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Manual preview now draws 68-pt face landmarks

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It could be difficult to tell if the point cloud was 'correct' or not
when manually fixing a face detection. For 68-point face landmarks, the
facial landmarks are now drawn to make it easier to tell if the face
is correctly detected.
This commit is contained in:
Christopher Throwaway 2018-06-27 17:55:27 -05:00
parent 46b2aa86da
commit c8c8e8dadc
1 changed files with 16 additions and 0 deletions
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16
facelib/LandmarksProcessor.py
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@ -27,6 +27,15 @@ mean_face_y = np.array([
landmarks_2D = np.stack( [ mean_face_x, mean_face_y ], axis=1 )
# 68 point landmark definitions
landmarks_68_pt = { "mouth": (48,68),
"right_eyebrow": (17,22),
"left_eyebrow": (22,27),
"right_eye": (36,42),
"left_eye": (42,48),
"nose": (27,35),
"jaw": (0,17) }
def get_transform_mat (image_landmarks, output_size, face_type):
if not isinstance(image_landmarks, np.ndarray):
image_landmarks = np.array (image_landmarks)
@ -169,6 +178,13 @@ def draw_landmarks (image, image_landmarks, color):
cv2.circle(image, (x, y), 2, color, -1)
#text_color = colorsys.hsv_to_rgb ( (i%4) * (0.25), 1.0, 1.0 )
#cv2.putText(image, str(i), (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.1,text_color,1)
if len(image_landmarks) == 68:
for feat,idx_range in landmarks_68_pt.items():
for idx in range( idx_range[0], idx_range[1] - 1 ):
pt1 = tuple(image_landmarks[idx])
pt2 = tuple(image_landmarks[idx + 1])
cv2.line( image, pt1, pt2, color )
def draw_rect_landmarks (image, rect, image_landmarks, face_size, face_type):
image_utils.draw_rect (image, rect, (255,0,0), 2 )