niki-amini-naieni / countx Goto Github PK

Nice work!
Thanks for sharing the code！
with your train command:
the result are
val:Test MAE: 21.80, Test RMSE: 73.82
test:Test MAE: 20.23, Test RMSE: 106.87
with cuda 11.8 torch 2.0.0 GPU 4090
In you code, the MAE and RMSE for the validation set was Calculated for each epoch. but, I change it into every 20 epochs
and the batch size was set to 48, 1000 epochs.
For reproducing your accuracy, should I change the batch size into 8, and Calculate MAE and RMSE for each epoch?

So far, I followed the instructions in setting up the environment and completing the preparation steps.

Now, I am trying to run inference. I assume I have to change --im_dir, --FSC147_anno_file, and --data_split_file, but am facing problems understanding what --FSC147_anno_file and --data_split_file are referring to and where I can get them.

Are these files that happen to be generated during training? I wanted to use the existing baseline model for inference rather than training.

python test.py --data_split "val" --output_dir "./test" --resume "./results/checkpoint-1000.pth" --img_dir "/scratch/local/hdd/nikian/images_384_VarV2" --FSC147_anno_file "/scratch/local/hdd/nikian/annotation_FSC147_384.json" --FSC147_D_anno_file "./FSC-147-D.json" --data_split_file "/scratch/local/hdd/nikian/Train_Test_Val_FSC_147.json"

This repository uses timm==0.3.2, for which a fix is needed to work with PyTorch 1.8.1+. This fix can be implemented by replacing the file timm/models/layers/helpers.py in the timm codebase with the file helpers.py provided in this repository.

how can i change this one, please help me trough

Thank you for your excellent work, could you please provide the test code of CounTX on the CARPK dataset?

Thanks for the interesting insights!

Will you be releasing the code and CLIP model weight soon? Thanks in advance!

Hello author!
Thank you very much for your contribution to the scientific research industry. Now, while running your code, in line 126 of modelscounting network.py, the variables img tokens [8512] and fim pos embedded [l, 196512] are "img_tokens=img_tokens+self. fim pos embedded"., Shape mismatch will result in an error message