Map: https://www.tripoffice.com/maps
Yolo: https://www.ultralytics.com/yolo
The whole process was done on a home Mac without the use of any LLMs. It's based on traditional object detection technology.
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Map: https://www.tripoffice.com/maps
Yolo: https://www.ultralytics.com/yolo
The whole process was done on a home Mac without the use of any LLMs. It's based on traditional object detection technology.
Side note; I love how YOLO, a deep learning based model, is now being referred to as traditional object detection. Template matching gang rise up.
Interesting idea and execution! So basically you wanted to find hotels where the rooms have office chairs and a desk? Or just in any of the images, e.g., a lobby? Side note; I love how YOLO, a deep learning based model, is now being referred to as traditional object detection. Template matching gang rise up.
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.
Interesting idea and execution! So basically you wanted to find hotels where the rooms have office chairs and a desk? Or just in any of the images, e.g., a lobby? Side note; I love how YOLO, a deep learning based model, is now being referred to as traditional object detection. Template matching gang rise up.
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.
Earlier quoted context omitted.
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.
50k manually? How long did it take you?
Earlier quoted context omitted.
I don't know, I assigned this task to trusted specialists from India.
Wow, manually reviewing 50k photos is a lot! Would you be willing to share what the cost of that was?
Earlier quoted context omitted.
Wow, manually reviewing 50k photos is a lot! Would you be willing to share what the cost of that was?
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.
Hotel rooms suck when you need to use them for work. Typically there are massive beds and I travel alone if for work. There is no proper chair, no writing table at all or one too small, and the sockets tend to be in the wrong corner of the room.
If I was an entrepreneur outside of software looking for a gap, I might have invented a hotel chain for work stays. But I'm not, so here is the idea for you to get rich with it (so I can stay there one day).
I like the OP's idea of using ML models to gather intelligence from hotel photos. For years I took a photo of nearly every hotel room with my laptop on the desk so that I could go back and re-book the rooms that were suitable if there was a conference in the same city again in the future.