box_loss, obj_loss, and cls_loss

[karl-gardner]

Hello Glenn et al.,

I am wondering what all the different losses mean in the results figure and where I can learn more about this? If you can give the equations for these losses that would be great. Specifically the box, obj, and cls loss? Is the box loss referring to the Generalized IOU loss (GIOU).

Thanks,

Karl Gardner | Texas Tech University

[glenn-jocher]

@kgardner330 box loss is the regression loss for output xywh bounding boxes. Loss criteria in use is CIoU(). You can see details in loss.py: https://github.com/ultralytics/yolov5/blob/5afc9c25ef0874dff0c18267947ea4e8b03c90f4/utils/loss.py#L131-L137

For a general description of the YOLO losses you should read the first 3 YOLO papers: https://pjreddie.com/publications/

[gepaohhh]

Hello Glenn et al., I am wonder why there is nothing in my graphics, weather is something wrong in my CUDA version

[glenn-jocher]

@gepaohhh you are showing mAP so you do have validation data, not sure why your losses are nan (which are not plotted).

[gepaohhh]

@glenn-jocher thankyou, later I found my losses are nan (which are not plotted) ,because there is something wrong in my CUDA and cuDNN, and the official network say due to my CUDA which is not suitable to my Convolution so you considered my dataset is good ? but i wonder if I only have one class of dataset , wheather this could effect my results ?, and can you give me some tips about 1 class train in yolov5 ? thank you

I'm sorry my english is not very well

[glenn-jocher]

@gepaohhh no changes are needed for single-class training, just label your dataset with class 0 and train normally.