Minor code readability

A-Yaghoubian · Dec 24, 2022 · a3527fd · a3527fd
1 parent 534ed46
commit a3527fd
Showing 1 changed file with 6 additions and 6 deletions.
diff --git a/utils/swap_func.py b/utils/swap_func.py
@@ -32,7 +32,7 @@ def __exit__(self, *_):
 
 
 def run_inference(opt, source, target, RetinaFace,
-                  ArcFace, G, result_img_path, source_z=None):
+                  ArcFace, FaceDancer, result_img_path, source_z=None):
     try:
 
         if not isinstance(target, str):
@@ -81,15 +81,15 @@ def run_inference(opt, source, target, RetinaFace,
             im_aligned = cv2.warpAffine(im, M, (256, 256), borderValue=0.0)
 
             # face swap
-            changed_face_cage = G.predict([np.expand_dims((im_aligned - 127.5) / 127.5, axis=0), source_z])
-            changed_face = (changed_face_cage[0] + 1) / 2
+            face_swap = FaceDancer.predict([np.expand_dims((im_aligned - 127.5) / 127.5, axis=0), source_z])
+            face_swap = (face_swap[0] + 1) / 2
 
             # get inverse transformation landmarks
             transformed_lmk = transform_landmark_points(M, lm_align)
 
             # warp image back
             iM, _ = inverse_estimate_norm(lm_align, transformed_lmk, 256, "arcface", shrink_factor=1.0)
-            iim_aligned = cv2.warpAffine(changed_face, iM, im_shape, borderValue=0.0)
+            iim_aligned = cv2.warpAffine(face_swap, iM, im_shape, borderValue=0.0)
 
             # blend swapped face with target image
             blend_mask = cv2.warpAffine(blend_mask_base, iM, im_shape, borderValue=0.0)
@@ -108,7 +108,7 @@ def run_inference(opt, source, target, RetinaFace,
         sys.exit(0)
 
 
-def video_swap(opt, face, input_video, RetinaFace, ArcFace, G, out_video_filename):
+def video_swap(opt, face, input_video, RetinaFace, ArcFace, FaceDancer, out_video_filename):
     video_forcheck = VideoFileClip(input_video)
 
     if video_forcheck.audio is None:
@@ -138,7 +138,7 @@ def video_swap(opt, face, input_video, RetinaFace, ArcFace, G, out_video_filenam
     for frame_index in tqdm(range(frame_count)):
         ret, frame = video.read()
         if ret:
-            _, source_z = run_inference(opt, face, frame, RetinaFace, ArcFace, G,
+            _, source_z = run_inference(opt, face, frame, RetinaFace, ArcFace, FaceDancer,
                                         os.path.join('./tmp_frames', 'frame_{:0>7d}.png'.format(frame_index)),
                                         source_z=source_z)
     video.release()