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updated readme with .exe informations

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Falko Victor Habel 2024-04-04 14:31:20 +02:00
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README.md
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@ -20,13 +20,19 @@ With these features, MPENN significantly simplifies the workflow for users who n
Welcome to MPENN, a comprehensive tool designed to streamline massive picture editing tasks for neural networks. Follow these steps to get started with MPENN and begin transforming your videos and images into machine learning-ready datasets.
## 1. Download MPENN
## 1. Downloading and Using MPENN
To start using MPENN, first obtain the software by downloading it from its [Gitea repository](https://gitea.example.com/mpenn/mpenn). Click on the latest release suitable for your operating system to begin the download process.
To begin using MPENN, download the software from its [Gitea repository](https://gitea.fabelous.app/Fabelous/mpenn). You can choose between two options for download:
## 2. Setting Up Your Environment
1. **Source code:** Download the source code and build the application yourself. This option is recommended if you have experience with programming and want to modify or extend MPENN's functionality.
After downloading MPENN, it's recommended to set up a virtual environment (venv) for running the software. This ensures that your Python environment remains clean and organized. Open your terminal or command prompt and navigate to the MPENN directory. Then, run the following commands:
2. **Precompiled binary (.exe):** Download the precompiled binary for your operating system. This will allow you to quickly start using MPENN without needing to build it from source. Please note that, upon executing the .exe, a folder will be created in the directory of the .exe containing some configuration files.
**No environment setup is necessary when using the binary.** You can run the .exe directly after downloading and it will function as intended.
## 2. Dependencies (Applicable for source code only)
If you have chosen to download the source code, we recommend setting up a virtual environment (venv) for running the software. This ensures that your Python environment remains clean and organized. Open your terminal or command prompt and navigate to the MPENN directory. Then, run the following commands:
```bash
# Create a virtual environment named 'mpenn-env'
@ -40,11 +46,12 @@ source mpenn-env/bin/activate
# Install MPENN dependencies
pip install -r requirements.txt
# run main.py to run mpenn
python main.py
```
With these steps, your environment will be prepared for running MPENN using the source code.
## Running MPENN
With your environment set up, you're ready to launch MPENN. Run the `main.py` File to get started:
### 1. Converting Video to Picture Sequence