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removing smooth_rect option

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Colombo 2020-02-18 10:28:01 +04:00
commit 4f928074b9
6 changed files with 119 additions and 180 deletions
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41
merger/MergeMasked.py
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@ -8,7 +8,7 @@ from facelib import FaceType, LandmarksProcessor
from core.interact import interact as io
from core.cv2ex import *
def MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img_bgr_uint8, img_bgr, img_face_landmarks, img_landmarks_prev, img_landmarks_next):
def MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img_bgr_uint8, img_bgr, img_face_landmarks):
img_size = img_bgr.shape[1], img_bgr.shape[0]
img_face_mask_a = LandmarksProcessor.get_image_hull_mask (img_bgr.shape, img_face_landmarks)
@ -21,26 +21,16 @@ def MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img
input_size = predictor_input_shape[0]
mask_subres_size = input_size*4
output_size = input_size
if cfg.super_resolution_power != 0 or cfg.smooth_rect:
if cfg.super_resolution_power != 0:
output_size *= 4
if cfg.smooth_rect:
average_frame_count=5
average_center_frame_count=1
else:
average_frame_count=0
average_center_frame_count=0
def get_transform_mat(*args, **kwargs):
return LandmarksProcessor.get_averaged_transform_mat (img_face_landmarks, img_landmarks_prev, img_landmarks_next, average_frame_count, average_center_frame_count, *args, **kwargs)
face_mat = get_transform_mat (output_size, face_type=cfg.face_type)
face_output_mat = get_transform_mat (output_size, face_type=cfg.face_type, scale= 1.0 + 0.01*cfg.output_face_scale)
face_mat = LandmarksProcessor.get_transform_mat (img_face_landmarks, output_size, face_type=cfg.face_type)
face_output_mat = LandmarksProcessor.get_transform_mat (img_face_landmarks, output_size, face_type=cfg.face_type, scale= 1.0 + 0.01*cfg.output_face_scale)
if mask_subres_size == output_size:
face_mask_output_mat = face_output_mat
else:
face_mask_output_mat = get_transform_mat (mask_subres_size, face_type=cfg.face_type, scale= 1.0 + 0.01*cfg.output_face_scale)
face_mask_output_mat = LandmarksProcessor.get_transform_mat (img_face_landmarks, mask_subres_size, face_type=cfg.face_type, scale= 1.0 + 0.01*cfg.output_face_scale)
dst_face_bgr = cv2.warpAffine( img_bgr , face_mat, (output_size, output_size), flags=cv2.INTER_CUBIC )
dst_face_bgr = np.clip(dst_face_bgr, 0, 1)
@ -67,11 +57,8 @@ def MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img
mod = cfg.super_resolution_power / 100.0
prd_face_bgr = cv2.resize(prd_face_bgr, (output_size,output_size))*(1.0-mod) + prd_face_bgr_enhanced*mod
prd_face_bgr = np.clip(prd_face_bgr, 0, 1)
elif cfg.smooth_rect:
prd_face_bgr = cv2.resize(prd_face_bgr, (output_size,output_size), cv2.INTER_CUBIC)
prd_face_bgr = np.clip(prd_face_bgr, 0, 1)
if cfg.super_resolution_power != 0 or cfg.smooth_rect:
if cfg.super_resolution_power != 0:
if predictor_masked:
prd_face_mask_a_0 = cv2.resize (prd_face_mask_a_0, (output_size, output_size), cv2.INTER_CUBIC)
else:
@ -88,14 +75,14 @@ def MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img
if cfg.mask_mode >= 4 and cfg.mask_mode <= 7:
full_face_fanseg_mat = get_transform_mat (cfg.fanseg_input_size, face_type=FaceType.FULL)
full_face_fanseg_mat = LandmarksProcessor.get_transform_mat (img_face_landmarks, cfg.fanseg_input_size, face_type=FaceType.FULL)
dst_face_fanseg_bgr = cv2.warpAffine(img_bgr, full_face_fanseg_mat, (cfg.fanseg_input_size,)*2, flags=cv2.INTER_CUBIC )
dst_face_fanseg_mask = cfg.fanseg_extract_func( FaceType.FULL, dst_face_fanseg_bgr )
if cfg.face_type == FaceType.FULL:
FAN_dst_face_mask_a_0 = cv2.resize (dst_face_fanseg_mask, (output_size,output_size), cv2.INTER_CUBIC)
else:
face_fanseg_mat = get_transform_mat (cfg.fanseg_input_size, face_type=cfg.face_type)
face_fanseg_mat = LandmarksProcessor.get_transform_mat (img_face_landmarks, cfg.fanseg_input_size, face_type=cfg.face_type)
fanseg_rect_corner_pts = np.array ( [ [0,0], [cfg.fanseg_input_size-1,0], [0,cfg.fanseg_input_size-1] ], dtype=np.float32 )
a = LandmarksProcessor.transform_points (fanseg_rect_corner_pts, face_fanseg_mat, invert=True )
@ -291,7 +278,7 @@ def MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img
k_size = int(frame_info.motion_power*cfg_mp)
if k_size >= 1:
k_size = np.clip (k_size+1, 2, 50)
if cfg.super_resolution_power != 0 or cfg.smooth_rect:
if cfg.super_resolution_power != 0:
k_size *= 2
out_face_bgr = imagelib.LinearMotionBlur (out_face_bgr, k_size , frame_info.motion_deg)
@ -331,20 +318,14 @@ def MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img
return out_img, out_merging_mask_a
def MergeMasked (predictor_func, predictor_input_shape, cfg, frame_info, prev_temporal_frame_infos=None, next_temporal_frame_infos=None):
def MergeMasked (predictor_func, predictor_input_shape, cfg, frame_info):
img_bgr_uint8 = cv2_imread(frame_info.filepath)
img_bgr_uint8 = imagelib.normalize_channels (img_bgr_uint8, 3)
img_bgr = img_bgr_uint8.astype(np.float32) / 255.0
outs = []
for face_num, img_landmarks in enumerate( frame_info.landmarks_list ):
img_landmarks_prev = [ x.landmarks_list[0] for x in prev_temporal_frame_infos if len(x.landmarks_list) != 0] \
if prev_temporal_frame_infos is not None else []
img_landmarks_next = [ x.landmarks_list[0] for x in next_temporal_frame_infos if len(x.landmarks_list) != 0] \
if next_temporal_frame_infos is not None else []
out_img, out_img_merging_mask = MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img_bgr_uint8, img_bgr, img_landmarks, img_landmarks_prev, img_landmarks_next)
out_img, out_img_merging_mask = MergeMaskedFace (predictor_func, predictor_input_shape, cfg, frame_info, img_bgr_uint8, img_bgr, img_landmarks)
outs += [ (out_img, out_img_merging_mask) ]
#Combining multiple face outputs