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

How can I get predicted class in eval.py #18

Open
atinfinity opened this issue Mar 13, 2019 · 11 comments
Open

How can I get predicted class in eval.py #18

atinfinity opened this issue Mar 13, 2019 · 11 comments

Comments

@atinfinity
Copy link

In https://github.com/AI-liu/Complex-YOLO#result, predicted box and predicted class is drawn.
But, I think that eval.py draws only predicted box and target box. So, I want to know how to get predicted class from all_boxes.

@abhigoku10
Copy link

@atinfinity i am too facing the same issue did u get a solution for it

@atinfinity
Copy link
Author

@abhigoku10
I think that pred_boxes has 15 elements. And, pred_boxes[7]~[14] has the confidence of classes.
https://github.com/AI-liu/Complex-YOLO/blob/master/eval.py#L59-L68

But, some element has negative value. So, I don't understand this reason.

@atinfinity atinfinity changed the title How to get predicted class in eval.py How can I get predicted class in eval.py Mar 14, 2019
@abhigoku10
Copy link

@atinfinity thanks for the inputs, yes negatives even i observed it and had one query does the prediction of the classes are proper

@abhigoku10
Copy link

@atinfinity where you able to get correct prediction of the classes . even i am getting negative values in the tensors

@abhigoku10
Copy link

@atinfinity i was able to solve the issue let me know if you have not solved it .

@siliconvalleypilot
Copy link

@abhigoku10 How did you solve the problem? I see negative values and np.argmax does not give the correct label position

@abhigoku10
Copy link

@qiaosongwang please take the updated code from the repo and train it you shall get correct values or i have forked the repo and made the corrections you can also take it fromthere

@siliconvalleypilot
Copy link

@abhigoku10 Great! Thanks

@imdsafi09
Copy link

I train the model till 158 epochs and then eval on different epoch but the detection is only for car which is not correct enough and the results here contain the class labels also but in my case no labels either..can someone please guide me whats the problem

@abhigoku10
Copy link

@imdsafi09 i would suggest you look into https://github.com/ghimiredhikura/Complex-YOLOv3 this is currently updated and the current repo is not by the author and is not updated also

@imdsafi09
Copy link

@abhigoku10 thanks for your reply. I am already working on your mentioned repo but i want to use it with vlp-16 and that case i dont know how to train it for my own data because the KITTI data set you know is based on vlp-64

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

4 participants