a8694b73f0
* fix localization nullpointer exception * fix devicelib error line:61,remove e * support create docker from cpu dockerfile * support preview or not when train(resolve cannot connect to X server)
133 lines
3.3 KiB
Markdown
133 lines
3.3 KiB
Markdown
# For Mac Users
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If you just have a **MacBook**.DeepFaceLab **GPU** mode does not works. However,it can also works with **CPU** mode.Follow the Steps below will help you build the **DRE** (DeepFaceLab Runtime Environment) Easier.
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### 1. Open a new terminal and Clone DeepFaceLab with git
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```
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$ git git@github.com:iperov/DeepFaceLab.git
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```
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### 2. Change the directory to DeepFaceLab
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```
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$ cd DeepFaceLab
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```
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### 3. Install Docker
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[Docker Desktop for Mac](https://hub.docker.com/editions/community/docker-ce-desktop-mac)
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### 4. Build Docker Image For DeepFaceLab
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```
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$ docker build -t deepfacelab-cpu -f Dockerfile.cpu .
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```
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### 5. Mount DeepFaceLab volume and Run it
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```
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$ docker run -p 8888:8888 --hostname deepfacelab-cpu --name deepfacelab-cpu -v $PWD:/notebooks deepfacelab-cpu
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```
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PS: Because your current directory is `DeepFaceLab`,so `-v $PWD:/notebooks` means Mount `DeepFaceLab` volume to `notebooks` in **Docker**
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And then you will see the log below:
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```
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The Jupyter Notebook is running at:
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http://(deepfacelab-cpu or 127.0.0.1):8888/?token=your token
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```
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### 6. Open a new terminal to run DeepFaceLab in /notebooks
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```
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$ docker exec -it deepfacelab-cpu bash
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$ ls -A
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```
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### 7. Use jupyter in deepfacelab-cpu bash
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```
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$ jupyter notebook list
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```
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or just open it on your browser `http://127.0.0.1:8888/?token=your_token`
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PS: You can run python with jupyter.However,we just run our code in bash.It's simpler and clearer.Now the **DRE** (DeepFaceLab Runtime Environment) almost builded.
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### 8. Stop or Kill Docker Container
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```
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$ docker stop deepfacelab-cpu
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$ docker kill deepfacelab-cpu
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```
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### 9. Start Docker Container
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```
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# start docker container
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$ docker start deepfacelab-cpu
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# open bash to run deepfacelab
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$ docker exec -it deepfacelab-cpu bash
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```
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PS: `STEP 8` or `STEP 9` just show you the way to stop and start **DRE**.
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### 10. enjoy it
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```
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# make sure you current directory is `/notebooks`
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$ pwd
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# make sure all `DeepFaceLab` code is in current path `/notebooks`
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$ ls -a
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# read and write permission
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$ chmod +x cpu.sh
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# run `DeepFaceLab`
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$ ./cpu.sh
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```
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### Details with `DeepFaceLab`
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#### 1. Concepts
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In our Case,**Cage**'s Face is **SRC Face**,and **Trump**'s Face is **DST Face**.and finally we get the **Result** below.
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So,before you run `./cpu.sh`.You should be aware of this.
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#### 2. Use MTCNN(mt) to extract faces
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Do not use DLIB extractor in CPU mode
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#### 3. Best practice for SORT
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1) delete first unsorted aligned groups of images what you can to delete.
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2) use `hist`
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#### 4. Use `H64 model` to train and convert
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Only H64 model reasonable to train on home CPU.You can choice other model like **H128 (3GB+)** | **DF (5GB+)** and so on ,it depends entirely on your CPU performance.
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#### 5. execute the script below one by one
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```
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root@deepfacelab-cpu:/notebooks# ./cpu.sh
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1) clear workspace 7) data_dst sort by hist
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2) extract PNG from video data_src 8) train
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3) data_src extract faces 9) convert
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4) data_src sort 10) converted to mp4
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5) extract PNG from video data_dst 11) quit
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6) data_dst extract faces
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Please enter your choice:
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```
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#### 6. Put all videos in `workspace` directory
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```
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.
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├── data_dst
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├── data_src
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├── dst.mp4
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├── model
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└── src.mp4
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3 directories, 2 files
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```
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