During training, these parameters are all 0 --- P, R, mAP50

[Dapao7777]

During training, these parameters are all 0 --- P, R, mAP50. My device is RTX4090. I changed half() and amp to float() and False. It is useless and a warning will appear. Here are a few screenshots of the training process:

[Dapao7777]

Ask for advice

[Youho99]

It's normal
Look at your warning message. Your labels are not in the correct format

[txctxc]

Several hours ago, I downloaded the latest official YOLOv9 GitHub repository manually instead of downloading it by

git clone https://github.com/SkalskiP/yolov9.git

as the latest repository has not been released yet.
Then I exported YOLOv9 format from my Roboflow dataset version. I have used this dataset format for YOLOv9 Object Detection and it works fine. Now I want to use the same dataset format for YOLOv9 Instance Segmentation. In Roboflow platform, my dataset is well-annotated by polygon masks.

python segment/train.py --epochs 50 --batch 1 --img 1408 --workers 8 --device 0 \
--data /root/autodl-tmp/yolov9/AutoKary2022-2/data.yaml \
--cfg models/segment/gelan-c-seg.yaml \
--weights /root/autodl-tmp/weights/gelan-c-seg.pt \
--name gelan-c-seg --hyp hyp.scratch-high.yaml --no-overlap --close-mosaic 10

where I used this code for training: https://github.com/WongKinYiu/yolov9/blob/main/segment/train.py
as the training process continued, I found something went wrong. The P, R, and mAP50 values all became 0 after epoch 3:

The detailed log is as follows:
detailedLog.txt

But I have not got any warning messages on my labels' format, so I think my situation is not quite the same as yours.

Any advice on how to fix this?
Best regards.

[Youho99]

Several hours ago, I downloaded the latest official YOLOv9 GitHub repository manually instead of downloading it by

git clone https://github.com/SkalskiP/yolov9.git

as the latest repository has not been released yet. Then I exported YOLOv9 format from my Roboflow dataset version. I have used this dataset format for YOLOv9 Object Detection and it works fine. Now I want to use the same dataset format for YOLOv9 Instance Segmentation. In Roboflow platform, my dataset is well-annotated by polygon masks.

python segment/train.py --epochs 50 --batch 1 --img 1408 --workers 8 --device 0 \
--data /root/autodl-tmp/yolov9/AutoKary2022-2/data.yaml \
--cfg models/segment/gelan-c-seg.yaml \
--weights /root/autodl-tmp/weights/gelan-c-seg.pt \
--name gelan-c-seg --hyp hyp.scratch-high.yaml --no-overlap --close-mosaic 10

where I used this code for training: https://github.com/WongKinYiu/yolov9/blob/main/segment/train.py as the training process continued, I found something went wrong. The P, R, and mAP50 values all became 0 after epoch 3:

The detailed log is as follows: detailedLog.txt

But I have not got any warning messages on my labels' format, so I think my situation is not quite the same as yours.

Any advice on how to fix this? Best regards.

This problem is not the same
Personally, I haven't tried segmentation.
Opens a new issue for this please

[cza0426]

So do I. During training, these parameters are 0 -- P, R, mAP50. The values of box_loss, cls_loss, and dfl_loss are NAN. My device RTX4060ti. How to solve it?