Stable Diffusion训练图片时，简陋的数据处理

0 图片从命名

如果有强迫症，看到似乎乱码的命名会不舒服，那么就批量从命名

import osdef rename_files_in_directory(directory, key_word, new_suffix):i = 1for filename in os.listdir(directory):new_file = key_word + str(i).zfill(3) + new_suffixsource = os.path.join(directory, filename)destination = os.path.join(directory, new_file)os.rename(source, destination)i += 1
# 使用方法
# rename_files_in_directory('/path/to/directory', '.new_suffix')
# D:\SdTrainerGUI\lora-scripts-v1.7.3\train\XiboBird\5_zkz

1 批量缩小图片分辨率

如果是用同一个相机拍的，分辨率都是一样的，只不过分辨率太大了8K以上的分辨率显卡受不了

from PIL import Image
import osdef resize_image(image_path, output_path, scale_factor):# 打开图片img = Image.open(image_path)# 获取图片的宽度和高度width, height = img.size# 计算新的宽度和高度new_width = width // scale_factornew_height = height // scale_factor# 使用ANTIALIAS滤镜来缩小图片# new_img = img.resize((new_width, new_height), Image.ANTIALIAS)new_img = img.resize((new_width, new_height), Image.ANTIALIAS)# 保存新图片new_img.save(output_path)def get_all_image(path, file_extension=".jpg"):return [os.path.join(path, f) for f in os.listdir(path) if f.endswith(file_extension)]def process_images(catalog_of_original_images, file_extension, scale_factor):# 获取原始图像目录的上一级目录parent_directory = os.path.dirname(catalog_of_original_images)# 设置输出目录output_catalog = os.path.join(parent_directory, "output")# 创建输出目录if not os.path.exists(output_catalog):os.makedirs(output_catalog)image_list = get_all_image(catalog_of_original_images, file_extension)for image in image_list:# 获取图片的文件名image_name = os.path.basename(image)# 设置输出图片的路径output_image_path = os.path.join(output_catalog, image_name)# 缩小图片并保存resize_image(image, output_image_path, scale_factor)if __name__ == '__main__':process_images(r"E:\Dwk\Photos\祥春鸟", ".jpg", 10)

2 图片数据集增强

最简易的增强是图片镜像，就是左右颠倒各一张，图片数据集数量直接翻倍

import os
from PIL import Image, ImageOpsdef data_enhancement(image_catalog, file_extension=".jpg"):image_list = [os.path.join(image_catalog, f) for f in os.listdir(image_catalog) if f.endswith(file_extension)]for image in image_list:# 打开图片img = Image.open(image)# 创建镜像图片mirror_img = ImageOps.mirror(img)# 获取图片的文件名（不包括后缀）image_name = os.path.splitext(os.path.basename(image))[0]# 设置镜像图片的文件名mirror_image_name = image_name + "_mirror" + file_extension# 设置镜像图片的路径mirror_image_path = os.path.join(image_catalog, mirror_image_name)# 保存镜像图片mirror_img.save(mirror_image_path)if __name__ == '__main__':data_enhancement(r"E:\Dwk\Photos\output", ".jpg")

3 tag内容批量修改（这里是只替换）

避免一个个文件打开逐个tag修改

import osdef replace_words_in_files(directory, old_word, new_word):# 获取指定目录下的所有文件files = os.listdir(directory)# 遍历所有文件for file in files:# 检查文件是否为.txt文件if file.endswith('.txt'):# 构建完整的文件路径file_path = os.path.join(directory, file)# 打开文件with open(file_path, 'r') as f:content = f.read()# 替换内容content = content.replace(old_word, new_word)# 写回文件with open(file_path, 'w') as f:f.write(content)if __name__ == '__main__':replace_words_in_files(r'D:\SdTrainerGUI\lora-scripts-v1.7.3\train\PreprocessingOutput','girl','boy')