Here's a comprehensive README template for your GitHub repository, covering all key points, usage instructions, and setup details. You'll need to add images or screenshots where noted.

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MKV to MP4 Video Converter with Multi-GPU Acceleration

This Python-based video converter converts .mkv files to .mp4 format using FFmpeg and supports multi-threading, as well as hardware acceleration for both NVIDIA and Intel GPUs (or a CPU fallback). It features a simple GUI using Tkinter, making it easy to select folders for batch conversions and monitor progress.

Table of Contents

• Features
• Requirements
• Installation
• Usage
• Configuration
• Algorithm
• Hardware Acceleration
• Example Outputs
• Troubleshooting

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Features

• Batch Conversion: Select entire folders to convert all .mkv files to .mp4.
• Multi-threading: Leverages multi-core processors for parallel processing, speeding up the conversion.
• GPU Acceleration: Utilizes both NVIDIA (NVENC) and Intel (QSV) hardware acceleration (if available).
• Progress Tracking: Displays real-time progress updates in the GUI.
• Fallback to CPU: Automatically uses CPU encoding if GPUs are unavailable.

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Requirements

1. FFmpeg: Install FFmpeg and add it to your system PATH. Download it from ffmpeg.org.
2. Python 3.7+: Ensure Python is installed.
3. Python Packages:
   • Install requirements using pip install -r requirements.txt.

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Installation

1. Clone the Repository:

   git clone https://github.com/gichinga03/mkv-to-mp4-main.git
   cd mkv-to-mp4-main

2. Create and Activate a Virtual Environment:

   python -m venv myvenv
   myvenv\Scripts\activate  # Windows
   # or
   source myvenv/bin/activate  # macOS/Linux

3. Install Dependencies:

   pip install -r requirements.txt

4. Setup FFmpeg:
   • Download and install FFmpeg.
   • Add the FFmpeg path to your environment variables for system-wide access.

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Usage

1. Run the Converter:

   python convertor2.py

2. Select Folders:
   • Click Browse Folder in the GUI to choose the input folder with .mkv files.
   • Select an output folder where the converted .mp4 files will be saved.

Example GUI

(Add your screenshots here to showcase the interface)

Configuration

Sample File Requirement

The program requires a sample .mkv file named sample.mkv in the main directory for detecting GPU encoders. Add this file manually, or update the file path in convertor2.py if necessary.

GPU Utilization

The program alternates conversions between available NVIDIA and Intel GPUs, if detected. This configuration optimizes GPU usage and reduces processing time. If no compatible GPU is available, the program falls back to CPU-based conversion.

Algorithm

1. Check Available GPUs:
   • A sample file (sample.mkv) is used to detect encoder support for NVIDIA (h264_nvenc) and Intel (h264_qsv) hardware.
2. Batch Conversion with Multi-threading:
   • Converts files in parallel, submitting one conversion per thread up to a maximum of 10 concurrent conversions.
3. Encoder Assignment:
   • Assigns NVIDIA or Intel GPU encoding for each file alternatively (or CPU if unavailable).
4. Progress Monitoring:
   • Tracks conversion progress and updates the GUI in real time.

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Hardware Acceleration

Supported Encoders

1. NVIDIA NVENC (h264_nvenc): Uses NVIDIA GPU hardware encoding.
2. Intel QSV (h264_qsv): Uses Intel Quick Sync Video encoding.
3. CPU Fallback (libx264): Uses software encoding if no compatible GPU is detected.

Add a sample image showing GPU encoder selection in action here.

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Example Outputs

Input File (.mkv)	Output File (.mp4)	Encoder Used
input1.mkv	output1.mp4	h264_nvenc
input2.mkv	output2.mp4	h264_qsv
input3.mkv	output3.mp4	libx264 (CPU)

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Troubleshooting

1. Error: Sample File Not Found:
   • Add a sample .mkv file to the directory to enable GPU detection.
2. FFmpeg Not Found:
   • Ensure FFmpeg is installed and added to your system PATH.
3. GPU Encoder Not Available:
   • Update GPU drivers and confirm your GPU model supports NVENC or QSV.
4. Program Hangs:
   • Reduce the number of threads or check your system resources.

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Contributing

Feel free to open issues or create pull requests to improve this project. Contributions are welcome!

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License

MIT License. See LICENSE file for more details.

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