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Otherwise it will fallback to the central processor and run very slowly. These are performance metrics for some hardware:. Download model's weights from Dropbox , Mega , Yandex. Disk or Google Drive [ MB, md5sum 46b26eabacbcfac66dc5cfc5e ]. Note : we found out that in versions after v4. To use Avatarify in Zoom you can choose from 2 options:.
For Mac it's quite difficult to create a virtual camera, so we'll use CamTwist app. Avatarify comes with a standard set of avatars of famous people, but you can extend this set simply copying your avatars into avatars folder.
You can use command v4l2-ctl --list-devices to list all devices in your system. The cam window is for controlling your face position and avatarify is for the avatar animation preview. Please follow these recommendations to drive your avatars. CAMID is an index number of camera like 0, 1, 2, Alternatively, you can hit 'F' for the software to attempt to find a better reference frame itself. This will slow down the framerate, but while this is happening, you can keep moving your head around: the preview window will flash green when it finds your facial pose is a closer match to the avatar than the one it is currently using.
You will see two numbers displayed as well: the first number is how closely you are currently aligned to the avatar, and the second number is how closely the reference frame is aligned.
You want to get the first number as small as possible - around 10 is usually a good alignment. When you are done, press 'F' again to exit reference frame search mode. You don't need to be exact, and some other configurations can yield better results still, but it's usually a good starting point. Our goal is to democratize deepfake avatars. To make the technology even more accessible, we have to tackle two major problems:. Python Awesome. Apr 20, 6 min read.
Avatarify Avatars for Skype and Zoom. Disk or Google Drive [ MB, md5sum 46b26eabacbcfac66dc5cfc5e ] Linux Linux uses v4l2loopback to create virtual camera. Install CUDA. Download Miniconda Python 3. To use Avatarify in Zoom you can choose from 2 options: Install Zoom v4. Install Miniconda Python 3. Download and install CamTwist from here.
It's easy. Windows Video tutorial is coming! This guide is tested for Windows Install Git. Press Windows button and type "miniconda". Run suggested Anaconda Prompt. If installation was successful, two windows "cam" and "avatarify" will appear. Leave these windows open for the next installation steps.
If there are multiple cameras including virtual ones in the system, you may need to select the correct one. Install VirtualCam plugin. Choose Install and register only 1 virtual camera. Run OBS Studio. In the appeared window, choose "[python. The steps are required only once during setup. Setup avatars Avatarify comes with a standard set of avatars of famous people, but you can extend this set simply copying your avatars into avatars folder.
Follow these advices for better visual quality: Make square crop of your avatar picture. Crop avatar's face so that it's not too close not too far. Use standard avarars as reference. Prefer pictures with uniform background.
It will diminish visual artifacts. Run Your web cam must be plugged-in. Note: run Skype or Zoom only after Avatarify is started. Run: bash run. In the Settings section choose Confine to Application Window and select python avatarify from the drop-down menu. Controls Keys Controls These will immediately switch between the first 9 avatars.
Every time you push the button — new avatar is sampled. X Reset reference frame. F Toggle reference frame search mode. R Mirror reference window. T Mirror output window. I Show FPS ESC Quit Driving your avatar These are the main principles for driving your avatar: Align your face in the camera window as closely as possible in proportion and position to the target avatar. Contribution Our goal is to democratize deepfake avatars.
To make the technology even more accessible, we have to tackle two major problems: Add support for more platforms Linux and Mac are already supported. Optimize neural network run-time. Running network real-time on CPU is of high priority. Please make pull requests if you have any improvements or bug-fixes.
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