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faceswap/scripts/extract.py

99 lines
3.9 KiB
Python

import cv2
from pathlib import Path
from tqdm import tqdm
import os
from lib.cli import DirectoryProcessor
from lib.utils import get_folder
from lib.multithreading import pool_process
from plugins.PluginLoader import PluginLoader
class ExtractTrainingData(DirectoryProcessor):
def create_parser(self, subparser, command, description):
self.parser = subparser.add_parser(
command,
help="Extract the faces from a pictures.",
description=description,
epilog="Questions and feedback: \
https://github.com/deepfakes/faceswap-playground"
)
def add_optional_arguments(self, parser):
parser.add_argument('-D', '--detector',
type=str,
choices=("hog", "cnn"), # case sensitive because this is used to load a plugin.
default="hog",
help="Detector to use. 'cnn' detects much more angles but will be much more resource intensive and may fail on large files.")
parser.add_argument('-f', '--filter',
type=str,
dest="filter",
default="filter.jpg",
help="Reference image for the person you want to process. Should be a front portrait"
)
parser.add_argument('-j', '--processes',
type=int,
default=1,
help="Number of processes to use.")
parser.add_argument('-dl', '--debug-landmarks',
action="store_true",
dest="debug_landmarks",
default=False,
help="Draw landmarks for debug.")
return parser
def process(self):
extractor_name = "Align" # TODO Pass as argument
self.extractor = PluginLoader.get_extractor(extractor_name)()
processes = self.arguments.processes
try:
if processes != 1:
files = list(self.read_directory())
for filename, faces in tqdm(pool_process(self.processFiles, files, processes=processes), total = len(files)):
self.num_faces_detected += 1
self.faces_detected[os.path.basename(filename)] = faces
else:
try:
for filename in tqdm(self.read_directory()):
image = cv2.imread(filename)
self.faces_detected[os.path.basename(filename)] = self.handleImage(image, filename)
except Exception as e:
print('Failed to extract from image: {}. Reason: {}'.format(filename, e))
finally:
self.write_alignments()
def processFiles(self, filename):
try:
image = cv2.imread(filename)
return filename, self.handleImage(image, filename)
except Exception as e:
print('Failed to extract from image: {}. Reason: {}'.format(filename, e))
def handleImage(self, image, filename):
count = 0
faces = self.get_faces(image)
rvals = []
for idx, face in faces:
count = idx
# Draws landmarks for debug
if self.arguments.debug_landmarks:
for (x, y) in face.landmarksAsXY():
cv2.circle(image, (x, y), 2, (0, 0, 255), -1)
resized_image = self.extractor.extract(image, face, 256)
output_file = get_folder(self.output_dir) / Path(filename).stem
cv2.imwrite(str(output_file) + str(idx) + Path(filename).suffix, resized_image)
f = {
"x": face.x,
"w": face.w,
"y": face.y,
"h": face.h,
"landmarksXY": face.landmarksAsXY()
}
rvals.append(f)
return rvals