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Added filters for NaN values.

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This commit is contained in:
Emiliana 2020-08-11 16:27:20 +02:00
parent acfcfd7ea3
commit 9ce7d39505
1 changed files with 8 additions and 0 deletions
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8
tracker.py
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@ -683,6 +683,7 @@ class Tracker():
t_y = crop_x1 + scale_x * (res * np.floor(np.mod(t_m, self.out_res_i)) / self.out_res + t_off_y)
avg_conf = np.average(t_conf)
lms = np.stack([t_x, t_y, t_conf], 1)
lms[np.isnan(lms).any(axis=1)] = np.array([0.,0.,0.], dtype=np.float32)
return (avg_conf, np.array(lms))
def estimate_depth(self, face_info):
@ -723,6 +724,8 @@ class Tracker():
pts_3d[0:66] = (pts_3d[0:66].dot(self.inverse_camera.transpose()) - face_info.translation).dot(inverse_rotation.transpose())
pnp_error = np.power(lms[0:17,0:2] - t_reference[0:17,0:2], 2).sum()
pnp_error += np.power(lms[30,0:2] - t_reference[30,0:2], 2).sum()
if np.isnan(pnp_error):
pnp_error = 9999999.
for i, pt in enumerate(face_info.face_3d[66:70]):
if i == 2:
# Right eyeball
@ -761,6 +764,7 @@ class Tracker():
pt_3d = pt_3d - face_info.translation
pt_3d = inverse_rotation.dot(pt_3d)
pts_3d[66+i,:] = pt_3d[:]
pts_3d[np.isnan(pts_3d).any(axis=1)] = np.array([0.,0.,0.], dtype=np.float32)
pnp_error = np.sqrt(pnp_error / (2.0 * image_pts.shape[0]))
if pnp_error > 300:
@ -900,6 +904,8 @@ class Tracker():
eye_y = eye_y + offset[1]
eye_state.append([open[i], eye_y, eye_x, conf])
eye_state = np.array(eye_state)
eye_state[np.isnan(eye_state).any(axis=1)] = np.array([1.,0.,0.,0.], dtype=np.float32)
return eye_state
def assign_face_info(self, results):
@ -1107,6 +1113,8 @@ class Tracker():
h += 2 * h * self.bbox_growth
faces.append((x,y,w,h))
self.faces = faces
self.faces = [x for x in self.faces if not np.isnan(np.array(x)).any()]
self.detected = len(self.faces)
duration = (time.perf_counter() - start) * 1000
if not self.silent: