For the purposes of object detection, are there any easy ways to create annotated training images? For example, if we have $10,000$ images and want to draw bounding boxes on 2 objects for each image, do we have to physically draw those boxes? Is that what most people do these days to create training data?
Asked
Active
Viewed 140 times
6
-
I would suggest you to get a look at what openCV can do. I don't think you'll need to draw boxes but you may have to answer manually for each picture if it's object A or B. – Jeanba Nov 23 '19 at 21:00
-
2Possible duplicate of [Are there tools to help labelling images?](https://ai.stackexchange.com/questions/12689/are-there-tools-to-help-labelling-images), but maybe this is not an exact duplicate. – nbro Nov 24 '19 at 00:45
-
None of these comments are in the direction of the question. James is asking whether there is a smarter way to automatically annotate large amount of training images. Here is my input. The short answer is: it depends. If objects are certain know objects that you may be able to use a trained model, you may have some decent annotations, but I am afraid that is likely. Google now does it with AutoML. Besides, you do not need more than 300-400 annotations per each object. Why you think you need to train 10,000 images in the first place? – TwinPenguins Nov 24 '19 at 13:53
-
I once had a fresh dataset and needed to draw bboxes. I made my own little python+opencv program. I always assumed that people in similar circumstances would do the same...but perhaps a wee bit different depending on the needs of the problem. So, the answer is yes, the boxes need to be draw by *somebody* and if it's your task, then you're the best person to do it. When I did it, I learned a lot about my images as well. – user1269942 Nov 25 '19 at 21:55
-
If you don't manually enter in the information, you expect a system to. Which becomes circular since you're trying to teach a system to detect images.... – FourierFlux Mar 08 '20 at 23:36