- Implementation of Non-local Neural Block.
- You can find different kinds of non-local block in lib/.
- The code is tested on MNIST dataset. You can select the type of non-local block in lib/network.py.
- If there is something wrong in my code, please contact me, thanks!
- python 3.6
- pytorch 0.4.1
- Figure out how to implement the concatenation type, and add the code to lib/.
- Fix the bug in lib/non_local.py (old version) when using multi-gpu. Someone shares the reason with me, and you can find it in here.
- Fix the error of 3D pooling in lib/non_local.py (old version). Appreciate protein27 for pointing it out.
- For convenience, I split the lib/non_local.py into four python files, and move the old versions (lib/non_loca.py and lib/non_local_simple_version.py) into lib/backup/.
- modify the code to support pytorch 0.4.1, and move the code supporting pytorch 0.3.1
to Non-Local_pytorch_0.3.1/.
- Select the type of non-local block in lib/network.py.
from lib.non_local_concatenation import NONLocalBlock2D from lib.non_local_gaussian import NONLocalBlock2D from lib.non_local_embedded_gaussian import NONLocalBlock2D from lib.non_local_dot_product import NONLocalBlock2D - Run demo_MNIST.py with one GPU or multi GPU.
CUDA_VISIBLE_DEVICES=0,1 python demo_MNIST.py
- Experiments on Kinetics dataset.
- Experiments on Charades dataset.
- Experiments on COCO dataset.
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