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🎥 KLing-Video-WatermarkRemover-Enhancer

One-click watermark removal for KLing videos - Make your videos more professional! 🚀

✨ Key Features

🎯 Perfect Watermark Removal

• Smart detection and precise removal of KLing watermarks
• Lossless quality with smooth, natural edges
• Batch processing support for maximum efficiency

🎨 AI Video Enhancement

• Super-resolution technology powered by Real-ESRGAN
• Smart optimization of brightness, contrast, and clarity
• Special facial detail enhancement for better-looking characters

⚡ Efficient & Convenient

• Simple command-line operation
• Support for batch video processing
• Customizable processing parameters

🔧 Installation

Follow these steps to install KLing-Video-WatermarkRemover-Enhancer:

git clone --recursive https://github.com/chenwr727/KLing-Video-WatermarkRemover-Enhancer.git
conda create -n kling python=3.10
conda activate kling
pip install -r requirements.txt

🛠️ Configuration

The config.yaml file defines parameters for watermark removal and video enhancement.

Watermark Removal

Parameters for watermark removal:

• position: [556, 1233, 701, 1267]

  • Defines the watermark area coordinates
  • Format: (x1, y1, x2, y2), representing top-left (556, 1233) and bottom-right (701, 1267) coordinates
  • Used to determine the watermark region during processing

• ckpt_p: "./weights/sttn.pth"

  • Path to the watermark removal model weights
  • sttn.pth is based on STTN (Spatio-Temporal Trajectory Network)

• mask_expand: 30

  • Pixel expansion of the watermark area
  • Ensures clean removal without artifacts

• neighbor_stride: 10

  • Stride size for temporal neighborhood computation
  • Controls sampling frequency of neighboring frames

Video Enhancement

Parameters for video enhancement:

• RealESRGAN_model_path: "./weights/RealESRGAN_x2plus.pth"

  • Path to Real-ESRGAN model weights for video quality enhancement
  • More models available in Real-ESRGAN/inference_realesrgan.py
  • RealESRGAN_x2plus.pth

• GFPGANer_model_path: "./weights/GFPGANv1.4.pth"

  • Path to GFPGAN model weights for facial enhancement
  • More models available in Real-ESRGAN/cog_predict.py
  • GFPGANv1.4.pth

🚀 Quick Start

Start enhancing your videos with just one command:

python main.py --input your_video.mp4 --remove-watermark --enhance-video

🎮 Common Usage Examples

# Remove watermark only
python main.py --input video.mp4 --remove-watermark

# Enhance video only
python main.py --input video.mp4 --enhance-video

# Process all videos in a folder
python main.py --input videos_folder --remove-watermark --enhance-video

📁 Project Structure

KLing-Video-WatermarkRemover-Enhancer/
├── 📄 main.py          # Main program entry
├── 📁 modules/         # Core function modules
├── 📁 utils/          # Utility functions
└── 📄 config.yaml     # Configuration file

🤝 References

• STTN - Powerful video inpainting technology
• Real-ESRGAN - State-of-the-art video super-resolution solution

🌟 Support

If this project helps you, please consider giving it a star ⭐️