Signapse_synthetic_signer
Project description
Signapse synthetic signer
Tested using python=3.10.9
Example command
python inference.py "{\"GPU\":\"cpu\",\"input_video_path\":\"path/to/video.mp4\",\"input_type\":\"video\",\"start\":0,\"stop\":-1,\"num_workers\":1,\"GAN_folder\":\"GAN\",\"signer\":\"Barbara\",\"stereo\":\"False\",\"pro\":\"True\",\"detailed_video\":\"False\",\"organisation_id\":\"0\",\"sign_request_id\":\"0\",\"sign_result_queue_url\":\"0\",\"synthetic_sign_results_bucket\":\"0\"}"
GAN_Checkpoint files
GAN input files need to be downloaded to the respective folders. The GAN files are saved on.
To choose the output signer appearance, pass the respective --signer XX
argument.
Barbara
--signer Barbara
Download the folder and store as ./Barbara.
Safyan
--signer Safyan
Download the folder and store as ./Safyan.
Mia
--signer Mia
Download the folder and store as ./Mia.
Face and Body Separate GANs
To run without Face and Body (--GAN_folder GAN)
Pass the respective --GAN_folder GAN
argument.
--GAN_folder GAN
To run with Face and Body (--GAN_folder GAN_FaB)
Pass the respective --GAN_folder GAN_FaB
argument.
--GAN_folder GAN_FaB
Face Mesh
To run with FaceMesh and FaceLandmarks (--GAN_folder GAN_FM)
--GAN_folder GAN_FM
To run with FaceMesh and no FaceLandmarks (--GAN_folder GAN_FM_NoFL)
--GAN_folder GAN_FM_NoFL
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