90c0d55457
- Caption dropout is supported in ``train_db.py``, ``fine_tune.py`` and ``train_network.py``. Thanks to forestsource!
- ``--caption_dropout_rate`` option specifies the dropout rate for captions (0~1.0, 0.1 means 10% chance for dropout). If dropout occurs, the image is trained with the empty caption. Default is 0 (no dropout).
- ``--caption_dropout_every_n_epochs`` option specifies how many epochs to drop captions. If ``3`` is specified, in epoch 3, 6, 9 ..., images are trained with all captions empty. Default is None (no dropout).
- ``--caption_tag_dropout_rate`` option specified the dropout rate for tags (comma separated tokens) (0~1.0, 0.1 means 10% chance for dropout). If dropout occurs, the tag is removed from the caption. If ``--keep_tokens`` option is set, these tokens (tags) are not dropped. Default is 0 (no droupout).
- The bulk image downsampling script is added. Documentation is [here](https://github.com/kohya-ss/sd-scripts/blob/main/train_network_README-ja.md#%E7%94%BB%E5%83%8F%E3%83%AA%E3%82%B5%E3%82%A4%E3%82%BA%E3%82%B9%E3%82%AF%E3%83%AA%E3%83%97%E3%83%88) (in Jpanaese). Thanks to bmaltais!
- Typo check is added. Thanks to shirayu!
- Add option to autolaunch the GUI in a browser and set the server_port. USe either `gui.ps1 --inbrowser --server_port 3456`or `gui.cmd -inbrowser -server_port 3456`
78 lines
4.0 KiB
Python
78 lines
4.0 KiB
Python
import os
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import cv2
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import argparse
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import shutil
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import math
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def resize_images(src_img_folder, dst_img_folder, max_resolution="512x512", divisible_by=1, caption_extension=''):
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# Split the max_resolution string by "," and strip any whitespaces
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max_resolutions = [res.strip() for res in max_resolution.split(',')]
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# Create destination folder if it does not exist
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if not os.path.exists(dst_img_folder):
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os.makedirs(dst_img_folder)
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# Iterate through all files in src_img_folder
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for filename in os.listdir(src_img_folder):
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# Check if the image is png, jpg or webp
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if not filename.endswith(('.png', '.jpg', '.webp')):
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# Copy the file to the destination folder if not png, jpg or webp
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# shutil.copy(os.path.join(src_img_folder, filename), os.path.join(dst_img_folder, filename))
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continue
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# Load image
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img = cv2.imread(os.path.join(src_img_folder, filename))
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for max_resolution in max_resolutions:
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# Calculate max_pixels from max_resolution string
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max_pixels = int(max_resolution.split("x")[0]) * int(max_resolution.split("x")[1])
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# Calculate current number of pixels
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current_pixels = img.shape[0] * img.shape[1]
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# Check if the image needs resizing
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if current_pixels > max_pixels:
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# Calculate scaling factor
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scale_factor = max_pixels / current_pixels
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# Calculate new dimensions
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new_height = int(img.shape[0] * math.sqrt(scale_factor))
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new_width = int(img.shape[1] * math.sqrt(scale_factor))
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# Resize image using area interpolation (best when downsampling)
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img = cv2.resize(img, (new_width, new_height), interpolation=cv2.INTER_AREA)
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# Calculate the new height and width that are divisible by divisible_by
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new_height = new_height if new_height % divisible_by == 0 else new_height - new_height % divisible_by
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new_width = new_width if new_width % divisible_by == 0 else new_width - new_width % divisible_by
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# Center crop the image to the calculated dimensions
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y = int((img.shape[0] - new_height) / 2)
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x = int((img.shape[1] - new_width) / 2)
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img = img[y:y + new_height, x:x + new_width]
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# Split filename into base and extension
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base, ext = os.path.splitext(filename)
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new_filename = base + '+' + max_resolution + '.jpg'
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# copy caption file with right name if one exist
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if os.path.exists(os.path.join(src_img_folder, base + caption_extension)):
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shutil.copy(os.path.join(src_img_folder, base + caption_extension), os.path.join(dst_img_folder, new_filename + caption_extension))
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# Save resized image in dst_img_folder
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cv2.imwrite(os.path.join(dst_img_folder, new_filename), img, [cv2.IMWRITE_JPEG_QUALITY, 100])
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print(f"Resized image: {filename} with size {img.shape[0]}x{img.shape[1]} as {new_filename}")
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def main():
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parser = argparse.ArgumentParser(description='Resize images in a folder to a specified max resolution(s)')
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parser.add_argument('src_img_folder', type=str, help='Source folder containing the images')
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parser.add_argument('dst_img_folder', type=str, help='Destination folder to save the resized images')
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parser.add_argument('--max_resolution', type=str, help='Maximum resolution(s) in the format "512x512,448x448,384x384, etc, etc"', default="512x512,448x448,384x384")
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parser.add_argument('--divisible_by', type=int, help='Ensure new dimensions are divisible by this value', default=1)
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parser.add_argument('--caption_extension', type=str, help='Extension of caption files to copy with resized images"', default=".txt")
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args = parser.parse_args()
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resize_images(args.src_img_folder, args.dst_img_folder, args.max_resolution, args.divisible_by, args.caption_extension)
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if __name__ == '__main__':
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main() |