def main(source, target, output=None, select_source=d('select_source'), select_target=d('select_target'),
# General arguments
resolution=d('resolution'), crop_scale=d('crop_scale'), gpus=d('gpus'),
cpu_only=d('cpu_only'), display=d('display'), verbose=d('verbose'), encoder_codec=d('encoder_codec'),
# Detection arguments:
detection_model=d('detection_model'), det_batch_size=d('det_batch_size'), det_postfix=d('det_postfix'),
# Sequence arguments:
iou_thresh=d('iou_thresh'), min_length=d('min_length'), min_size=d('min_size'),
center_kernel=d('center_kernel'), size_kernel=d('size_kernel'), smooth_det=d('smooth_det'),
seq_postfix=d('seq_postfix'), write_empty=d('write_empty'),
# Pose arguments:
pose_model=d('pose_model'), pose_batch_size=d('pose_batch_size'), pose_postfix=d('pose_postfix'),
cache_pose=d('cache_pose'), cache_frontal=d('cache_frontal'), smooth_poses=d('smooth_poses'),
# Landmarks arguments:
lms_model=d('lms_model'), lms_batch_size=d('lms_batch_size'), landmarks_postfix=d('landmarks_postfix'),
cache_landmarks=d('cache_landmarks'), smooth_landmarks=d('smooth_landmarks'),
# Segmentation arguments:
seg_model=d('seg_model'), seg_batch_size=d('seg_batch_size'), segmentation_postfix=d('segmentation_postfix'),
cache_segmentation=d('cache_segmentation'), smooth_segmentation=d('smooth_segmentation'),
seg_remove_mouth=d('seg_remove_mouth'),
# Finetune arguments:
finetune=d('finetune'), finetune_iterations=d('finetune_iterations'), finetune_lr=d('finetune_lr'),
finetune_batch_size=d('finetune_batch_size'), finetune_workers=d('finetune_workers'),
finetune_save=d('finetune_save'),
# Swapping arguments:
batch_size=d('batch_size'), reenactment_model=d('reenactment_model'), completion_model=d('completion_model'),
blending_model=d('blending_model'), criterion_id=d('criterion_id'), min_radius=d('min_radius'),
output_crop=d('output_crop'), renderer_process=d('renderer_process')):
face_swapping = FaceSwapping(
resolution, crop_scale, gpus, cpu_only, display, verbose, encoder_codec,
detection_model=detection_model, det_batch_size=det_batch_size, det_postfix=det_postfix,
iou_thresh=iou_thresh, min_length=min_length, min_size=min_size, center_kernel=center_kernel,
size_kernel=size_kernel, smooth_det=smooth_det, seq_postfix=seq_postfix, write_empty=write_empty,
pose_model=pose_model, pose_batch_size=pose_batch_size, pose_postfix=pose_postfix,
cache_pose=cache_pose, cache_frontal=cache_frontal, smooth_poses=smooth_poses,
lms_model=lms_model, lms_batch_size=lms_batch_size, landmarks_postfix=landmarks_postfix,
cache_landmarks=cache_landmarks, smooth_landmarks=smooth_landmarks,
seg_model=seg_model, seg_batch_size=seg_batch_size, segmentation_postfix=segmentation_postfix,
cache_segmentation=cache_segmentation, smooth_segmentation=smooth_segmentation,
seg_remove_mouth=seg_remove_mouth,
finetune=finetune, finetune_iterations=finetune_iterations, finetune_lr=finetune_lr,
finetune_batch_size=finetune_batch_size, finetune_workers=finetune_workers, finetune_save=finetune_save,
batch_size=batch_size, reenactment_model=reenactment_model, completion_model=completion_model,
blending_model=blending_model, criterion_id=criterion_id, min_radius=min_radius, output_crop=output_crop,
renderer_process=renderer_process)
if len(source) == 1 and len(target) == 1 and os.path.isfile(source[0]) and os.path.isfile(target[0]):
face_swapping(source[0], target[0], output, select_source, select_target)
else:
batch(source, target, output, face_swapping, postfix='.mp4', skip_existing=True)
def main(
input,
output=d('output'),
resolution=d('resolution'),
crop_scale=d('crop_scale'),
gpus=d('gpus'),
cpu_only=d('cpu_only'),
display=d('display'),
verbose=d('verbose'),
# Detection arguments:
detection_model=d('detection_model'),
det_batch_size=d('det_batch_size'),
det_postfix=d('det_postfix'),
# Sequence arguments:
iou_thresh=d('iou_thresh'),
min_length=d('min_length'),
min_size=d('min_size'),
center_kernel=d('center_kernel'),
size_kernel=d('size_kernel'),
smooth_det=d('smooth_det'),
seq_postfix=d('seq_postfix'),
write_empty=d('write_empty'),
# Pose arguments:
pose_model=d('pose_model'),
pose_batch_size=d('pose_batch_size'),
pose_postfix=d('pose_postfix'),
cache_pose=d('cache_pose'),
cache_frontal=d('cache_frontal'),
smooth_poses=d('smooth_poses'),
# Landmarks arguments:
lms_model=d('lms_model'),
lms_batch_size=d('lms_batch_size'),
landmarks_postfix=d('landmarks_postfix'),
cache_landmarks=d('cache_landmarks'),
smooth_landmarks=d('smooth_landmarks'),
# Segmentation arguments:
seg_model=d('seg_model'),
seg_batch_size=d('seg_batch_size'),
segmentation_postfix=d('segmentation_postfix'),
cache_segmentation=d('cache_segmentation'),
smooth_segmentation=d('smooth_segmentation'),
seg_remove_mouth=d('seg_remove_mouth')):
video_process = VideoProcessCallable(
resolution,
crop_scale,
gpus,
cpu_only,
display,
verbose,
detection_model=detection_model,
det_batch_size=det_batch_size,
det_postfix=det_postfix,
iou_thresh=iou_thresh,
min_length=min_length,
min_size=min_size,
center_kernel=center_kernel,
size_kernel=size_kernel,
smooth_det=smooth_det,
seq_postfix=seq_postfix,
write_empty=write_empty,
pose_model=pose_model,
pose_batch_size=pose_batch_size,
pose_postfix=pose_postfix,
cache_pose=cache_pose,
cache_frontal=cache_frontal,
smooth_poses=smooth_poses,
lms_model=lms_model,
lms_batch_size=lms_batch_size,
landmarks_postfix=landmarks_postfix,
cache_landmarks=cache_landmarks,
smooth_landmarks=smooth_landmarks,
seg_model=seg_model,
seg_batch_size=seg_batch_size,
segmentation_postfix=segmentation_postfix,
cache_segmentation=cache_segmentation,
smooth_segmentation=smooth_segmentation,
seg_remove_mouth=seg_remove_mouth)
if len(input) == 1 and os.path.isfile(input[0]):
video_process.cache(input, output)
else:
batch(input, None, output, video_process, postfix='.mp4')
