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Train with dota-train-dataset(1024,14384files),the mAP on dota-val-dataset is 70.84 #4
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For training on the train dataset,evaluation on the val dataset. My results can gain the mAP:73.37447 I guess that your results are resulted by these three aspects:
If you have any questions for this problem, please let me know. I'll try to help you to get the normal results. |
Yeah,the learning rate does have a significant impact on results. I got the mAP65 when the environment is 2 Tesla P40,4 imgs per gpu,lr=0.01(train on train-dota-dataset, test on val-dota-dataset). |
Have you tried mixed precision training? |
I haven't tried the mixed precision training to train this model. |
Thank you for your code, I'm learning how to use it, but I've had some problems and hope to get your help.
config: orientedreppoints_r50_demo.py
changes:
img_per_gpu=2 -> img_per_gpu=4
workers_per_gpu=2 -> workers_per_gpu=4
lr=0.01 -> lr=0.005
environment: 2 gpu(Tesla P40)
about mAP on val: 70.84.
classaps:[89.43 73.79 40.19 66.33 73.53 82.06 88.16 90.86 60.59 86.46 65.51 64.86 71.29 57.60 51.94 ]
my question: I use your checkpoints(form trainval-dataset) to detect dota-val-dataset and the mAP is about 82.
But the mAP 70.84(checkpoints form train-dota-dataset, test on val) feels lower than I expected(73 ~ 75). Is this normal?
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