about effect

[ily666666]

I download your code,and train it according to the readme.txt, but when I train it 150 epoches,Its mIOU up to 82.47%.So ,can you tell me how should I train to achieve the effect of the essay.

[ily666666]

backbone is resnet50

[juhongm999]

Can you provide us the command that you run?
On which benchmark are you training the model?
Also, which mIoU are you talking about (training/validation)?

[ily666666]

python train.py --backbone resnet50 --benchmark fss --lr 1e-3 --bsz 10
And this is one info in log.txt
*** Validation [@epoch 138] Avg L: 0.12781 mIoU: 82.47 FB-IoU: 89.57 ***

[ily666666]

Sorry ,I don't mean anything else, I am just puzzled

[juhongm999]

Training HSNet on FSS-1000 dataset takes approximately 3 days until convergence (when trained with four 2080 Ti GPUs).
If you are training with one GPU only, it will take longer.
As you see in our tensorboard log we provided in the README.md (https://drive.google.com/file/d/1i9WlwCEqK4XOdBRh0nShtxxEdWe-1q_r/view), the best model is retrieved when the validation mIoU is the highest (82.85) at epoch 731 (as seen below).

Also FSS-1000 consists of training/validation/test splits. The model (having val mIoU of 82.85) should be further tested using command below:

python test.py --backbone resnet50 --benchmark fss --nshot 1 --load "path_to_trained_model/best_model.pt"

which gives 1-shot results of 85.5 (mIoU) on the test split of FSS-1000.
If you have any further issues, please leave us a comment.