A Step-by-Step Guide to Enhancing Images with Advanced AI Models

				
					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. This will process the image in smaller patches and then stitch them back together.\n')

# If your system runs out of memory, set test_patch_wise = True to process images in smaller patches.
# This helps avoid out-of-memory errors by handling each patch independently.
test_patch_wise = False

# Clean up existing directories to avoid conflicts with BSRGAN
!rm -r BSRGAN/testsets/RealSRSet
upload_folder = 'BSRGAN/testsets/RealSRSet'
result_folder = 'results'

# Check if the upload and result directories exist, and remove them if they do.
if os.path.isdir(upload_folder):
    shutil.rmtree(upload_folder)  # Clear the upload directory to start fresh.
if os.path.isdir(result_folder):
    shutil.rmtree(result_folder)  # Clear the result directory to avoid conflicts.

# Create new directories for the uploaded images and results.
os.mkdir(upload_folder)
os.mkdir(result_folder)

# Upload images for testing. You can select multiple images for batch processing.
uploaded = files.upload()

# Move each uploaded image to the designated folder for processing.
for filename in uploaded.keys():
  dst_path = os.path.join(upload_folder, filename)
  print(f'Moving {filename} to {dst_path}')
  shutil.move(filename, dst_path)