TF for Detection / SS

conda create -n 가상환경명 python=3.7 -y

conda activate 가상환경명
conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.1 -c pytorch -y

 

(dat-det) mmlab@mmlab-TitanX9-mango:~/Projects/dat-det$ export PATH="/home/mmlab/anaconda3/envs/dat-det/bin:$PATH"

 

Package            Version      Editable project location
------------------ ------------ -----------------------------------------------------------------------------------
addict             2.4.0
certifi            2022.12.7
cycler             0.11.0
Cython             0.29.33
fonttools          4.38.0
future             0.18.3
importlib-metadata 6.7.0
kiwisolver         1.4.5
markdown-it-py     2.2.0
matplotlib         3.5.3
mdurl              0.1.2
mkl-fft            1.3.1
mkl-random         1.2.2
mkl-service        2.4.0
mmcv-full          1.4.0
mmdet              2.11.0       /home/mmlab/Projects/swin-detect/Swin-Transformer/Swin-Transformer-Object-Detection
mmengine           0.9.0
mmpycocotools      12.0.3
numpy              1.21.5
opencv-python      4.8.1.78
packaging          23.2
pandas             1.3.5
Pillow             9.4.0
pip                22.3.1
platformdirs       3.11.0
Pygments           2.16.1
pyparsing          3.1.1
python-dateutil    2.8.2
pytz               2023.3.post1
PyYAML             6.0.1
rich               13.6.0
scipy              1.7.3
setuptools         65.6.3
shapely            2.0.2
six                1.16.0
termcolor          2.3.0
terminaltables     3.1.10
timm               0.4.12
tomli              2.0.1
torch              1.6.0
torchvision        0.7.0
tqdm               4.66.1
typing_extensions  4.7.1
wheel              0.38.4
yapf               0.40.1  # TypeError: FormatCode() got an unexpected keyword argument 'verify'

zipp               3.15.0

 

Detection-contest/Swin-Transformer (github.com)

GitHub - Detection-contest/Swin-Transformer

 

 

ImageNet 다운로드 커맨드

## 1. Download the data
# get ILSVRC2012_img_val.tar (about 6.3 GB). MD5: 29b22e2961454d5413ddabcf34fc5622
# wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_val.tar
# get ILSVRC2012_img_train.tar (about 138 GB). MD5: 1d675b47d978889d74fa0da5fadfb00e
# wget https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_train.tar

## 2. Extract the training data:
mkdir train && mv ILSVRC2012_img_train.tar train/ && cd train
tar -xvf ILSVRC2012_img_train.tar && rm -f ILSVRC2012_img_train.tar
find . -name "*.tar" | while read NAME ; do mkdir -p "${NAME%.tar}"; tar -xvf "${NAME}" -C "${NAME%.tar}"; rm -f "${NAME}"; done
cd ..

## 3. Extract the validation data and move images to subfolders:
mkdir val && mv ILSVRC2012_img_val.tar val/ && cd val && tar -xvf ILSVRC2012_img_val.tar
wget -qO- https://raw.githubusercontent.com/soumith/imagenetloader.torch/master/valprep.sh | bash


## 4. Delete corrupted image
# there is one png under JPEG name. some readers fail on this image so need to remove it
# this line is commented by default to avoid such unexpected behaviour
# rm train/n04266014/n04266014_10835.JPEG

## 5. Sometimes TFRecords may be usefull
# wget https://raw.githubusercontent.com/tensorflow/models/master/research/slim/datasets/imagenet_lsvrc_2015_synsets.txt