Chasel-Tsui / mmrotate-dcfl

Official implementation of the CVPR23 paper: Dynamic Coarse-to-Fine Learning for Oriented Tiny Object Detection
Apache License 2.0
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accuracy on DOTA v2.0 dataset #16

Open wjs0725 opened 11 months ago

wjs0725 commented 11 months ago

Thanks for your great work. But when I use your config dotav2_test_dcfl_r50_1x.py to train the model on DOTA v2.0 dataset, I only achieve 28.86% map on test set.

this is the command used for training the model: python -u tools/train.py /cluster/home3/wjs/mmrotate-dcfl/configs/dcfl/dotav2_test_dcfl_r50_1x.py --work-dir='./ckpt/dota2_4_dcfl'

and the log is shown below: 20231013_021328.log.json

After training, I generate the model's prediction on test set through: python ./tools/test.py /cluster/home3/wjs/mmrotate-dcfl/configs/dcfl/dotav2_test_dcfl_r50_1x.py ./ckpt/dota2_4_dcfl/epoch_12.pth --format-only --eval-options submission_dir="./ckpt/dota2_4_dcfl/Task1_results"

then I submit the file to the online server, and this is the email I recieve:

image

I feel confused about the large gap on the result. Could you help me with this problem? Thank you very much!

Chasel-Tsui commented 11 months ago

Hi, thanks for your interest in our work. The training log looks good, and the validation performance looks good on the val set. Did you modify anything related to the config? and could you please check the image number of the test set to make sure that the full set set is used. Besides, maybe you can take a look at the generated submission files to verify whether the prediction results are in the correct format.

622tongtong commented 1 month ago

Hi, thanks for your interest in our work. The training log looks good, and the validation performance looks good on the val set. Did you modify anything related to the config? and could you please check the image number of the test set to make sure that the full set set is used. Besides, maybe you can take a look at the generated submission files to verify whether the prediction results are in the correct format.

Hi, thanks for your sharing. I would like to know the number of trainval images and test images after splitting. Cause I also get a low mAP.

LW091 commented 1 week ago

Thanks for your great work. But when I use your config dotav2_test_dcfl_r50_1x.py to train the model on DOTA v2.0 dataset, I only achieve 28.86% map on test set.

this is the command used for training the model: python -u tools/train.py /cluster/home3/wjs/mmrotate-dcfl/configs/dcfl/dotav2_test_dcfl_r50_1x.py --work-dir='./ckpt/dota2_4_dcfl'

and the log is shown below: 20231013_021328.log.json

After training, I generate the model's prediction on test set through: python ./tools/test.py /cluster/home3/wjs/mmrotate-dcfl/configs/dcfl/dotav2_test_dcfl_r50_1x.py ./ckpt/dota2_4_dcfl/epoch_12.pth --format-only --eval-options submission_dir="./ckpt/dota2_4_dcfl/Task1_results"

then I submit the file to the online server, and this is the email I recieve: image

I feel confused about the large gap on the result. Could you help me with this problem? Thank you very much!

Have you solved the problem? My results are also lower than the paper.