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import argparse | ||
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class DataProcessingOptions(): | ||
def __init__(self): | ||
self.parser = argparse.ArgumentParser() | ||
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def parse_args(self): | ||
self.parser.add_argument('--extract_video_frame', action='store_true', help='extract video frame') | ||
self.parser.add_argument('--extract_audio', action='store_true', help='extract audio files from videos') | ||
self.parser.add_argument('--extract_deep_speech', action='store_true', help='extract deep speech features') | ||
self.parser.add_argument('--crop_face', action='store_true', help='crop face') | ||
self.parser.add_argument('--generate_training_json', action='store_true', help='generate training json file') | ||
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self.parser.add_argument('--source_video_dir', type=str, default="./asserts/training_data/split_video_25fps", | ||
help='path of source video in 25 fps') | ||
self.parser.add_argument('--openface_landmark_dir', type=str, default="./asserts/training_data/split_video_25fps_landmark_openface", | ||
help='path of openface landmark dir') | ||
self.parser.add_argument('--video_frame_dir', type=str, default="./asserts/training_data/split_video_25fps_frame", | ||
help='path of video frames') | ||
self.parser.add_argument('--audio_dir', type=str, default="./asserts/training_data/split_video_25fps_audio", | ||
help='path of audios') | ||
self.parser.add_argument('--deep_speech_dir', type=str, default="./asserts/training_data/split_video_25fps_deepspeech", | ||
help='path of deep speech') | ||
self.parser.add_argument('--crop_face_dir', type=str, default="./asserts/training_data/split_video_25fps_crop_face", | ||
help='path of crop face dir') | ||
self.parser.add_argument('--json_path', type=str, default="./asserts/training_data/training_json.json", | ||
help='path of training json') | ||
self.parser.add_argument('--clip_length', type=int, default=9, help='clip length') | ||
self.parser.add_argument('--deep_speech_model', type=str, default="./asserts/output_graph.pb", | ||
help='path of pretrained deepspeech model') | ||
return self.parser.parse_args() | ||
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class LipSickInferenceOptions(): | ||
def __init__(self): | ||
self.parser = argparse.ArgumentParser() | ||
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def parse_args(self): | ||
self.parser.add_argument('--source_channel', type=int, default=3, help='channels of source image') | ||
self.parser.add_argument('--ref_channel', type=int, default=15, help='channels of reference image') | ||
self.parser.add_argument('--audio_channel', type=int, default=29, help='channels of audio feature') | ||
self.parser.add_argument('--mouth_region_size', type=int, default=256, help='help to resize window') | ||
self.parser.add_argument('--source_video_path', | ||
default='./asserts/examples/test4.mp4', | ||
type=str, | ||
help='path of source video') | ||
self.parser.add_argument('--source_openface_landmark_path', | ||
default='./asserts/examples/test4.csv', | ||
type=str, | ||
help='path of detected openface landmark') | ||
self.parser.add_argument('--driving_audio_path', | ||
default='./asserts/examples/driving_audio_1.wav', | ||
type=str, | ||
help='path of driving audio') | ||
self.parser.add_argument('--pretrained_lipsick_path', | ||
default='./asserts/pretrained_lipsick.pth', | ||
type=str, | ||
help='pretrained model of lipsick') | ||
self.parser.add_argument('--deepspeech_model_path', | ||
default='./asserts/output_graph.pb', | ||
type=str, | ||
help='path of deepspeech model') | ||
self.parser.add_argument('--res_video_dir', | ||
default='./asserts/inference_result', | ||
type=str, | ||
help='path of generated videos') | ||
return self.parser.parse_args() |