Since I used our campus server, the CUDA version is 10.1 and should be unchangeable. Other parts were according to the installations. I ran the following command for inference:
/
srun -u --gres=gpu:1 -c 4 python3 inference_ytvos.py --with_box_refine --binary --freeze_text_encoder --output_dir ytvos_dirs/resnet_50 --resume r50_refytvos_finetune.pth --backbone resnet50 --visualize --ytvos_path /nfs/data3/shuaicong/ref-youtube-vos --batch_size 1
/
The results seemed bad. Even in the valid folder most of them are white images.
Also for some videos, 4 or 5 folders were generated, but for some of them maybe there were just two.
Therefore, the evaluation result was undoubtedly very low. J was 0.106 and F was 0.087.
Q1: I want to make sure that the values of the paper and competition server matched, even though it was a two-digit number in the paper, in the evaluation it was three decimal places, like a percent sign was added to the number in the paper, right?
Q2: Please check whether the command is correct or not and are there any ways to improve the performance of inference? I have no idea how to improve the results if the installation parts and the inference command are both okay...
Q3: --resume r50_refytvos_finetune.pth or --resume r50_pretrain.pth? Although I ran them both with similar results.
Thank you in advance!
wjn922
