Can you provide the right utils/datasets.py file?

[hnuzhy]

I got an error when running the train process.
assert nf > 0 or not augment, f'{prefix}No labels in {cache_path}. Can not train without labels. See {HELP_URL}'
It shows that the provided utils/datasets.py file seems wrong for not changing into loading keypoints json file. So, could you please provide the right utils/datasets.py file?

[wmcnally]

Which training command are you running? If you're doing COCO training, did you download the coco dataset? If not, from the main project folder run sh data/scripts/get_coco_kp.sh

[hnuzhy]

Thank you for your answer! I'm running the COCO training KAPAO-L. Below is my running script

python -m torch.distributed.launch --nproc_per_node 3 train.py --workers 15 --device 0,1,2 \
    --img 1280 --batch 48 --epochs 500 --data data/coco-kp.yaml --hyp data/hyps/hyp.kp-p6.yaml \
    --val-scales 1 --val-flips -1 --weights yolov5l6.pt --project runs/kapao --name train_coco2017_e500

Actually, I have downloaded and built my COCO dataset project. And I have also checked the script data/scripts/get_coco_kp.sh to find some config information that might be ignored by me. It actually did not change the annotations/labels of COCO keypoints. So I still got the same error when running the train process.

Until now, I have two questions:

1. What's the meaning of kp_labels in data/coco-kp.yaml? I wrote the txt file kp_labels/train2017.txt with paths of training images. Am I right?
2. Does the kapao rewrite the dataset processing script utils/datasets.py? It is originally designed for the dataloader of object detection task YOLOv5. And I did not find the loading and parsing scripts of COCO json keypoints person_keypoints_train2017.json and person_keypoints_val2017.json in the new utils/datasets.py file.

[hnuzhy]

Which training command are you running? If you're doing COCO training, did you download the coco dataset? If not, from the main project folder run sh data/scripts/get_coco_kp.sh

While, I have found the utils/labels.py file and run it to generate suitable COCO labels for kapao. Now, the training is running normally~ By the way, the totally epoch is set to 500 which is super large and time-consuming for my 3*3090GPUs (24GB/per). Should it be that large for KAPAO-L convergence?

[wmcnally]

You could run for 300 epochs and get close to the same results.

[hnuzhy]

You could run for 300 epochs and get close to the same results.

OK, thank you for your advice :-)