1 min readfrom Machine Learning

What image/video training data is hardest to find right now? [R]

Our take

As we build a crowdsourced photo collection platform, we want to hear from you about the image and video training data that's hardest to find. Our innovative approach combines smartphone photos with automated labeling using YOLO and CLIP, enriched by over 40 metadata fields. We’re considering collecting specific datasets, such as European street scenes, supermarket shelves with OCR-extracted prices, analog utility meters, restaurant menus with prices, and EV charging stations. What image data do you wish existed?

I'm building a crowdsourced photo collection platform

(contributors take photos with smartphones, we auto-label

with YOLO/CLIP + enrich with 40+ metadata fields per image

including weather, time, GPS, OCR).

Before I decide what to collect first, I want to know:

what image data do YOU wish existed but doesn't?

Some ideas I'm considering:

- European street scenes (no dataset covers Switzerland/France)

- Supermarket shelves with OCR-extracted prices

- Analog utility meters

- Restaurant menus with prices

- EV charging stations by type

What would YOU actually use?

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