328 lines
15 KiB
Python
328 lines
15 KiB
Python
# -*- coding: utf-8 -*-
|
||
"""laya-opencv安装脚本 / laya-opencv installer.
|
||
|
||
步骤：虚拟环境 → PyTorch → Laya → 检查 → 视觉组件（OpenCV，可选）→ 收尾。
|
||
|
||
由 install.bat / install.sh 调用，Windows、Linux 通用。可以重复运行，已装好的部分会跳过。
|
||
Called by install.bat / install.sh. Safe to re-run: finished steps are skipped.
|
||
|
||
python app/install.py install
|
||
python app/install.py --dry-run only print the commands
|
||
"""
|
||
import json
|
||
import os
|
||
import shutil
|
||
import subprocess
|
||
import sys
|
||
from pathlib import Path
|
||
|
||
sys.path.insert(0, str(Path(__file__).resolve().parent))
|
||
import wb_lang # noqa: E402
|
||
|
||
ROOT = Path(__file__).resolve().parent.parent
|
||
VENV = ROOT / ".venv"
|
||
IS_WINDOWS = os.name == "nt"
|
||
VENV_PY = VENV / ("Scripts/python.exe" if IS_WINDOWS else "bin/python")
|
||
DRY_RUN = "--dry-run" in sys.argv
|
||
|
||
DEFAULTS = {
|
||
"language": "auto",
|
||
"pip_index": "auto",
|
||
"torch_index": "",
|
||
"install_local_laya": True,
|
||
"install_vision": True,
|
||
"desktop_shortcut": True,
|
||
}
|
||
# 视觉组件：OpenCV 5 的主包去掉了训练模块（cv2.ml），所以固定用 4.x
|
||
VISION_PACKAGES = ["opencv-python-headless>=4.9,<5", "numpy"]
|
||
|
||
# 每条消息: (中文, English)
|
||
MSG = {
|
||
"cfg_bad": ("[!] config.json 格式有误，已改用默认配置: %s", "[!] config.json is not valid JSON; using defaults: %s"),
|
||
"cmd_failed": ("\n[!] 上面的命令失败了（退出码 %d），安装中止。", "\n[!] The command above failed (exit code %d); installation stopped."),
|
||
"torch_have": (" 已安装 torch %s（GPU %s），跳过。", " torch %s is already installed (GPU %s); skipping."),
|
||
"gpu_yes": ("可用", "available"),
|
||
"gpu_no": ("不可用", "not available"),
|
||
"torch_index": (" 按 config.json 的 torch_index 安装 PyTorch。", " Installing PyTorch from torch_index in config.json."),
|
||
"torch_gpu": (" 检测到 NVIDIA 显卡，安装 GPU 版 PyTorch（体积约 2~3 GB，需要一些时间）。",
|
||
" NVIDIA GPU found; installing the GPU build of PyTorch (about 2-3 GB, this takes a while)."),
|
||
"torch_cpu": (" 没有检测到 NVIDIA 显卡，安装 CPU 版 PyTorch。", " No NVIDIA GPU found; installing the CPU build of PyTorch."),
|
||
"torch_fallback": (" [!] 自动选择 PyTorch 版本失败，改用 pip 默认版本安装。",
|
||
" [!] Could not pick a PyTorch build automatically; installing pip's default build."),
|
||
"shortcut_name": ("laya-opencv", "laya-opencv"),
|
||
"shortcut_done": (" 已在桌面创建快捷方式「%s」。", ' Created the desktop shortcut "%s".'),
|
||
"title": (" laya-opencv 安装程序", " laya-opencv installer"),
|
||
"dir": (" 安装目录: %s", " Install folder: %s"),
|
||
"need_py": ("[!] 需要 Python 3.10 或更高版本，当前是 %s。", "[!] Python 3.10 or newer is required; this is %s."),
|
||
"s_venv": ("准备虚拟环境 (.venv)", "Prepare the virtual environment (.venv)"),
|
||
"venv_have": (" 已存在，直接使用。", " Already there; using it."),
|
||
"venv_fail": ("[!] 创建虚拟环境失败。", "[!] Could not create the virtual environment."),
|
||
"venv_apt": ("\n Debian / Ubuntu 请先执行: sudo apt install python3-venv", "\n On Debian / Ubuntu run first: sudo apt install python3-venv"),
|
||
"s_torch": ("安装 PyTorch", "Install PyTorch"),
|
||
"s_laya": ("安装 Laya 和服务端组件", "Install Laya and the server components"),
|
||
"s_check": ("检查安装结果", "Check the installation"),
|
||
"dry_skip": (" (dry-run，跳过检查)", " (dry run, check skipped)"),
|
||
"check_fail": ("[!] 检查没有通过：laya=%s，服务端组件=%s，torch=%s", "[!] Check failed: laya=%s, server components=%s, torch=%s"),
|
||
"gpu_ok": (" GPU 可用 (%s)", " GPU available (%s)"),
|
||
"gpu_wrong_build": (" GPU 不可用 —— 有 NVIDIA 显卡，但当前 PyTorch 不是 GPU 版。\n"
|
||
" Laya 会用 CPU 运行（能用，只是慢一些）。想用 GPU，\n"
|
||
" 请到 https://pytorch.org/get-started/locally/ 选择对应命令，\n"
|
||
" 用 %s -m pip 重新安装 torch。",
|
||
" GPU not available: there is an NVIDIA GPU, but this PyTorch is not a GPU build.\n"
|
||
" Laya will run on the CPU (it works, just slower). To use the GPU,\n"
|
||
" pick the matching command at https://pytorch.org/get-started/locally/\n"
|
||
" and reinstall torch with %s -m pip."),
|
||
"gpu_none": (" GPU 不可用，使用 CPU 运行。", " GPU not available; running on the CPU."),
|
||
"remote_only": ("\n config.json 里 install_local_laya 为 false：跳过 PyTorch 和 Laya，\n"
|
||
" 工作台只使用远程接口（TypeSafe / aiask.me）。",
|
||
"\n install_local_laya is false in config.json: skipping PyTorch and Laya.\n"
|
||
" The workbench will use remote interfaces only (TypeSafe / aiask.me)."),
|
||
"s_vision": ("安装视觉组件（OpenCV）", "Install the vision components (OpenCV)"),
|
||
"vision_have": (" 已安装 OpenCV %s，跳过。", " OpenCV %s is already installed; skipping."),
|
||
"vision_swap": (" 已安装的 OpenCV %s 不带训练模块，换成 4.x 版本。", " The installed OpenCV %s has no training module; switching to a 4.x build."),
|
||
"vision_ok": (" OpenCV %s，训练模块可用。", " OpenCV %s, training module available."),
|
||
"vision_fail": (" [!] 视觉组件没有装上，图像检测和训练暂时不可用，其余功能不受影响。\n"
|
||
" 解决网络问题后重新运行安装脚本即可补装。",
|
||
" [!] The vision components could not be installed; image inspection and training are unavailable for now.\n"
|
||
" Everything else works. Run the installer again once the network problem is fixed."),
|
||
"vision_skip": ("\n config.json 里 install_vision 为 false：跳过 OpenCV，不提供图像检测和训练。",
|
||
"\n install_vision is false in config.json: skipping OpenCV; image inspection and training will be unavailable."),
|
||
"s_finish": ("收尾", "Finish up"),
|
||
"done": (" 完成。", " Done."),
|
||
"all_done": (" 安装完成。运行 %s 启动工作台。", " Installation finished. Run %s to start the workbench."),
|
||
"first_start": (" 首次启动会下载模型（约 650 MB），以后启动只需加载模型。",
|
||
" The first start downloads the model (about 650 MB); later starts only load it."),
|
||
}
|
||
|
||
|
||
def load_config():
|
||
cfg = dict(DEFAULTS)
|
||
path = ROOT / "config.json"
|
||
example = ROOT / "config.example.json"
|
||
if not path.exists() and example.exists() and not DRY_RUN:
|
||
path.write_bytes(example.read_bytes()) # 首次安装：从模板生成 config.json
|
||
if not path.exists() and example.exists():
|
||
path = example
|
||
if path.exists():
|
||
try:
|
||
cfg.update(json.loads(path.read_text(encoding="utf-8-sig")))
|
||
except ValueError as error:
|
||
print("[!] config.json: %s" % error)
|
||
return cfg
|
||
|
||
|
||
CFG = load_config()
|
||
LANG = wb_lang.detect(CFG.get("language"))
|
||
# "auto"：中文环境用清华镜像，其他环境用官方源
|
||
if str(CFG.get("pip_index") or "").strip().lower() == "auto":
|
||
CFG["pip_index"] = "https://pypi.tuna.tsinghua.edu.cn/simple" if LANG == "zh" else ""
|
||
|
||
|
||
def T(key, *args):
|
||
text = MSG[key][1 if LANG == "en" else 0]
|
||
return text % args if args else text
|
||
|
||
|
||
def step(n, total, key):
|
||
print("\n[%d/%d] %s" % (n, total, T(key)))
|
||
|
||
|
||
def run(cmd, check=True):
|
||
"""执行命令并把输出直接显示出来，返回是否成功。"""
|
||
cmd = [str(c) for c in cmd]
|
||
print(" > " + " ".join(cmd))
|
||
if DRY_RUN:
|
||
return True
|
||
code = subprocess.call(cmd, cwd=str(ROOT))
|
||
if code != 0 and check:
|
||
raise SystemExit(T("cmd_failed", code))
|
||
return code == 0
|
||
|
||
|
||
def probe(code):
|
||
"""在虚拟环境里跑一小段 Python，返回输出；失败返回 None。"""
|
||
if DRY_RUN or not VENV_PY.exists():
|
||
return None
|
||
try:
|
||
out = subprocess.run([str(VENV_PY), "-c", code], capture_output=True, text=True,
|
||
timeout=180, cwd=str(ROOT))
|
||
except (OSError, subprocess.TimeoutExpired):
|
||
return None
|
||
return out.stdout.strip() if out.returncode == 0 else None
|
||
|
||
|
||
def pip(*args, check=True):
|
||
cmd = [VENV_PY, "-m", "pip", "install", "--disable-pip-version-check"]
|
||
if CFG.get("pip_index"):
|
||
cmd += ["-i", CFG["pip_index"]]
|
||
return run(cmd + list(args), check=check)
|
||
|
||
|
||
def has_nvidia():
|
||
exe = shutil.which("nvidia-smi")
|
||
if not exe:
|
||
return False
|
||
try:
|
||
return subprocess.run([exe], capture_output=True, timeout=30).returncode == 0
|
||
except (OSError, subprocess.TimeoutExpired):
|
||
return False
|
||
|
||
|
||
def torch_state():
|
||
"""返回 (版本, cuda 是否可用)；没装返回 (None, False)。"""
|
||
out = probe("import torch; print(torch.__version__); print(int(torch.cuda.is_available()))")
|
||
if not out:
|
||
return None, False
|
||
lines = out.splitlines()
|
||
return lines[0], lines[-1] == "1"
|
||
|
||
|
||
def install_torch(nvidia):
|
||
version, cuda = torch_state()
|
||
if version:
|
||
print(T("torch_have", version, T("gpu_yes") if cuda else T("gpu_no")))
|
||
return
|
||
if CFG.get("torch_index"):
|
||
print(T("torch_index"))
|
||
run([VENV_PY, "-m", "pip", "install", "--disable-pip-version-check", "torch",
|
||
"--index-url", CFG["torch_index"]])
|
||
return
|
||
# uv 能按显卡驱动自动挑对应的 PyTorch 版本；没有显卡时装体积小得多的 CPU 版
|
||
backend = "auto" if nvidia else "cpu"
|
||
print(T("torch_gpu") if nvidia else T("torch_cpu"))
|
||
if pip("uv", check=False):
|
||
cmd = [VENV_PY, "-m", "uv", "pip", "install", "--python", VENV_PY, "--torch-backend", backend]
|
||
if CFG.get("pip_index"):
|
||
cmd += ["--default-index", CFG["pip_index"]]
|
||
if run(cmd + ["torch"], check=False):
|
||
return
|
||
print(T("torch_fallback"))
|
||
pip("torch")
|
||
|
||
|
||
def vision_state():
|
||
"""返回 (OpenCV 版本, 训练模块是否可用)；没装返回 (None, False)。"""
|
||
out = probe("import cv2, numpy; print(cv2.__version__); "
|
||
"print(int(all(hasattr(getattr(cv2, 'ml', None), n) for n in ('SVM_create', 'RTrees_create', 'KNearest_create'))))")
|
||
if not out:
|
||
return None, False
|
||
lines = out.splitlines()
|
||
return lines[0], lines[-1] == "1"
|
||
|
||
|
||
def install_vision():
|
||
version, has_ml = vision_state()
|
||
if version and has_ml:
|
||
print(T("vision_have", version))
|
||
return
|
||
if version:
|
||
print(T("vision_swap", version))
|
||
run([VENV_PY, "-m", "pip", "uninstall", "-y", "opencv-python", "opencv-python-headless"], check=False)
|
||
ok = pip(*VISION_PACKAGES, check=False)
|
||
version, has_ml = vision_state()
|
||
if DRY_RUN:
|
||
return
|
||
if ok and version and has_ml:
|
||
print(T("vision_ok", version))
|
||
else:
|
||
print(T("vision_fail"))
|
||
|
||
|
||
def make_shortcut():
|
||
if not IS_WINDOWS or DRY_RUN or not CFG.get("desktop_shortcut", True):
|
||
return
|
||
name = T("shortcut_name")
|
||
target = str(ROOT / "start.bat").replace("'", "''")
|
||
workdir = str(ROOT).replace("'", "''")
|
||
script = (
|
||
"$d=[Environment]::GetFolderPath('Desktop');"
|
||
"$s=(New-Object -ComObject WScript.Shell).CreateShortcut((Join-Path $d '%s.lnk'));"
|
||
"$s.TargetPath='%s';$s.WorkingDirectory='%s';$s.Save()" % (name, target, workdir)
|
||
)
|
||
# 项目原来叫 Laya 工作台 / Laya Workbench。桌面上的旧快捷方式如果指向这个目录，
|
||
# 或者指向的位置已经不存在（文件夹改过名），就删掉，免得留下一个失效的
|
||
cleanup = (
|
||
"$d=[Environment]::GetFolderPath('Desktop');$w=New-Object -ComObject WScript.Shell;"
|
||
"foreach($n in @('Laya \u5de5\u4f5c\u53f0','Laya Workbench')){$f=Join-Path $d ($n+'.lnk');"
|
||
"if(Test-Path -LiteralPath $f){$t=$w.CreateShortcut($f).TargetPath;"
|
||
"if(($t -eq '%s') -or (($t) -and -not (Test-Path -LiteralPath $t))){Remove-Item -LiteralPath $f}}}" % target
|
||
)
|
||
try:
|
||
done = subprocess.run(["powershell.exe", "-NoProfile", "-ExecutionPolicy", "Bypass",
|
||
"-Command", script], capture_output=True, timeout=60)
|
||
if done.returncode == 0:
|
||
print(T("shortcut_done", name))
|
||
subprocess.run(["powershell.exe", "-NoProfile", "-ExecutionPolicy", "Bypass", "-Command", cleanup],
|
||
capture_output=True, timeout=60)
|
||
except (OSError, subprocess.TimeoutExpired):
|
||
pass
|
||
|
||
|
||
def main():
|
||
local = bool(CFG.get("install_local_laya", True))
|
||
vision = bool(CFG.get("install_vision", True))
|
||
total = 2 + (3 if local else 0) + (1 if vision else 0)
|
||
print("=" * 56)
|
||
print(T("title"))
|
||
print(T("dir", ROOT))
|
||
print("=" * 56)
|
||
if sys.version_info < (3, 10):
|
||
raise SystemExit(T("need_py", sys.version.split()[0]))
|
||
|
||
step(1, total, "s_venv")
|
||
if VENV_PY.exists():
|
||
print(T("venv_have"))
|
||
else:
|
||
if not run([sys.executable, "-m", "venv", VENV], check=False):
|
||
raise SystemExit(T("venv_fail") + ("" if IS_WINDOWS else T("venv_apt")))
|
||
run([VENV_PY, "-m", "ensurepip", "--upgrade"], check=False)
|
||
|
||
if local:
|
||
step(2, total, "s_torch")
|
||
nvidia = has_nvidia()
|
||
install_torch(nvidia)
|
||
|
||
step(3, total, "s_laya")
|
||
pip("-U", "laya[serve]")
|
||
|
||
step(4, total, "s_check")
|
||
if DRY_RUN:
|
||
print(T("dry_skip"))
|
||
else:
|
||
laya_version = probe("import laya; print(laya.__version__)")
|
||
serve_ok = probe("import laya.serve, fastapi, uvicorn; print('ok')")
|
||
version, cuda = torch_state()
|
||
if not laya_version or not serve_ok or not version:
|
||
raise SystemExit(T("check_fail", laya_version, serve_ok, version))
|
||
print(" laya %s" % laya_version)
|
||
print(" torch %s" % version)
|
||
if cuda:
|
||
gpu = probe("import torch; print(torch.cuda.get_device_name(0))")
|
||
print(T("gpu_ok", gpu or "cuda"))
|
||
elif nvidia:
|
||
print(T("gpu_wrong_build", ".venv\\Scripts\\python.exe" if IS_WINDOWS else ".venv/bin/python"))
|
||
else:
|
||
print(T("gpu_none"))
|
||
else:
|
||
print(T("remote_only"))
|
||
|
||
if vision:
|
||
step(total - 1, total, "s_vision")
|
||
install_vision()
|
||
else:
|
||
print(T("vision_skip"))
|
||
|
||
step(total, total, "s_finish")
|
||
make_shortcut()
|
||
print(T("done"))
|
||
|
||
print("\n" + "=" * 56)
|
||
print(T("all_done", "start.bat" if IS_WINDOWS else "./start.sh"))
|
||
if local:
|
||
print(T("first_start"))
|
||
print("=" * 56)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main()
|