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# 資專研究札記By賴昱錡 (Nov.&Dec.)
## 2022/11/8
Comparison of deep learning methods for colorizing historical aerial imagery
https://meetingorganizer.copernicus.org/EGU22/EGU22-7686.html
ColorAI -Automatic Image Colorization using CycleGAN
https://www.researchgate.net/publication/350957456_ColorAI_-Automatic_Image_Colorization_using_CycleGAN
CycleGAN model:
https://github.com/junyanz/CycleGAN
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
+ Create a dataset folder under /dataset for your dataset.
+ Create subfolders testA, testB, trainA, and trainB under your dataset's folder. Place any images you want to transform from a to b (cat2dog) in the testA folder, images you want to transform from b to a (dog2cat) in the testB folder, and do the same for the trainA and trainB folders.
Tensorflow Datasets:
https://www.tensorflow.org/datasets?hl=zh-tw
## 2022/11/10
Visdom's Github
https://github.com/fossasia/visdom
CycleGan-horse2zebra
https://machinelearningmastery.com/cyclegan-tutorial-with-keras/
GANILLA:
https://github.com/giddyyupp/ganilla
https://arxiv.org/abs/2002.05638
## 2022/11/15
各種 GAN 的延伸:
https://github.com/NVIDIA/pix2pixHD
https://github.com/taesungp/contrastive-unpaired-translation
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/docs/tips.md#notes-on-colorization
https://yanwei-liu.medium.com/wandb-weights-and-biases-a-better-choice-over-tensorboard-6c75b5f972b1
## 2022/11/17
pix2pix原理
https://blog.csdn.net/weixin_36474809/article/details/89004841
CycleGAN原理
https://blog.csdn.net/qq_40520596/article/details/104714762
Python 的 gdown 套件
https://clay-atlas.com/blog/2020/03/13/python-chinese-note-package-gdown-download-google-drive/
各種 GAN
https://github.com/eriklindernoren/PyTorch-GAN
2022/11/25
pix2pix model 的 instruction
`
Change the --dataroot and --name to your own dataset's path and model's name. Use --gpu_ids 0,1,.. to train on multiple GPUs and --batch_size to change the batch size. Add --direction BtoA if you want to train a model to transfrom from class B to A.
`
maptiles 的截圖
https://github.com/riatelab/maptiles/
https://github.com/AliFlux/MapTilesDownloader
Linux scp指令應用:
https://blog.gtwang.org/linux/linux-scp-command-tutorial-examples/
Kaggle pix2pix datasets
https://www.kaggle.com/datasets/vikramtiwari/pix2pix-dataset
## 2022/12/1
pandas&matplotlib
https://www.learncodewithmike.com/2021/03/pandas-and-matplotlib.html
## 2022/12/5
Notes on Colorization
```!
No need to run combine_A_and_B.py for colorization. Instead, you need to prepare natural images and set --dataset_mode colorization and --model colorization in the script. The program will automatically convert each RGB image into Lab color space, and create L -> ab image pair during the training. Also set --input_nc 1 and --output_nc 2. The training and test directory should be organized as /your/data/train and your/data/test. See example scripts scripts/train_colorization.sh and scripts/test_colorization for more details.
```
## 2022/12/8
https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/issues/1161
https://paperswithcode.com/task/image-colorization?fbclid=IwAR0AI_17vmTLvfdrpL_chgWyOcGFon-Q7aa54IxFh1cXxUJ2tJ6pKu74EpM
## 2022/12/14
找度量模型成效的方法:
FID score
https://github.com/mseitzer/pytorch-fid
https://blog.csdn.net/weixin_43135178/article/details/120621393
## 2022/12/15
FID evaluating
pytorch_fid ./Fake ./Real
FID: 49.12806924497005
pix2pix testing options
```oython=
def initialize(self, parser):
parser = BaseOptions.initialize(self, parser) # define shared options
parser.add_argument('--results_dir', type=str, default='./results/', help='saves results here.')
parser.add_argument('--aspect_ratio', type=float, default=1.0, help='aspect ratio of result images')
parser.add_argument('--phase', type=str, default='test', help='train, val, test, etc')
# Dropout and Batchnorm has different behavioir during training and test.
parser.add_argument('--eval', action='store_true', help='use eval mode during test time.')
parser.add_argument('--num_test', type=int, default=50, help='how many test images to run')
# rewrite devalue values
parser.set_defaults(model='test')
# To avoid cropping, the load_size should be the same as crop_size
parser.set_defaults(load_size=parser.get_default('crop_size'))
self.isTrain = False
return parser
```
CUT model
https://blog.csdn.net/qq_37614597/article/details/114671050
科展報告書撰寫模板
https://twsf.ntsec.gov.tw/activity/race-1/58/pdf/NPHSF2018-052511.pdf
初步測試結果:
https://hackmd.io/@expectlai/rkkJffR_s
TTUR
https://github.com/bioinf-jku/TTUR