【SwinIR】その画質で公開するんですか？画像のクオリティーを爆上げする超解像AI

前置き

ユーザーさんにとってプロフィール画像など
すべてにおける画像は質が高いほうが信頼度が増します

信頼は個人でも企業でも最もと言っても過言ではないほど重要な指標です

Before After

早速ですが、Before Afterをご覧ください。

Before

After

環境

・Google Colab

SwinIRのGitHub URL

画像のクオリティーを上げるソースコード

・realESRGANをクローン
・環境に必要パッケージをインストール
・BSRGANをクローン
・SwinIRをクローン
・モデルをダウンロード

# Clone realESRGAN
!git clone https://github.com/xinntao/Real-ESRGAN.git
%cd Real-ESRGAN
# Set up the environment
!pip install basicsr
!pip install facexlib
!pip install gfpgan
!pip install -r requirements.txt
!python setup.py develop

# Clone BSRGAN
!git clone https://github.com/cszn/BSRGAN.git

!rm -r SwinIR
# Clone SwinIR
!git clone https://github.com/JingyunLiang/SwinIR.git
!pip install timm

# Download the pre-trained models
!wget https://github.com/cszn/KAIR/releases/download/v1.0/BSRGAN.pth -P BSRGAN/model_zoo
!wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P experiments/pretrained_models
!wget https://github.com/JingyunLiang/SwinIR/releases/download/v0.0/003_realSR_BSRGAN_DFO_s64w8_SwinIR-M_x4_GAN.pth -P experiments/pretrained_models
!wget https://github.com/JingyunLiang/SwinIR/releases/download/v0.0/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth -P experiments/pretrained_models

・画像をパッチに分割してSwinIRをテスト
・BSRGANとの互換性の調整
・画像をアップロード

import os
import glob
from google.colab import files
import shutil
print(' Note1: You can find an image on the web or download images from the RealSRSet (proposed in BSRGAN, ICCV2021) at https://github.com/JingyunLiang/SwinIR/releases/download/v0.0/RealSRSet+5images.zip.\n Note2: You may need Chrome to enable file uploading!\n Note3: If out-of-memory, set test_patch_wise = True.\n')

# test SwinIR by partioning the image into patches
test_patch_wise = False

# to be compatible with BSRGAN
!rm -r BSRGAN/testsets/RealSRSet
upload_folder = 'BSRGAN/testsets/RealSRSet'
result_folder = 'results'

if os.path.isdir(upload_folder):
    shutil.rmtree(upload_folder)
if os.path.isdir(result_folder):
    shutil.rmtree(result_folder)
os.mkdir(upload_folder)
os.mkdir(result_folder)

# upload images
uploaded = files.upload()
for filename in uploaded.keys():
  dst_path = os.path.join(upload_folder, filename)
  print(f'move {filename} to {dst_path}')
  shutil.move(filename, dst_path)

以下をそれぞれ実行
・BSRGAN
・realESRGAN
・SwinIR
・SwinIR-Large

# BSRGAN
!rm -r results
if not test_patch_wise:
  %cd BSRGAN
  !python main_test_bsrgan.py
  %cd ..
  shutil.move('BSRGAN/testsets/RealSRSet_results_x4', 'results/BSRGAN')

# realESRGAN
if test_patch_wise:
  !python inference_realesrgan.py -n RealESRGAN_x4plus --input BSRGAN/testsets/RealSRSet -s 4 --output results/realESRGAN --tile 800
else:
  !python inference_realesrgan.py -n RealESRGAN_x4plus --input BSRGAN/testsets/RealSRSet -s 4 --output results/realESRGAN

# SwinIR
if test_patch_wise:
  !python SwinIR/main_test_swinir.py --task real_sr --model_path experiments/pretrained_models/003_realSR_BSRGAN_DFO_s64w8_SwinIR-M_x4_GAN.pth --folder_lq BSRGAN/testsets/RealSRSet --scale 4 --tile 800
else:
  !python SwinIR/main_test_swinir.py --task real_sr --model_path experiments/pretrained_models/003_realSR_BSRGAN_DFO_s64w8_SwinIR-M_x4_GAN.pth --folder_lq BSRGAN/testsets/RealSRSet --scale 4
shutil.move('results/swinir_real_sr_x4', 'results/SwinIR')

# SwinIR-Large
if test_patch_wise:
  !python SwinIR/main_test_swinir.py --task real_sr --model_path experiments/pretrained_models/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth --folder_lq BSRGAN/testsets/RealSRSet --scale 4 --large_model --tile 640
else:
  !python SwinIR/main_test_swinir.py --task real_sr --model_path experiments/pretrained_models/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth --folder_lq BSRGAN/testsets/RealSRSet --scale 4 --large_model
shutil.move('results/swinir_real_sr_x4_large', 'results/SwinIR_large')
for path in sorted(glob.glob(os.path.join('results/SwinIR_large', '*.png'))):
  os.rename(path, path.replace('SwinIR.png', 'SwinIR_large.png')) # here is a bug in Colab file downloading: no same-name files

各画像の視覚化

# utils for visualization
import cv2
import matplotlib.pyplot as plt
def display(img1, img2):
  total_figs = 5
  fig = plt.figure(figsize=(total_figs*12, 14))
  ax1 = fig.add_subplot(1, total_figs, 1) 
  plt.title('Input image', fontsize=30)
  ax1.axis('off')
  ax2 = fig.add_subplot(1, total_figs, 2)
  plt.title('BSRGAN (ICCV2021) output', fontsize=30)
  ax2.axis('off')
  ax3 = fig.add_subplot(1, total_figs, 3)
  plt.title('Real-ESRGAN output', fontsize=30)
  ax3.axis('off')
  ax4 = fig.add_subplot(1, total_figs, 4)
  plt.title('SwinIR (ours) output', fontsize=30)
  ax4.axis('off')
  ax5 = fig.add_subplot(1, total_figs, 5)
  plt.title('SwinIR-Large (ours) output', fontsize=30)
  ax5.axis('off')
  ax1.imshow(img1)
  ax2.imshow(img2['BSRGAN'])
  ax3.imshow(img2['realESRGAN'])
  ax4.imshow(img2['SwinIR'])
  ax5.imshow(img2['SwinIR-L'])

def imread(img_path):
  img = cv2.imread(img_path)
  img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
  return img

# display each image in the upload folder
print('Note: BSRGAN may be better at face restoration, but worse at building restoration because it uses different datasets in training.')
if test_patch_wise:
  print('BSRGAN does not support "test_patch_wise" mode for now. Set test_patch_wise = False to see its results.\n')
else:
  print('\n')
input_folder = upload_folder
result_folder = 'results/SwinIR'
input_list = sorted(glob.glob(os.path.join(input_folder, '*')))
output_list = sorted(glob.glob(os.path.join(result_folder, '*')))
for input_path, output_path in zip(input_list, output_list):
  img_input = imread(input_path)
  img_output = {}
  img_output['SwinIR'] = imread(output_path)
  img_output['SwinIR-L'] = imread(output_path.replace('SwinIR/', 'SwinIR_large/').replace('SwinIR.png', 'SwinIR_large.png'))
  if test_patch_wise:
    img_output['BSRGAN'] = img_output['SwinIR']*0+255
  else:
    img_output['BSRGAN'] = imread(output_path.replace('SwinIR', 'BSRGAN'))
  path = output_path.replace('/SwinIR/', '/realESRGAN/').replace('_SwinIR.png','_out{}'.format(os.path.splitext(input_path)[1]))
  if os.path.exists(path):
    shutil.move(path, path.replace('_out.', '_realESRGAN.'))
  img_output['realESRGAN'] = imread(path.replace('_out.', '_realESRGAN.'))

  display(img_input, img_output)

画像のダウンロード

# Download the results
zip_filename = 'SwinIR_result.zip'
if os.path.exists(zip_filename):
  os.remove(zip_filename)
os.system(f"zip -r -j {zip_filename} results/*")
files.download(zip_filename)

実際に以下のようにダウンロードされます

まとめ

神は細部に宿るということで

画質という些細な事でも気にかけることで

一流に近づくんじゃないかなと...

以上です

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