123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128 |
- import glob
- import os
- import cv2
- import argparse
- import shutil
- import math
- from PIL import Image
- import numpy as np
- def resize_images(src_img_folder, dst_img_folder, max_resolution="512x512", divisible_by=2, interpolation=None, save_as_png=False, copy_associated_files=False):
- # Split the max_resolution string by "," and strip any whitespaces
- max_resolutions = [res.strip() for res in max_resolution.split(',')]
- # # Calculate max_pixels from max_resolution string
- # max_pixels = int(max_resolution.split("x")[0]) * int(max_resolution.split("x")[1])
- # Create destination folder if it does not exist
- if not os.path.exists(dst_img_folder):
- os.makedirs(dst_img_folder)
- # Select interpolation method
- if interpolation == 'lanczos4':
- cv2_interpolation = cv2.INTER_LANCZOS4
- elif interpolation == 'cubic':
- cv2_interpolation = cv2.INTER_CUBIC
- else:
- cv2_interpolation = cv2.INTER_AREA
- # Iterate through all files in src_img_folder
- img_exts = (".png", ".jpg", ".jpeg", ".webp", ".bmp") # copy from train_util.py
- for filename in os.listdir(src_img_folder):
- # Check if the image is png, jpg or webp etc...
- if not filename.endswith(img_exts):
- # Copy the file to the destination folder if not png, jpg or webp etc (.txt or .caption or etc.)
- shutil.copy(os.path.join(src_img_folder, filename), os.path.join(dst_img_folder, filename))
- continue
- # Load image
- # img = cv2.imread(os.path.join(src_img_folder, filename))
- image = Image.open(os.path.join(src_img_folder, filename))
- if not image.mode == "RGB":
- image = image.convert("RGB")
- img = np.array(image, np.uint8)
- base, _ = os.path.splitext(filename)
- for max_resolution in max_resolutions:
- # Calculate max_pixels from max_resolution string
- max_pixels = int(max_resolution.split("x")[0]) * int(max_resolution.split("x")[1])
- # Calculate current number of pixels
- current_pixels = img.shape[0] * img.shape[1]
- # Check if the image needs resizing
- if current_pixels > max_pixels:
- # Calculate scaling factor
- scale_factor = max_pixels / current_pixels
- # Calculate new dimensions
- new_height = int(img.shape[0] * math.sqrt(scale_factor))
- new_width = int(img.shape[1] * math.sqrt(scale_factor))
- # Resize image
- img = cv2.resize(img, (new_width, new_height), interpolation=cv2_interpolation)
- else:
- new_height, new_width = img.shape[0:2]
- # Calculate the new height and width that are divisible by divisible_by (with/without resizing)
- new_height = new_height if new_height % divisible_by == 0 else new_height - new_height % divisible_by
- new_width = new_width if new_width % divisible_by == 0 else new_width - new_width % divisible_by
- # Center crop the image to the calculated dimensions
- y = int((img.shape[0] - new_height) / 2)
- x = int((img.shape[1] - new_width) / 2)
- img = img[y:y + new_height, x:x + new_width]
- # Split filename into base and extension
- new_filename = base + '+' + max_resolution + ('.png' if save_as_png else '.jpg')
- # Save resized image in dst_img_folder
- # cv2.imwrite(os.path.join(dst_img_folder, new_filename), img, [cv2.IMWRITE_JPEG_QUALITY, 100])
- image = Image.fromarray(img)
- image.save(os.path.join(dst_img_folder, new_filename), quality=100)
- proc = "Resized" if current_pixels > max_pixels else "Saved"
- print(f"{proc} image: {filename} with size {img.shape[0]}x{img.shape[1]} as {new_filename}")
- # If other files with same basename, copy them with resolution suffix
- if copy_associated_files:
- asoc_files = glob.glob(os.path.join(src_img_folder, base + ".*"))
- for asoc_file in asoc_files:
- ext = os.path.splitext(asoc_file)[1]
- if ext in img_exts:
- continue
- for max_resolution in max_resolutions:
- new_asoc_file = base + '+' + max_resolution + ext
- print(f"Copy {asoc_file} as {new_asoc_file}")
- shutil.copy(os.path.join(src_img_folder, asoc_file), os.path.join(dst_img_folder, new_asoc_file))
- def setup_parser() -> argparse.ArgumentParser:
- parser = argparse.ArgumentParser(
- description='Resize images in a folder to a specified max resolution(s) / 指定されたフォルダ内の画像を指定した最大画像サイズ(面積)以下にアスペクト比を維持したままリサイズします')
- parser.add_argument('src_img_folder', type=str, help='Source folder containing the images / 元画像のフォルダ')
- parser.add_argument('dst_img_folder', type=str, help='Destination folder to save the resized images / リサイズ後の画像を保存するフォルダ')
- parser.add_argument('--max_resolution', type=str,
- help='Maximum resolution(s) in the format "512x512,384x384, etc, etc" / 最大画像サイズをカンマ区切りで指定 ("512x512,384x384, etc, etc" など)', default="512x512,384x384,256x256,128x128")
- parser.add_argument('--divisible_by', type=int,
- help='Ensure new dimensions are divisible by this value / リサイズ後の画像のサイズをこの値で割り切れるようにします', default=1)
- parser.add_argument('--interpolation', type=str, choices=['area', 'cubic', 'lanczos4'],
- default='area', help='Interpolation method for resizing / リサイズ時の補完方法')
- parser.add_argument('--save_as_png', action='store_true', help='Save as png format / png形式で保存')
- parser.add_argument('--copy_associated_files', action='store_true',
- help='Copy files with same base name to images (captions etc) / 画像と同じファイル名(拡張子を除く)のファイルもコピーする')
- return parser
- def main():
- parser = setup_parser()
- args = parser.parse_args()
- resize_images(args.src_img_folder, args.dst_img_folder, args.max_resolution,
- args.divisible_by, args.interpolation, args.save_as_png, args.copy_associated_files)
- if __name__ == '__main__':
- main()
|