Easy and Quick DaGAN Windows Installation Guide
Table of Contents:
- Introduction
- Installation
- Setting Up Anaconda
- Creating the Code Directory
- Downloading the Codes
- Setting Up the Virtual Environment
- Installing Dependencies
- Using the Virtual Environment
- Downloading Pre-Trained Checkpoints
- Setting Up Input and Driving Files
- Running the Inference Codes
- Viewing the Results
- Training a Depth Model (Optional)
- Conclusion
Article: A Step-by-Step Guide to Installing Dakan on a Windows Machine
Introduction
Dakan is an impressive deep learning model that generates talking face animations. In this tutorial, I will guide You through the process of installing Dakan on your local Windows machine, specifically on a system with an NVIDIA GPU. However, don't worry if you don't have an NVIDIA GPU; it can still be run on CPU-only, but with some limitations. So let's dive right in!
Installation
To begin, you need to install Anaconda, a popular distribution of the Python and R programming languages. If you don't have Anaconda installed, you can download it from the official Website and choose the 64-bit version suitable for your Windows system.
Setting Up Anaconda
Once Anaconda is installed, open it by searching for it in the search bar. After opening Anaconda, we need to find a location in which to install the Dakan codes. It is recommended to Create a tutorial folder for this purpose. You can create the folder using the "mkdir" command and then navigate into it using the "cd" command. Additionally, if you need to switch disks, use the appropriate command with your disk name. For example, if your disk is named "F," the command would be "f:" to switch to that disk.
Downloading the Codes
Next, you need to download the Dakan codes. There are two options for this: manual download or using Git clone. For the manual download, you can visit the official repository and download the zip file. Extract the files and move them to the tutorial folder. Alternatively, if you have Git clone installed, you can copy the repository's link and use the "git clone" command followed by the link to download the codes.
Setting Up the Virtual Environment
After downloading the codes, navigate to the root folder where the codes are located. This folder contains all the necessary codes and additional files. Now, we need to create a virtual environment for Dakan. Copy the first line of code, which creates the environment, and run it in the Anaconda prompt. The environment will be automatically activated, indicated by the change in the prompt.
Installing Dependencies
With the Dakan environment activated, you can proceed to install the required dependencies. Copy the Second line of code, which installs Conda and PyTorch, and run it in the Anaconda prompt. Make sure all the dependencies are installed correctly by copying and running the third line, which installs the necessary requirements from the dashboard.txt file.
Using the Virtual Environment
Congratulations! You have successfully set up the virtual environment for Dakan. The next time you want to use this environment, simply activate it again using the command "conda activate dakan." There is no need to reinstall the dependencies as the environment can be reused.
Downloading Pre-Trained Checkpoints
To generate accurate talking face animations, Dakan requires pre-trained checkpoints. You can download the required checkpoints from the repository. For example, one essential checkpoint is the depth phase model, which can be found in the "depth_models" folder. Download the necessary checkpoint files and store them in the "checkpoints" folder within the tutorial directory.
Setting Up Input and Driving Files
To use Dakan effectively, it is recommended to create specific folders for input images, driving videos, and checkpoints. Create an "input" folder to store face images, a "driving" folder for driving videos, and a "checkpoints" folder for the pre-trained checkpoints. You can download sample input images and driving videos online. Copy the generated files into the respective folders.
Running the Inference Codes
Now comes the exciting part! Open the Anaconda prompt and navigate to the Dakan base folder. Copy the command for running the inference codes, specifying the required input image, checkpoint, and driving video. Paste the command into the prompt and wait for the video to be processed. The length of time will vary depending on the complexity of the video and the performance of your machine.
Viewing the Results
Once the inference process is complete, navigate back to the base folder. Open the result file with any preferred software to view the face animation. Take note that the web demo may provide clearer results compared to the local setup, but both should give a similar output. Experiment with different settings and inputs for enhanced animations.
Training a Depth Model (Optional)
Training a depth model is a more advanced topic beyond the scope of this tutorial. However, if you are interested in training your own depth model for Dakan, you will need to follow additional steps. Refer to the official documentation or Seek expert guidance for comprehensive training instructions.
Conclusion
Congratulations! You have successfully installed Dakan on your local Windows machine and learned how to generate talking face animations. Remember to download the necessary pre-trained checkpoints and set up your input and driving files correctly. By following the step-by-step instructions provided in this tutorial, you can now enjoy creating engaging and realistic face animations using Dakan. Happy animating!
Highlights:
- Install Dakan on your local Windows machine
- Requires Anaconda and NVIDIA GPU (CPU-only option available)
- Set up a virtual environment and install dependencies
- Download pre-trained checkpoints for accurate animations
- Create input and driving folders for effective usage
- Run inference codes to generate face animations
- View and experiment with the results
- Training a depth model requires additional knowledge and instructions
- Enjoy creating engaging and realistic face animations with Dakan
FAQ:
Q: Can I install Dakan on a Windows machine without an NVIDIA GPU?
A: Yes, you can install and run Dakan on a CPU-only Windows machine. However, the performance may be slower compared to using an NVIDIA GPU.
Q: Can I use custom input images and driving videos with Dakan?
A: Absolutely! Dakan allows you to use your own face images and driving videos. Just make sure to organize them properly in the input and driving folders.
Q: Is it necessary to create a virtual environment for Dakan?
A: Yes, creating a virtual environment ensures a clean and isolated setup for Dakan, preventing any conflicts with your existing Python environment.
Q: Can I train my own depth model for Dakan?
A: Yes, training a depth model is possible but more advanced. It requires additional steps and knowledge beyond the scope of this tutorial. Refer to the official documentation or seek expert guidance for detailed training instructions.
Q: Are there any limitations or known issues with Dakan?
A: While Dakan is a powerful tool for generating face animations, there may be certain limitations or known issues depending on the specific setup and usage. It is recommended to refer to the official documentation or community forums for any troubleshooting or further assistance.
Q: How can I support the creator of Dakan?
A: You can support the creator by checking out their Patreon page or engaging with their main videos. Supporting creators helps them continue developing and improving tools like Dakan.