Deep-Live-Monitor

If you find this project useful, please give it a star ❤️❤️

Results 🔥🔥🔥🔥🔥🔥🔥

2024-08-16.14-58-31.mov

2024-08-16.15-10-11.mov

2024-08-16.15-16-24.mov

2024-08-16.15-11-48.mov

2024-08-16.15-03-46.mov

2024-08-16.15-26-12.mov

🔥 How do I install it?

I tested it on Windows, RTX 4090, 24Gb. Inference speed is a little bit lower

1.Setup your platform

• python (3.10 recommended)
• pip
• git
• ffmpeg
• visual studio 2022 runtimes (windows)

2. Clone Repository

git clone https://github.com/Mrkomiljon/Deep-Live-Monitor.git
cd Deep-Live-Monitor

3. Download Models

1. GFPGANv1.4
2. inswapper_128_fp16.onnx

Then put those 2 files on the "models" folder

4. Install dependency

We highly recommend to work with a venv to avoid issues.

pip install -r requirements.txt

🔥 DONE!!! If you dont have any GPU, You should be able to run roop using python run.py command. Keep in mind that while running the program for first time, it will download some models which can take time depending on your network connection.

If the GFPGAN model doesn't download automatically, download it manually!

*Proceed if you want to use GPU Acceleration

CUDA Execution Provider (Nvidia)*

1. Install CUDA Toolkit 11.8

2. Install dependencies:

pip uninstall onnxruntime onnxruntime-gpu
pip install onnxruntime-gpu==1.16.3

3. Usage in case the provider is available:

python run.py --execution-provider cuda

CoreML Execution Provider (Apple Silicon)

1. Install dependencies:

pip uninstall onnxruntime onnxruntime-silicon
pip install onnxruntime-silicon==1.13.1

2. Usage in case the provider is available:

python run.py --execution-provider coreml

CoreML Execution Provider (Apple Legacy)

1. Install dependencies:

pip uninstall onnxruntime onnxruntime-coreml
pip install onnxruntime-coreml==1.13.1

2. Usage in case the provider is available:

python run.py --execution-provider coreml

DirectML Execution Provider (Windows)

1. Install dependencies:

pip uninstall onnxruntime onnxruntime-directml
pip install onnxruntime-directml==1.15.1

2. Usage in case the provider is available:

python run.py --execution-provider directml

OpenVINO™ Execution Provider (Intel)

1. Install dependencies:

pip uninstall onnxruntime onnxruntime-openvino
pip install onnxruntime-openvino==1.15.0

2. Usage in case the provider is available:

python run.py --execution-provider openvino

🔥 Executing python run.py --execution-provider cuda command will launch this window:

• Choose a face image (the face you want to use).
• Choose the target image or video (where you want to replace the face).
• Click Start.
• Open the file explorer and go to the output directory you selected.
• You’ll see a folder named after the video title where the frames are being processed.
• When it’s done, the output file will be ready in that folder.
• That’s it!

For the monitor mode

You should open any video on desktop

🔥 Additional command line arguments are given below. To learn out what they do, check this guide.

options:
  -h, --help                                               show this help message and exit
  -s SOURCE_PATH, --source SOURCE_PATH                     select an source image
  -t TARGET_PATH, --target TARGET_PATH                     select an target image or video
  -o OUTPUT_PATH, --output OUTPUT_PATH                     select output file or directory
  --frame-processor FRAME_PROCESSOR [FRAME_PROCESSOR ...]  frame processors (choices: face_swapper, face_enhancer, ...)
  --keep-fps                                               keep original fps
  --keep-audio                                             keep original audio
  --keep-frames                                            keep temporary frames
  --many-faces                                             process every face
  --video-encoder {libx264,libx265,libvpx-vp9}             adjust output video encoder
  --video-quality [0-51]                                   adjust output video quality
  --max-memory MAX_MEMORY                                  maximum amount of RAM in GB
  --execution-provider {cpu} [{cpu} ...]                   available execution provider (choices: cpu, ...)
  --execution-threads EXECUTION_THREADS                    number of execution threads
  -v, --version                                            show program's version number and exit

🔥🔥🔥 Acknowledgements

I would like to thank main authors.

（Some demo images/videos above are sourced from image websites/repos. If there is any infringement, I will immediately remove them and apologize.）