Closed aimuch closed 4 years ago
It should be caused by importing a package in DOTA_devkit. Try to add this folder into PYTHONPATH
:
cd maskrcnn_benchmark/DOTA_devkit
export PYTHONPATH=$PYTHONPATH:`pwd`
@MingtaoFu Thx, It works.
echo $PYTHONPATH
$ /root/gliding_vertex/maskrcnn_benchmark/:/root/gliding_vertex/maskrcnn_benchmark/DOTA_devkit/
But, there is another error, when I run python -m torch.distributed.launch --nproc_per_node=3 tools/train_net.py --config-file configs/glide/dota.yaml
:
ModuleNotFoundError: No module named 'maskrcnn_benchmark'
Could you please post the complete error information?
Could you please post the complete error information?
(pytorch) root@e62aafd8a04c:~/gliding_vertex# python -m torch.distributed.launch --nproc_per_node=1 tools/train_net.py --config-file configs/glide/dota.yaml
configs/glide/dota.yaml
Traceback (most recent call last):
File "tools/train_net.py", line 206, in
I have re-cloned this project and checked it. The line cfg.merge_from_file(args.config_file)
runs normally. Have you modified some parts of this project?
Generally, this problem occurs when the key in dota.yaml is not in gliding_vertex/maskrcnn_benchmark/config/defaults.py
. Please ensure that INPUT.RANDOM_ROTATE_ON
is in the file.
I have re-cloned this project and checked it. The line
cfg.merge_from_file(args.config_file)
runs normally. Have you modified some parts of this project? Generally, this problem occurs when the key in dota.yaml is not ingliding_vertex/maskrcnn_benchmark/config/defaults.py
. Please ensure thatINPUT.RANDOM_ROTATE_ON
is in the file.
Thx, It works. My GPU only has 8 G, I try change IMS_PER_BATCH to small or change input size。 It still reminds that out of memory of GPU.
You can try to change the parameter: ‘numworkers’
@aimuch @xs-trinity-lwei
I think it is not caused by num_workers
because it only affect the speed of loading data. Empirically, I think it is caused by the too large IoU matrix. In fact, if you refer to the issues of Maskrcnn_benchmark
, you can see that many people suffer from it.
We faced this problem, too, even if we used titan xp with 12GB memory. To address this problem, we decompose the computation of IoU matrix. You can find the snippets in related Python files. There is a variable that controls the decomposition grain, try to tune it.
Hi, when I run
python prepare.py
, there is error: