def _output_processing(self, extract_media, size):
""" Prepare faces for output
Loads the aligned face, generate the thumbnail, perform any processing actions and verify
the output.
Parameters
----------
extract_media: :class:`plugins.extract.pipeline.ExtractMedia`
Output from :class:`plugins.extract.pipeline.Extractor`
size: int
The size that the aligned face should be created at
"""
for face in extract_media.detected_faces:
face.load_aligned(extract_media.image, size=size, centering="head")
face.thumbnail = generate_thumbnail(face.aligned.face,
size=96,
quality=60)
self._post_process.do_actions(extract_media)
extract_media.remove_image()
faces_count = len(extract_media.detected_faces)
if faces_count == 0:
logger.verbose("No faces were detected in image: %s",
os.path.basename(extract_media.filename))
if not self._verify_output and faces_count > 1:
self._verify_output = True
def extract_one_face(self, alignment, image):
""" Extract one face from image """
logger.trace("Extracting one face: (frame: '%s', alignment: %s)",
self.current_frame, alignment)
face = DetectedFace()
face.from_alignment(alignment, image=image)
face.load_aligned(image, size=self.size, centering="head")
face.thumbnail = generate_thumbnail(face.aligned.face, size=80, quality=60)
return face
def post_edit_trigger(self, frame_index, face_index):
""" Update the jpg thumbnail and the viewport thumbnail on a face edit.
Parameters
----------
frame_index: int
The frame that the face is being set for
face_index: int
The face index within the frame
"""
face = self._frame_faces[frame_index][face_index]
aligned = AlignedFace(face.landmarks_xy,
image=self._globals.current_frame["image"],
centering="head",
size=96)
face.thumbnail = generate_thumbnail(aligned.face, size=96)
self._tk_edited.set(True)
def _output_faces(self, filename, image):
""" For each frame save out the faces
Parameters
----------
filename: str
The filename (without the full path) of the current frame
image: :class:`numpy.ndarray`
The full frame that faces are to be extracted from
Returns
-------
int
The total number of faces that have been extracted
"""
logger.trace("Outputting frame: %s", filename)
face_count = 0
frame_name = os.path.splitext(filename)[0]
faces = self._select_valid_faces(filename, image)
if not faces:
return face_count
if self._is_legacy:
faces = self._process_legacy(filename, image, faces)
for idx, face in enumerate(faces):
output = "{}_{}.png".format(frame_name, str(idx))
meta = dict(alignments=face.to_png_meta(),
source=dict(
alignments_version=self._alignments.version,
original_filename=output,
face_index=idx,
source_filename=filename,
source_is_video=self._frames.is_video,
source_frame_dims=image.shape[:2]))
self._saver.save(
output, encode_image(face.aligned.face, ".png", metadata=meta))
if not self._arguments.large and self._is_legacy:
face.thumbnail = generate_thumbnail(face.aligned.face,
size=96,
quality=60)
self._alignments.data[filename]["faces"][
idx] = face.to_alignment()
face_count += 1
self._saver.close()
return face_count
def _set_thumbail(self, filename, frame, frame_index):
""" Extracts the faces from the frame and adds to alignments file
Parameters
----------
filename: str
The filename of the frame within the alignments file
frame: :class:`numpy.ndarray`
The frame that contains the faces
frame_index: int
The frame index of this frame in the :attr:`_frame_faces`
"""
for face_idx, face in enumerate(self._frame_faces[frame_index]):
aligned = AlignedFace(face.landmarks_xy,
image=frame,
centering="head",
size=96)
face.thumbnail = generate_thumbnail(aligned.face, size=96)
self._alignments.thumbnails.add_thumbnail(filename, face_idx, face.thumbnail)
with self._pbar["lock"]:
self._pbar["pbar"].update(1)
def post_edit_trigger(self, frame_index, face_index):
""" Update the jpg thumbnail, the viewport thumbnail, the landmark masks and the aligned
face on a face edit.
Parameters
----------
frame_index: int
The frame that the face is being set for
face_index: int
The face index within the frame
"""
face = self._frame_faces[frame_index][face_index]
face.load_aligned(None, force=True) # Update average distance
face.mask = self._extractor.get_masks(frame_index, face_index)
aligned = AlignedFace(face.landmarks_xy,
image=self._globals.current_frame["image"],
centering="head",
size=96)
face.thumbnail = generate_thumbnail(aligned.face, size=96)
if self._globals.filter_mode == "Misaligned Faces":
self._detected_faces.tk_face_count_changed.set(True)
self._tk_edited.set(True)
