github/DeepFaceLab
1
0
Fork 0
mirror of https://github.com/iperov/DeepFaceLab.git synced 2025-08-20 21:43:21 -07:00
Code Issues Projects Releases Packages Wiki Activity Actions

manual extractor: increased FPS,

Browse source 
sort by final : now you can specify target number of images,
converter: fix seamless mask and exception,
huge refactoring
This commit is contained in:
iperov 2019-02-28 11:56:31 +04:00
commit 438213e97c
30 changed files with 1834 additions and 1718 deletions
Download patch file Download diff file Expand all files Collapse all files

7
facelib/LandmarksExtractor.py
View file

@ -3,10 +3,6 @@ import os
import cv2
from pathlib import Path
from utils import std_utils
def transform(point, center, scale, resolution):
pt = np.array ( [point[0], point[1], 1.0] )
h = 200.0 * scale
@ -123,8 +119,7 @@ class LandmarksExtractor(object):
image = crop(input_image, center, scale).transpose ( (2,0,1) ).astype(np.float32) / 255.0
image = np.expand_dims(image, 0)
with std_utils.suppress_stdout_stderr():
predicted = self.keras_model.predict (image)
predicted = self.keras_model.predict (image)
pts_img = get_pts_from_predict ( predicted[-1][0], center, scale)
pts_img = [ ( int(pt[0]), int(pt[1]) ) for pt in pts_img ]

2
facelib/LandmarksProcessor.py
View file

@ -134,7 +134,7 @@ def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0):
elif face_type == FaceType.HEAD:
padding = (output_size / 64) * 24
else:
raise ValueError ('wrong face_type')
raise ValueError ('wrong face_type: ', face_type)
mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2]
mat = mat * (output_size - 2 * padding)