com

Why?