Files
colomi 0eb61f3e60 初始化换发型项目:3个微服务代码 + 部署脚本
包含:
- hair_service_sd: 换发型/换发色算法服务 (端口 8801)
- photo_service: LoRA 训练调度服务 (端口 32678)
- stable-diffusion-webui: SD WebUI 推理服务 (端口 57860)
- kohya_ss_home: 训练环境代码
- meidaojia: 监控测试脚本
- setup.sh: 一键部署脚本 (conda环境恢复 + 配置生成 + 完整性检查)
- start_all_services.sh: 启动3个服务
- configure.ini.template: 路径模板化 (BASE_DIR自动推导)
- conda_envs/py310.yml: py310 环境定义

大文件 (weights/, models/, data/, conda_envs/*.tar.gz 等) 通过 .gitignore 排除,
由网盘单独上传。
2026-07-11 18:11:49 +08:00

85 lines
2.1 KiB
Python
Executable File

import hashlib
import os.path
from modules import shared
import modules.cache
dump_cache = modules.cache.dump_cache
cache = modules.cache.cache
def calculate_sha256(filename):
hash_sha256 = hashlib.sha256()
blksize = 1024 * 1024
with open(filename, "rb") as f:
for chunk in iter(lambda: f.read(blksize), b""):
hash_sha256.update(chunk)
return hash_sha256.hexdigest()
def sha256_from_cache(filename, title, use_addnet_hash=False):
hashes = cache("hashes-addnet") if use_addnet_hash else cache("hashes")
try:
ondisk_mtime = os.path.getmtime(filename)
except FileNotFoundError:
return None
if title not in hashes:
return None
cached_sha256 = hashes[title].get("sha256", None)
cached_mtime = hashes[title].get("mtime", 0)
if ondisk_mtime > cached_mtime or cached_sha256 is None:
return None
return cached_sha256
def sha256(filename, title, use_addnet_hash=False):
hashes = cache("hashes-addnet") if use_addnet_hash else cache("hashes")
sha256_value = sha256_from_cache(filename, title, use_addnet_hash)
if sha256_value is not None:
return sha256_value
if shared.cmd_opts.no_hashing:
return None
print(f"Calculating sha256 for {filename}: ", end='')
if use_addnet_hash:
with open(filename, "rb") as file:
sha256_value = addnet_hash_safetensors(file)
else:
sha256_value = calculate_sha256(filename)
print(f"{sha256_value}")
hashes[title] = {
"mtime": os.path.getmtime(filename),
"sha256": sha256_value,
}
dump_cache()
return sha256_value
def addnet_hash_safetensors(b):
"""kohya-ss hash for safetensors from https://github.com/kohya-ss/sd-scripts/blob/main/library/train_util.py"""
hash_sha256 = hashlib.sha256()
blksize = 1024 * 1024
b.seek(0)
header = b.read(8)
n = int.from_bytes(header, "little")
offset = n + 8
b.seek(offset)
for chunk in iter(lambda: b.read(blksize), b""):
hash_sha256.update(chunk)
return hash_sha256.hexdigest()