目录

今天预订的 MacBook Pro M2Max 16寸 顶配 64G内存 2T硬盘到了，¥36097 。

硬件信息

芯片、内存

system_profiler SPHardwareDataType | head -n 9
Hardware:

    Hardware Overview:

      Model Name: MacBook Pro
      Model Identifier: Mac14,6
      Model Number: XXXXXXXXXXXX
      Chip: Apple M2 Max
      Total Number of Cores: 12 (8 performance and 4 efficiency)
      Memory: 64 GB

硬盘

system_profiler SPStorageDataType | head -n 8
Storage:

    Macintosh HD:

      Free: 1.37 TB (1,372,357,345,280 bytes)
      Capacity: 2 TB (1,995,218,165,760 bytes)
      Mount Point: /System/Volumes/Update/mnt1
      File System: APFS

更改主机名

sudo scutil --set HostName MBP

hostname
MBP

HomeBrew

安装

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# zsh => .zshrc  bash => .bashrc
vim ~/.zshrc
export PATH=$PATH:/opt/homebrew/bin

source ~/.zshrc

配置镜像源

vim ~/.bash_profile

export HOMEBREW_API_DOMAIN="https://mirrors.tuna.tsinghua.edu.cn/homebrew-bottles/api"
export HOMEBREW_BOTTLE_DOMAIN="https://mirrors.tuna.tsinghua.edu.cn/homebrew-bottles"
export HOMEBREW_BREW_GIT_REMOTE="https://mirrors.tuna.tsinghua.edu.cn/git/homebrew/brew.git"
export HOMEBREW_CORE_GIT_REMOTE="https://mirrors.tuna.tsinghua.edu.cn/git/homebrew/homebrew-core.git"
export HOMEBREW_PIP_INDEX_URL="https://pypi.tuna.tsinghua.edu.cn/simple"

source ~/.bash_profile

Miniconda

安装

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh
sudo sh Miniconda3-latest-MacOSX-arm64.sh

❌ 配置镜像源

vim ~/.condarc

channels:
  - defaults
show_channel_urls: true
default_channels:
  - http://mirrors.aliyun.com/anaconda/pkgs/main
  - http://mirrors.aliyun.com/anaconda/pkgs/r
  - http://mirrors.aliyun.com/anaconda/pkgs/msys2
custom_channels:
  conda-forge: http://mirrors.aliyun.com/anaconda/cloud
  msys2: http://mirrors.aliyun.com/anaconda/cloud
  bioconda: http://mirrors.aliyun.com/anaconda/cloud
  menpo: http://mirrors.aliyun.com/anaconda/cloud
  pytorch: http://mirrors.aliyun.com/anaconda/cloud
  simpleitk: http://mirrors.aliyun.com/anaconda/cloud

conda clean -i

我配置了清华和阿里云的镜像源，但是都没有成功，最后还是使用了默认的源。

查看缓存目录

conda info | grep "package cache :"
          package cache : /opt/miniconda/pkgs

命令

当前 conda 信息

conda info

     active environment : base
    active env location : /opt/miniconda
            shell level : 1
       user config file : /Users/junjian/.condarc
 populated config files : 
          conda version : 23.1.0
    conda-build version : not installed
         python version : 3.10.9.final.0
       virtual packages : __archspec=1=arm64
                          __osx=13.2=0
                          __unix=0=0
       base environment : /opt/miniconda  (writable)
      conda av data dir : /opt/miniconda/etc/conda
  conda av metadata url : None
           channel URLs : https://repo.anaconda.com/pkgs/main/osx-arm64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/osx-arm64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /opt/miniconda/pkgs
                          /Users/junjian/.conda/pkgs
       envs directories : /opt/miniconda/envs
                          /Users/junjian/.conda/envs
               platform : osx-arm64
             user-agent : conda/23.1.0 requests/2.28.1 CPython/3.10.9 Darwin/22.3.0 OSX/13.2
                UID:GID : 501:20
             netrc file : None
           offline mode : False

创建虚拟环境（将 base 虚拟环境中的 python 链接到新建的虚拟环境中）

sudo conda create --name tensorflow python

删除虚拟环境

conda env remove --name ultralytics

激活虚拟环境

conda activate tensorflow

退出虚拟环境

conda deactivate

查看虚拟环境

conda env list
# conda environments:
#
base                  *  /opt/miniconda

指定虚拟环境安装软件包（默认安装到base环境）

sudo conda install -c apple -n tensorflow tensorflow-deps
sudo conda install -c pytorch -n pytorch pytorch torchvision torchaudio

pip

配置文件在 ~/.config/pip/pip.conf。

配置镜像源

pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

查看缓存目录

pip cache dir
/Users/junjian/Library/Caches/pip

Docker

安装 Docker Desktop

配置镜像源

打开 Docker Desktop 的设置，选择 Docker Engine，然后在 JSON 配置中添加镜像源，然后重启就生效，如下：

{
  "registry-mirrors": [
    "https://75oltije.mirror.aliyuncs.com",
    "http://hub-mirror.c.163.com",
    "https://docker.mirrors.ustc.edu.cn"
  ]
}

配置文件在 ~/.docker/daemon.json。

运行 docker info 查看配置是否生效。

$ docker info

Server:
 Registry Mirrors:
  https://75oltije.mirror.aliyuncs.com/
  http://hub-mirror.c.163.com/
  https://docker.mirrors.ustc.edu.cn/

样本标注工具

labelImg

安装

conda create -n labelimg
conda activate labelimg
conda install -n labelimg python=3.9
conda install -c conda-forge labelimg -n labelimg

必须指定 python 的版本，高版本会出现下面的错误：

2023-03-26 17:28:36.037 python3.10[13381:279105] TSM AdjustCapsLockLEDForKeyTransitionHandling - _ISSetPhysicalKeyboardCapsLockLED Inhibit
Traceback (most recent call last):
  File "/opt/miniconda/lib/python3.10/site-packages/libs/canvas.py", line 530, in paintEvent
    p.drawLine(self.prev_point.x(), 0, self.prev_point.x(), self.pixmap.height())
TypeError: arguments did not match any overloaded call:
  drawLine(self, QLineF): argument 1 has unexpected type 'float'
  drawLine(self, QLine): argument 1 has unexpected type 'float'
  drawLine(self, int, int, int, int): argument 1 has unexpected type 'float'
  drawLine(self, QPoint, QPoint): argument 1 has unexpected type 'float'
  drawLine(self, Union[QPointF, QPoint], Union[QPointF, QPoint]): argument 1 has unexpected type 'float'
[1]    13381 abort      labelImg ./ classes.txt

使用

labelImg images classes.txt labels

Label Studio

pip install -U label-studio
label-studio start

参考资料