python demo.py --config config/vox-256.yaml \
--checkpoint vox-adv-cpk.pth.tar \
--source_image path/to/face.jpg \
--driving_video path/to/driving.mp4 \
--result_video output.mp4
The output is a deepfake video where the source face seamlessly imitates the expressions, lip movements, and head orientation of the driving video.
The model contained within this file implements the First Order Motion Model. Unlike earlier methods (such as "X2Face" or straightforward GANs) that required subject-specific training, this model allows "one-shot" animation.
How it works:
The "Vox-adv-cpk.pth.tar" file is a model checkpoint file for a deep learning model, likely trained for speaker verification tasks with adversarial robustness. It contains the model's weights and potentially other training states. This guide provides a foundational understanding of how to approach such a file, covering its possible origins, contents, and usage.
Vox-adv-cpk.pth.tar a weight file for a deep-learning model used in Vox-adv-cpk.pth.tar
, an open-source software that allows users to animate still images with their own facial expressions in real-time for video calls Model Technical Details : The file contains the pre-trained weights for the First Order Motion Model
, which enables the "driving" of a source image using a video stream. : This specific version ( vox-adv-cpk ) is a variation of the base model ( ). While the base model is trained for 100 epochs, the vox-adv-cpk version is fine-tuned for an additional 50 epochs using an adversarial discriminator to improve realism and detail. File Format : It is a compressed PyTorch checkpoint ( ) wrapped in a TAR archive. Despite being a file, the software is designed to read it directly; do not unpack it during installation. : Approximately Key Usage Instructions To use this file with Avatarify-Python , follow these critical placement steps: : Obtain the weights from official mirrors like : Place the file in the root directory of your local avatarify-python No Unpacking : The application expects the file exactly as it is. Unpacking it will lead to a FileNotFoundError when running the software. Performance & Requirements : For real-time performance, an NVIDIA GPU with CUDA support is highly recommended. GTX 1080 Ti : ~33 FPS. : ~15 FPS. CPU Fallback python demo
: The model can run on a CPU, but performance will be extremely slow, often making it unusable for live video. Troubleshooting Common Issues
No such file or directory: 'vox-adv-cpk.pth.tar' #341 - GitHub The output is a deepfake video where the
with torch.no_grad(): fake_frames = model(face_sequences, audio_features)
The Developer's Responsibility:
If you download Vox-adv-cpk.pth.tar, you are holding a tool that can break social trust. Ethical implementations include: