Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Image labels are wrong #1

Open
DogukanAltay opened this issue Jan 30, 2019 · 5 comments
Open

Image labels are wrong #1

DogukanAltay opened this issue Jan 30, 2019 · 5 comments

Comments

@DogukanAltay
Copy link

You should specify the labeling format. If it is <class_id> , the bounding boxes are completely broken.

@chuanenlin
Copy link
Owner

The class ID is the first digit of each line in the label .txt files. In YOLO, the IDs start from 0 and increments by one for each new class. Since the labels are specifically for one class only (drone), all the labels have ID of 0.

@JSGFJSG
Copy link

JSGFJSG commented Apr 2, 2019

Could you explain how is stored the bounding box information in the label files?. Because if you draw the bounding box in the image, it is completely broken.

Thanks

@chuanenlin
Copy link
Owner

@JSGFJSG The labels are in the format: [class_id] [x_center] [y_center] [x_width] [y_width] which is the standard format for YOLO.

@JSGFJSG
Copy link

JSGFJSG commented Apr 2, 2019

@chuanenlin Why don't you use the bounding box coordinates normalized by image width and height as is indicated in https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects?. Thanks in advance.

@chuanenlin
Copy link
Owner

@JSGFJSG I haven't normalized the coordinates because this is the correct labeling format for the Linux (original) version of YOLO. However, I think it should be relatively straightforward to do normalization since you can easily find the image width and height of all raw images.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants