Body: <p>For the purposes of object detection, are there any easy ways to create annotated training images? For example, if we have <span class="math-container">$10,000$</span> 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?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-23T21:00:14.833Z
Comments.Text: 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.
Comments.UserDisplayName: Jeanba
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-24T00:45:43.393Z
Comments.Text: Possible 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.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-24T13:53:04.503Z
Comments.Text: 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?
Comments.UserDisplayName: TwinPenguins
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-25T21:55:35.340Z
Comments.Text: 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.
Comments.UserDisplayName: user1269942
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-03-08T23:36:36.653Z
Comments.Text: 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....
Comments.UserDisplayName: FourierFlux
Tags: <machine-learning><convolutional-neural-networks><datasets><object-detection>
Title: Are there any easy ways to create annotated training images for object detection?
UserDisplayName: James
ThreadText: # Are there any easy ways to create annotated training images for object detection?
  
  (Asked by: username_0 on 2019-11-23)
  
  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?
  
  **Tags:** machine-learning, convolutional-neural-networks, datasets, object-detection
  
  > **Comments:**
  > **username_1**: 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.  
  > **username_2**: Possible 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.  
  > **username_3**: None of these comments are in the direction of the question. username_0 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?  
  > **username_4**: 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.  
  > **username_5**: 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....  
  
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