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 os
def rename_files_in_directory(directory, key_word, new_suffix):
i = 1
for filename in os.listdir(directory):
new_file = key_word + str(i).zfill(3) + new_suffix
source = 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 os
def 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_factor
new_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, ImageOps
def 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 os
def 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')