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https://github.com/iperov/DeepFaceLab.git
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5ac7e5d7f1
Pixel loss may help to enhance fine details and stabilize face color. Use it only if quality does not improve over time. SAE: previous SAE model will not work with this update. Greatly decreased chance of model collapse. Increased model accuracy. Residual blocks now default and this option has been removed. Improved 'learn mask'. Added masked preview (switch by space key) Converter: fixed rct/lct in seamless mode added mask mode (6) learned*FAN-prd*FAN-dst added mask editor, its created for refining dataset for FANSeg model, and not for production, but you can spend your time and test it in regular fakes with face obstructions
53 lines
2.3 KiB
Python
53 lines
2.3 KiB
Python
from enum import IntEnum
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import cv2
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import numpy as np
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from utils.cv2_utils import *
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class SampleType(IntEnum):
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IMAGE = 0 #raw image
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FACE_BEGIN = 1
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FACE = 1 #aligned face unsorted
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FACE_YAW_SORTED = 2 #sorted by yaw
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FACE_YAW_SORTED_AS_TARGET = 3 #sorted by yaw and included only yaws which exist in TARGET also automatic mirrored
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FACE_WITH_CLOSE_TO_SELF = 4
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FACE_END = 4
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QTY = 5
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class Sample(object):
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def __init__(self, sample_type=None, filename=None, face_type=None, shape=None, landmarks=None, ie_polys=None, pitch=None, yaw=None, mirror=None, close_target_list=None):
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self.sample_type = sample_type if sample_type is not None else SampleType.IMAGE
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self.filename = filename
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self.face_type = face_type
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self.shape = shape
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self.landmarks = np.array(landmarks) if landmarks is not None else None
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self.ie_polys = ie_polys
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self.pitch = pitch
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self.yaw = yaw
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self.mirror = mirror
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self.close_target_list = close_target_list
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def copy_and_set(self, sample_type=None, filename=None, face_type=None, shape=None, landmarks=None, ie_polys=None, pitch=None, yaw=None, mirror=None, close_target_list=None):
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return Sample(
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sample_type=sample_type if sample_type is not None else self.sample_type,
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filename=filename if filename is not None else self.filename,
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face_type=face_type if face_type is not None else self.face_type,
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shape=shape if shape is not None else self.shape,
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landmarks=landmarks if landmarks is not None else self.landmarks.copy(),
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ie_polys=ie_polys if ie_polys is not None else self.ie_polys,
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pitch=pitch if pitch is not None else self.pitch,
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yaw=yaw if yaw is not None else self.yaw,
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mirror=mirror if mirror is not None else self.mirror,
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close_target_list=close_target_list if close_target_list is not None else self.close_target_list)
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def load_bgr(self):
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img = cv2_imread (self.filename).astype(np.float32) / 255.0
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if self.mirror:
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img = img[:,::-1].copy()
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return img
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def get_random_close_target_sample(self):
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if self.close_target_list is None:
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return None
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return self.close_target_list[randint (0, len(self.close_target_list)-1)]
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