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* migrate to whip part1 * migrate to whip part2 * migrate to whip part3 * migrate to whip part4 * migrate to whip/whep with bidirectional * migrate to whip/whep with bidirectional * use next library * add _next to lid datachannel files * cleanup and add todos * use internal helper rtcGetPayloadTypesForCodec * fix lint * refactor decode() * move logic to codecs * move logic to codecs * break encoders and decoders into multiple files * break encoders and decoders into multiple files * cleanup more * drop action for stream endpoints, keep type for self documentation * restore the v4 store * fix: align frame_width and frame_height to even in both collect() and read_resolution() in both decoders. --------- Co-authored-by: harisreedhar <h4harisreedhar.s.s@gmail.com>
FaceFusion
Industry leading face manipulation platform.
Installation
Be aware, the installation needs technical skills and is not recommended for beginners. In case you are not comfortable using a terminal, our Windows Installer and macOS Installer get you started.
Usage
Run the command:
python facefusion.py [commands] [options]
options:
-h, --help show this help message and exit
-v, --version show program's version number and exit
commands:
run run the program
batch-run run the program in batch mode
force-download force automate downloads and exit
benchmark benchmark the program
api start the API server
job-list list jobs by status
job-create create a drafted job
job-submit submit a drafted job to become a queued job
job-submit-all submit all drafted jobs to become a queued jobs
job-delete delete a drafted, queued, failed or completed job
job-delete-all delete all drafted, queued, failed and completed jobs
job-add-step add a step to a drafted job
job-remix-step remix a previous step from a drafted job
job-insert-step insert a step to a drafted job
job-remove-step remove a step from a drafted job
job-run run a queued job
job-run-all run all queued jobs
job-retry retry a failed job
job-retry-all retry all failed jobs
Documentation
Read the documentation for a deep dive.
Languages
Python
99.7%
CSS
0.3%