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SAEHD:
added option Eyes priority (y/n) fix eye problems during training ( especially on HD architectures ) by forcing the neural network to train eyes with higher priority before/after https://i.imgur.com/YQHOuSR.jpg It does not guarantee the right eye direction.
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Colombo
parent
4f928074b9
commit
9598ba0141
5 changed files with 105 additions and 60 deletions
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@ -35,11 +35,12 @@ class SampleProcessor(object):
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MODE_BGR = 40 #BGR
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MODE_G = 41 #Grayscale
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MODE_GGG = 42 #3xGrayscale
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MODE_FACE_MASK_HULL = 43 #mask hull as grayscale
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MODE_FACE_MASK_ALL_HULL = 43 #mask all hull as grayscale
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MODE_FACE_MASK_EYES_HULL = 44 #mask eyes hull as grayscale
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MODE_FACE_MASK_STRUCT = 45 #mask structure as grayscale
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MODE_BGR_SHUFFLE = 46 #BGR shuffle
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MODE_BGR_RANDOM_HSV_SHIFT = 47
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MODE_FACE_MASK_ALL_EYES_HULL = 45 #combo all + eyes as grayscale
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MODE_FACE_MASK_STRUCT = 46 #mask structure as grayscale
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MODE_BGR_SHUFFLE = 47 #BGR shuffle
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MODE_BGR_RANDOM_HSV_SHIFT = 48
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MODE_END = 50
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class Options(object):
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@ -107,11 +108,13 @@ class SampleProcessor(object):
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if target_face_type == SPTF.NONE:
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raise ValueError("target face type must be defined for face samples")
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else:
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if mode_type == SPTF.MODE_FACE_MASK_HULL:
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raise ValueError("MODE_FACE_MASK_HULL applicable only for face samples")
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if mode_type == SPTF.MODE_FACE_MASK_ALL_HULL:
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raise ValueError("MODE_FACE_MASK_ALL_HULL applicable only for face samples")
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if mode_type == SPTF.MODE_FACE_MASK_EYES_HULL:
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raise ValueError("MODE_FACE_MASK_EYES_HULL applicable only for face samples")
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elif mode_type == SPTF.MODE_FACE_MASK_STRUCT:
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if mode_type == SPTF.MODE_FACE_MASK_ALL_EYES_HULL:
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raise ValueError("MODE_FACE_MASK_ALL_EYES_HULL applicable only for face samples")
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if mode_type == SPTF.MODE_FACE_MASK_STRUCT:
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raise ValueError("MODE_FACE_MASK_STRUCT applicable only for face samples")
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can_warp = (img_type==SPTF.IMG_WARPED or img_type==SPTF.IMG_WARPED_TRANSFORMED)
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@ -141,16 +144,33 @@ class SampleProcessor(object):
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if mode_type == SPTF.NONE:
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raise ValueError ('expected MODE_ type')
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if mode_type == SPTF.MODE_FACE_MASK_HULL:
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if sample.eyebrows_expand_mod is not None:
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img = LandmarksProcessor.get_image_hull_mask (sample_bgr.shape, sample.landmarks, eyebrows_expand_mod=sample.eyebrows_expand_mod )
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else:
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img = LandmarksProcessor.get_image_hull_mask (sample_bgr.shape, sample.landmarks)
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if mode_type == SPTF.MODE_FACE_MASK_ALL_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_EYES_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_ALL_EYES_HULL:
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if mode_type == SPTF.MODE_FACE_MASK_ALL_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_ALL_EYES_HULL:
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if sample.eyebrows_expand_mod is not None:
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all_mask = LandmarksProcessor.get_image_hull_mask (sample_bgr.shape, sample.landmarks, eyebrows_expand_mod=sample.eyebrows_expand_mod )
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else:
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all_mask = LandmarksProcessor.get_image_hull_mask (sample_bgr.shape, sample.landmarks)
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all_mask = np.clip(all_mask, 0, 1)
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if mode_type == SPTF.MODE_FACE_MASK_EYES_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_ALL_EYES_HULL:
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eyes_mask = LandmarksProcessor.get_image_eye_mask (sample_bgr.shape, sample.landmarks)
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eyes_mask = np.clip(eyes_mask, 0, 1)
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if mode_type == SPTF.MODE_FACE_MASK_ALL_HULL:
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img = all_mask
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elif mode_type == SPTF.MODE_FACE_MASK_EYES_HULL:
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img = eyes_mask
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elif mode_type == SPTF.MODE_FACE_MASK_ALL_EYES_HULL:
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img = all_mask + eyes_mask
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if sample.ie_polys is not None:
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sample.ie_polys.overlay_mask(img)
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elif mode_type == SPTF.MODE_FACE_MASK_EYES_HULL:
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img = LandmarksProcessor.get_image_eye_mask (sample_bgr.shape, sample.landmarks)
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elif mode_type == SPTF.MODE_FACE_MASK_STRUCT:
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if sample.eyebrows_expand_mod is not None:
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@ -186,12 +206,13 @@ class SampleProcessor(object):
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if sample.face_type == FaceType.MARK_ONLY:
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mat = LandmarksProcessor.get_transform_mat (sample.landmarks, sample.shape[0], target_ft)
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if mode_type == SPTF.MODE_FACE_MASK_HULL or \
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if mode_type == SPTF.MODE_FACE_MASK_ALL_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_EYES_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_ALL_EYES_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_STRUCT:
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img = cv2.warpAffine( img, mat, (sample.shape[0],sample.shape[0]), flags=cv2.INTER_CUBIC )
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img = imagelib.warp_by_params (params, img, can_warp, can_transform, can_flip=True, border_replicate=False)
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img = cv2.resize( img, (resolution,resolution), cv2.INTER_CUBIC )[...,None]
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img = cv2.warpAffine( img, mat, (sample.shape[0],sample.shape[0]), flags=cv2.INTER_LINEAR )
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img = imagelib.warp_by_params (params, img, can_warp, can_transform, can_flip=True, border_replicate=False, cv2_inter=cv2.INTER_LINEAR)
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img = cv2.resize( img, (resolution,resolution), cv2.INTER_LINEAR )[...,None]
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else:
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img = cv2.warpAffine( img, mat, (sample.shape[0],sample.shape[0]), flags=cv2.INTER_CUBIC )
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img = imagelib.warp_by_params (params, img, can_warp, can_transform, can_flip=True, border_replicate=True)
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@ -200,11 +221,12 @@ class SampleProcessor(object):
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else:
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mat = LandmarksProcessor.get_transform_mat (sample.landmarks, resolution, target_ft)
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if mode_type == SPTF.MODE_FACE_MASK_HULL or \
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if mode_type == SPTF.MODE_FACE_MASK_ALL_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_EYES_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_STRUCT:
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img = imagelib.warp_by_params (params, img, can_warp, can_transform, can_flip=True, border_replicate=False)
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img = cv2.warpAffine( img, mat, (resolution,resolution), borderMode=cv2.BORDER_CONSTANT, flags=cv2.INTER_CUBIC )[...,None]
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mode_type == SPTF.MODE_FACE_MASK_ALL_EYES_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_STRUCT:
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img = imagelib.warp_by_params (params, img, can_warp, can_transform, can_flip=True, border_replicate=False, cv2_inter=cv2.INTER_LINEAR)
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img = cv2.warpAffine( img, mat, (resolution,resolution), borderMode=cv2.BORDER_CONSTANT, flags=cv2.INTER_LINEAR )[...,None]
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else:
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img = imagelib.warp_by_params (params, img, can_warp, can_transform, can_flip=True, border_replicate=True)
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img = cv2.warpAffine( img, mat, (resolution,resolution), borderMode=cv2.BORDER_REPLICATE, flags=cv2.INTER_CUBIC )
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@ -213,10 +235,11 @@ class SampleProcessor(object):
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img = cv2.resize( img, (resolution,resolution), cv2.INTER_CUBIC )
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if mode_type == SPTF.MODE_FACE_MASK_HULL or \
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if mode_type == SPTF.MODE_FACE_MASK_ALL_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_EYES_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_ALL_EYES_HULL or \
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mode_type == SPTF.MODE_FACE_MASK_STRUCT:
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out_sample = np.clip(img.astype(np.float32), 0, 1)
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out_sample = img.astype(np.float32)
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else:
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img = np.clip(img.astype(np.float32), 0, 1)
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