iizukak / torchart

Experimental Art Projects with PyTorch

torchart

Experimental Art Projects with PyTorch

Installation

$ pip3 install -r ./requirements.txt
$ export PYTHONPATH="$PWD:$PYTHONPATH"

Filter Visualization

Sample Outputs

These images are visualized filters for VGG16 filters. Model is from torchvision's pretrained model.

You can check sample images in this directory.

Layer: model.features[3], Filter: 34(Left) 39(Center), 52(Right)

Layer: model.features[10], Filter: 1(Left) 163(Center) 237(Right)

Layer: model.features[29], Filter: 33(Left) 132(Center), 390(Right)

Usage

You can use layer and filters options to specify target number of layer and filters.

$ python3 torchart/filtervisualization/main.py
$ python3 torchart/filtervisualization/main.py layer=3 filters='[23, 34, 39, 52]'
$ python3 torchart/filtervisualization/main.py layer=10 filters='[1, 161, 163, 237, 241]'
$ python3 torchart/filtervisualization/main.py layer=29 filters='[5, 33, 132, 177, 241, 286, 312]'

If you want to change more hyper parametrs, Please check torchart/filtervisualization/config.yaml. We are using hydra. And you can change hyper parameters as command line arguments.

Output directory structure is

outputs
└── yyyy-mm-dd
    ├── hh-mm-ss
    │   ├── main.log
    │   ├── vgg16_{layer_number}_{filter_number}.png
...

Unit Test and Code Formart Checking

pytest

$ pytest torchart

flake8

$ flake8 torchart

mypy

$ mypy torchart

isort

$ isort -c torchart