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Slightly optimized eye alignment and landmark decoding.

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This commit is contained in:
Emiliana 2020-08-10 14:40:40 +02:00
parent cc7667734b
commit 50224a1e2e
1 changed files with 12 additions and 21 deletions
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33
tracker.py
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@ -7,6 +7,7 @@ import time
import queue
import threading
import copy
from skimage.transform import SimilarityTransform
from retinaface import RetinaFaceDetector
from remedian import remedian
@ -783,19 +784,12 @@ class Tracker():
return upper_left, lower_right, center, radius, c1, a
def prepare_eye(self, frame, full_frame, lms, flip):
outer_pt = tuple(lms[0])
inner_pt = tuple(lms[1])
h, w, _ = frame.shape
(x1, y1), (x2, y2), center, radius, reference, a = self.corners_to_eye((outer_pt, inner_pt), w, h, flip)
im = rotate_image(frame[:, :, ::], a, reference)
im = im[int(y1):int(y2), int(x1):int(x2),:]
if np.prod(im.shape) < 1:
return None, None, None, None, None, None
transform = SimilarityTransform()
transform.estimate(lms, np.array([[0,16], [32,16]]))
M = transform.params[0:2, :]
im = cv2.warpAffine(frame, M, (32, 32), 0)
if flip:
im = cv2.flip(im, 1)
scale = np.array([(x2 - x1), (y2 - y1)]) / 32.
im = cv2.resize(im, (32, 32), interpolation=cv2.INTER_LINEAR)
#im = self.equalize(im)
if self.debug_gaze:
if not flip:
full_frame[0:32, 0:32] = im
@ -804,7 +798,7 @@ class Tracker():
im = im.astype(np.float32)[:,:,::-1] / self.std - self.mean
im = np.expand_dims(im, 0)
im = np.transpose(im, (0,3,2,1))
return im, x1, y1, scale, reference, a
return im, np.linalg.inv(transform.params)
def extract_face(self, frame, lms):
lms = np.array(lms)[:,0:2][:,::-1]
@ -830,10 +824,10 @@ class Tracker():
e_y = [0,0]
scale = [0,0]
reference = [None, None]
angles = [0, 0]
M_inv = [np.identity(3), np.identity(3)]
face_frame, lms, offset = self.extract_face(frame, lms)
(right_eye, e_x[0], e_y[0], scale[0], reference[0], angles[0]) = self.prepare_eye(face_frame, frame, np.array([lms[36,0:2], lms[39,0:2]]), False)
(left_eye, e_x[1], e_y[1], scale[1], reference[1], angles[1]) = self.prepare_eye(face_frame, frame, np.array([lms[42,0:2], lms[45,0:2]]), True)
(right_eye, M_inv[0]) = self.prepare_eye(face_frame, frame, np.array([lms[36,0:2], lms[39,0:2]]), False)
(left_eye, M_inv[1]) = self.prepare_eye(face_frame, frame, np.array([lms[42,0:2], lms[45,0:2]]), True)
if right_eye is None or left_eye is None:
return [(1.0, 0.0, 0.0, 0.0), (1.0, 0.0, 0.0, 0.0)]
both_eyes = np.concatenate((right_eye, left_eye))
@ -874,13 +868,10 @@ class Tracker():
frame[int(eye_y+1), 32+int(eye_x+1)] = (0, 0, 255)
frame[int(eye_y), 32+int(eye_x+1)] = (0, 0, 255)
if i == 0:
eye_x = e_x[i] + scale[i][0] * eye_x
else:
eye_x = e_x[i] + scale[i][0] * (32. - eye_x)
eye_y = e_y[i] + scale[i][1] * eye_y
eye_x, eye_y = rotate(reference[i], (eye_x, eye_y), -angles[i])
if i == 1:
eye_x = 32. - eye_x
eye_x, eye_y, w = M_inv[i].dot(np.array([eye_x, eye_y, 1]))
eye_x = eye_x + offset[0]
eye_y = eye_y + offset[1]
eye_state.append([open[i], eye_y, eye_x, conf])