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faceswap/lib/alignments.py
torzdf 2783c27e00
Fix convert-adjust (#531)
* Add dimensions to alignments + refactor

* Add frame_dims + funcs to DetectFaces. Add alignments lib

* Convert Adjust working

* Refactor and tidy up
2018-11-07 20:21:22 +00:00

269 lines
9.9 KiB
Python

#!/usr/bin/env python3
""" Alignments file functions for reading, writing and manipulating
a serialized alignments file """
import os
from datetime import datetime
import cv2
from lib import Serializer
from lib.utils import rotate_landmarks
class Alignments():
""" Holds processes pertaining to the alignments file.
folder: folder alignments file is stored in
filename: Filename of alignments file excluding extension. If a
valid extension is provided, then it will be used to
decide the serializer, and the serializer argument will
be ignored.
serializer: If provided, this will be the format that the data is
saved in (if data is to be saved). Can be 'json', 'pickle'
or 'yaml'
"""
def __init__(self, folder, filename="alignments", serializer="json",
verbose=False):
self.verbose = verbose
self.serializer = self.get_serializer(filename, serializer)
self.file = self.get_location(folder, filename)
self.data = self.load()
# << PROPERTIES >> #
@property
def frames_count(self):
""" Return current frames count """
return len(self.data)
@property
def faces_count(self):
""" Return current faces count """
return sum(len(faces) for faces in self.data.values())
@property
def have_alignments_file(self):
""" Return whether an alignments file exists """
return os.path.exists(self.file)
# << INIT FUNCTIONS >> #
def get_serializer(self, filename, serializer):
""" Set the serializer to be used for loading and
saving alignments
If a filename with a valid extension is passed in
this will be used as the serializer, otherwise the
specified serializer will be used """
extension = os.path.splitext(filename)[1]
if extension in (".json", ".p", ".yaml", ".yml"):
retval = Serializer.get_serializer_from_ext(extension)
elif serializer not in ("json", "pickle", "yaml"):
raise ValueError("Error: {} is not a valid serializer. Use "
"'json', 'pickle' or 'yaml'")
else:
retval = Serializer.get_serializer(serializer)
if self.verbose:
print("Using {} serializer for alignments".format(retval.ext))
return retval
def get_location(self, folder, filename):
""" Return the path to alignments file """
extension = os.path.splitext(filename)[1]
if extension in (".json", ".p", ".yaml", ".yml"):
location = os.path.join(str(folder), filename)
else:
location = os.path.join(str(folder),
"{}.{}".format(filename,
self.serializer.ext))
if self.verbose:
print("Alignments filepath: {}".format(location))
return location
# << I/O >> #
def load(self):
""" Load the alignments data if it exists or create empty dict """
if not self.have_alignments_file:
raise ValueError("Error: Alignments file not found at "
"{}".format(self.file))
try:
print("Reading alignments from: {}".format(self.file))
with open(self.file, self.serializer.roptions) as align:
data = self.serializer.unmarshal(align.read())
except IOError as err:
print("Error: {} not read: {}".format(self.file, err.strerror))
exit(1)
return data
def reload(self):
""" Read the alignments data from the correct format """
self.data = self.load()
def save(self):
""" Write the serialized alignments file """
try:
print("Writing alignments to: {}".format(self.file))
with open(self.file, self.serializer.woptions) as align:
align.write(self.serializer.marshal(self.data))
except IOError as err:
print("Error: {} not written: {}".format(self.file, err.strerror))
def backup(self):
""" Backup copy of old alignments """
if not os.path.isfile(self.file):
return
now = datetime.now().strftime("%Y%m%d_%H%M%S")
src = self.file
split = os.path.splitext(src)
dst = split[0] + "_" + now + split[1]
print("Backing up original alignments to {}".format(dst))
os.rename(src, dst)
# << VALIDATION >> #
def frame_exists(self, frame):
""" return path of images that have faces """
return frame in self.data.keys()
def frame_has_faces(self, frame):
""" Return true if frame exists and has faces """
return bool(self.data.get(frame, list()))
def frame_has_multiple_faces(self, frame):
""" Return true if frame exists and has faces """
if not frame:
return False
return bool(len(self.data.get(frame, list())) > 1)
# << DATA >> #
def get_faces_in_frame(self, frame):
""" Return the alignments for the selected frame """
return self.data.get(frame, list())
def get_full_frame_name(self, frame):
""" Return a frame with extension for when the extension is
not known """
return next(key for key in self.data.keys()
if key.startswith(frame))
def count_faces_in_frame(self, frame):
""" Return number of alignments within frame """
return len(self.data.get(frame, list()))
# << MANIPULATION >> #
def delete_face_at_index(self, frame, idx):
""" Delete the face alignment for given frame at given index """
idx = int(idx)
if idx + 1 > self.count_faces_in_frame(frame):
return False
del self.data[frame][idx]
return True
def add_face(self, frame, alignment):
""" Add a new face for a frame and return it's index """
self.data[frame].append(alignment)
return self.count_faces_in_frame(frame) - 1
def update_face(self, frame, idx, alignment):
""" Replace a face for given frame and index """
self.data[frame][idx] = alignment
# << GENERATORS >> #
def yield_faces(self):
""" Yield face alignments for one image """
for frame_fullname, alignments in self.data.items():
frame_name = os.path.splitext(frame_fullname)[0]
yield frame_name, alignments, len(alignments), frame_fullname
@staticmethod
def yield_original_index_reverse(image_alignments, number_alignments):
""" Return the correct original index for
alignment in reverse order """
for idx, _ in enumerate(reversed(image_alignments)):
original_idx = number_alignments - 1 - idx
yield original_idx
# << LEGACY FUNCTIONS >> #
# < Original Frame Dimensions > #
# For dfaker and convert-adjust the original dimensions of a frame are
# required to calculate the transposed landmarks. As transposed landmarks
# will change on face size, we store original frame dimensions
# These were not previously required, so this adds the dimensions
# to the landmarks file
def get_legacy_no_dims(self):
""" Return a list of frames that do not contain the original frame
height and width attributes """
keys = list()
for key, val in self.data.items():
for alignment in val:
if "frame_dims" not in alignment.keys():
keys.append(key)
break
return keys
def add_dimensions(self, frame_name, dimensions):
""" Backward compatability fix. Add frame dimensions
to alignments """
for face in self.get_faces_in_frame(frame_name):
face["frame_dims"] = dimensions
# < Rotation > #
# The old rotation method would rotate the image to find a face, then
# store the rotated landmarks along with a rotation value to tell the
# convert process that it had to rotate the frame to find the landmarks.
# This is problematic for numerous reasons. The process now rotates the
# landmarks to correctly correspond with the original frame. The below are
# functions to convert legacy alignments to the currently supported
# infrastructure.
# This can eventually be removed
def get_legacy_rotation(self):
""" Return a list of frames with legacy rotations
Looks for an 'r' value in the alignments file that
is not zero """
keys = list()
for key, val in self.data.items():
if any(alignment.get("r", None) for alignment in val):
keys.append(key)
return keys
def rotate_existing_landmarks(self, frame_name):
""" Backwards compatability fix. Rotates the landmarks to
their correct position and deletes r
NB: The original frame dimensions must be passed in otherwise
the transformation cannot be performed """
for face in self.get_faces_in_frame(frame_name):
angle = face.get("r", 0)
if not angle:
return
dims = face["frame_dims"]
r_mat = self.get_original_rotation_matrix(dims, angle)
rotate_landmarks(face, r_mat)
del face["r"]
@staticmethod
def get_original_rotation_matrix(dimensions, angle):
""" Calculate original rotation matrix and invert """
height, width = dimensions
center = (width/2, height/2)
r_mat = cv2.getRotationMatrix2D( # pylint: disable=no-member
center, -1.0 * angle, 1.)
abs_cos = abs(r_mat[0, 0])
abs_sin = abs(r_mat[0, 1])
rotated_width = int(height*abs_sin + width*abs_cos)
rotated_height = int(height*abs_cos + width*abs_sin)
r_mat[0, 2] += rotated_width/2 - center[0]
r_mat[1, 2] += rotated_height/2 - center[1]
return r_mat