Manga-Translator-GUI

What is this?

The goal of this project is to enable general users to easily translate the text in images within a folder into their desired language, all at once.

This tool is based on the Batch operation support provided by the Docker image from the zyddnys/manga-image-translator project.

The project is designed to enable general users to access and use the Batch operation feature more easily.
It directly depends on the above-mentioned project and is a non-commercial, purpose-built project.

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1. Requirements

This project is built to operate on Linux via WSL2 or WSL-based Docker Desktop on Windows.

The program's primary purpose is to create a Docker container by executing user-defined commands and to output results accurately.
Please ensure Docker Desktop is installed and verify that Docker commands can be executed successfully in the CMD console.

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2. Optional Configurations

If WSL2 is installed as a Non-Distro setup without Docker Desktop, or if the PC supports Nvidia GPUs, you can configure the system accordingly for faster speeds and greater stability.

Although running with a CPU provides similar results, running multiple processes simultaneously may cause the PC to slow down or freeze, depending on the operating environment.

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3. Execution and Precautions

1. install docker-desktop

2. pulling the docker image by zyddnys Open the Command Prompt and enter the following:

 docker pull zyddnys/manga-image-translator:main

3. Run the executable file included in this project. exe file here : Download Exe V1.01
4. When selecting a folder, ensure the folder path does not contain spaces, as this can cause the program to malfunction.

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Comments on Potential Computing Issues

Docker Desktop Dependency

• Ensure Docker Desktop is properly configured. Some users may experience issues with Docker if Windows is not updated to the latest version or if WSL2 is not installed correctly.
• Use the command wsl --list --verbose to verify that WSL2 is active and correctly set up.
• If running on a CPU, simultaneous operations might cause resource exhaustion. Monitor system performance to avoid crashes.

GPU Acceleration

• Nvidia GPU support requires the Nvidia Container Toolkit. Install it using Nvidia's official documentation.
• Confirm GPU compatibility with the nvidia-smi command. Unsupported GPUs or driver issues might result in fallback to CPU, significantly slowing down operations.

File Path Issues

• Spaces in folder paths can disrupt Docker command execution. Consider sanitizing paths in the code or handling exceptions programmatically to alert users.

Executable Restrictions

• Ensure the executable file has proper permissions and is not blocked by antivirus software. It is recommended to run the executable as an administrator for full functionality.

Resource Management

• Docker containers consume significant resources, especially for image processing tasks. Ensure adequate system resources (RAM, CPU, and disk space) are available.
• Use the docker stats command to monitor resource usage and terminate containers if necessary.

Cross-Platform Compatibility

• Non-Windows users may encounter issues if the project is tailored primarily for Windows with WSL2. Providing equivalent configurations or alternatives for Linux and macOS could enhance usability.

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Reporting Issues

If you encounter any errors, please leave a report in the Issues section of this project.
We will review and address them as soon as possible.