How to train YOLOv9 Instance Segmentation on a Custom Dataset

Hello, in the official YOLOv9 repository, the code for training YOLOv9 instance segmentation was updated several hours ago as mentioned in the following links: Is YOLO v9 segmentation task open-sourced? · Issue #174 · WongKinYiu/yolov9 · GitHub
I am a newbie and quite confused about how to export YOLOv9 Instance Segmentation Dataset format from roboflow.
I did a try on YOLOv9 Instance Segmentation on my Roboflow dataset several hours ago but failed, and here is what I did:

  1. I downloaded the latest official YOLOv9 GitHub repository manually instead of downloading it by
git clone

as the latest repository has not been released yet.

  1. Export 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.

  2. train:

python segment/ --epochs 50 --batch 1 --img 1408 --workers 8 --device 0 \
--data /mydatasetroot/data.yaml \
--cfg models/segment/gelan-c-seg.yaml \
--weights /myweightsroot/ \
--name gelan-c-seg --hyp hyp.scratch-high.yaml --no-overlap --close-mosaic 10

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

I searched for the issues in YOLOv9 repository and found this similar issue: During training, these parameters are all 0 --- P, R, mAP50 · Issue #252 · WongKinYiu/yolov9 · GitHub
and the author said referring to his warning messages, it may be because his labels are not in the correct format. But I have not got any warning messages on my labels’ format, so I think my situation is not quite the same as his.

It would be constructive if anyone could provide a demo jupyter notebook on how to train YOLOv9 Instance Segmentation on a custom dataset exported from Roboflow platform.
I appreciate your patience in reading these.

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