Messatsu92 OP t1_isat4q8 wrote on October 14, 2022 at 3:30 PM

Reply to comment by Left_Boat_3632 in [D] - Data Labelling - Computer Vision with 10k labels by Messatsu92

>labelimg

Thanks for your suggestion. Unfortunately I have to keep them with the best quality possible, but I don't think that it's related to the pictures.
I've tried with Label Studio & CVAT to create a new project from scratch with 1 low quality picture and 10k labels and it doesn't work (or lags a lot).

Left_Boat_3632 t1_isatuv2 wrote on October 14, 2022 at 3:35 PM

It could be something with your system then.

You don't have to degrade the quality of the original images. If you create a copy of the images and downsoze the copy, you can label the copied files while maintaining a link between the name of the original file and a name of the copy.

What size are the files?

Messatsu92 OP t1_isauci0 wrote on October 14, 2022 at 3:38 PM

I've tried with just 1 little picture (400kb, 512*512), it's working, but when I add the 10k labels into the JSON, unfortunately CVAT, Label Studio etc. lag a lot or don't work at all (freeze).

Left_Boat_3632 t1_isauk6u wrote on October 14, 2022 at 3:40 PM

Definitely sounds like an issue woth the amount of labels.

You could try splitting your dataset into chunks of 100 labels or 1000 labels and label that way?

Messatsu92 OP t1_isaw7mw wrote on October 14, 2022 at 3:51 PM

Exactly, it's definitely an issue with the amount of labels.

About my use case, I've to list 100k pictures with 10k labels. For each picture, the user have to use the object detection to detect the item, then he has to annotate (by chosing one of the 10k labels of items)

Trying to figure out if there's a workaround or software that maybe could fit with my needs...