1996scarlet / openvtuber Goto Github PK

Segmentation fault: 11

Stack trace:
  [bt] (0) 1   libmxnet.so                         0x000000011e2c42b0 mxnet::Storage::Get() + 4880
  [bt] (1) 2   libsystem_platform.dylib            0x00007fff72b2b5fd _sigtramp + 29
  [bt] (2) 3   libsystem_platform.dylib            0x00007fff72b29074 _platform_strcpy + 84
  [bt] (3) 4   CoreFoundation                      0x00007fff3899e7fe __104-[CFPrefsSearchListSource synchronouslySendDaemonMessage:andAgentMessage:andDirectMessage:replyHandler:]_block_invoke.119 + 83
  [bt] (4) 5   CoreFoundation                      0x00007fff3899e79a CFPREFERENCES_IS_WAITING_FOR_SYSTEM_AND_USER_CFPREFSDS + 74
  [bt] (5) 6   CoreFoundation                      0x00007fff3899e634 -[CFPrefsSearchListSource synchronouslySendDaemonMessage:andAgentMessage:andDirectMessage:replyHandler:] + 172
  [bt] (6) 7   CoreFoundation                      0x00007fff3899d10d -[CFPrefsSearchListSource alreadylocked_generationCountFromListOfSources:count:] + 215
  [bt] (7) 8   CoreFoundation                      0x00007fff3899ce4b -[CFPrefsSearchListSource alreadylocked_getDictionary:] + 360
  [bt] (8) 9   CoreFoundation                      0x00007fff3899ca74 -[CFPrefsSearchListSource alreadylocked_copyValueForKey:] + 152

    def render_68pts_lines(self, frame, landmarks, color_keypoints, color_lines):
        for pts68 in landmarks:
            # Base contour
            for i in range(16):
                cv2.line(frame, tuple(pts68[i]), tuple(pts68[i + 1]), color_lines, 2, lineType=cv2.LINE_AA)
                cv2.circle(frame, tuple(pts68[i]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[16]), 1, color_keypoints, 1, cv2.LINE_AA)

            # Left Eyebrow
            for i in range(17, 21):
                cv2.line(frame, tuple(pts68[i]), tuple(pts68[i + 1]), color_lines, 2, lineType=cv2.LINE_AA)
                cv2.circle(frame, tuple(pts68[i]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[21]), 1, color_keypoints, 1, cv2.LINE_AA)

            # Right Eyebrow
            for i in range(22, 26):
                cv2.line(frame, tuple(pts68[i]), tuple(pts68[i + 1]), color_lines, 2, lineType=cv2.LINE_AA)
                cv2.circle(frame, tuple(pts68[i]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[26]), 1, color_keypoints, 1, cv2.LINE_AA)

            # Nose
            for i in range(27, 30):
                cv2.line(frame, tuple(pts68[i]), tuple(pts68[i + 1]), color_lines, 2, lineType=cv2.LINE_AA)
                cv2.circle(frame, tuple(pts68[i]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[30]), 1, color_keypoints, 1, cv2.LINE_AA)
            for i in range(31, 35):
                cv2.line(frame, tuple(pts68[i]), tuple(pts68[i + 1]), color_lines, 2, lineType=cv2.LINE_AA)
                cv2.circle(frame, tuple(pts68[i]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[35]), 1, color_keypoints, 1, cv2.LINE_AA)

            # Left eye
            for i in range(36, 41):
                cv2.line(frame, tuple(pts68[i]), tuple(pts68[i + 1]), color_lines, 2, lineType=cv2.LINE_AA)
                cv2.circle(frame, tuple(pts68[i]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.line(frame, tuple(pts68[41]), tuple(pts68[36]), color_lines, 2, lineType=cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[41]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[36]), 1, color_keypoints, 1, cv2.LINE_AA)

            # Right eye
            for i in range(42, 47):
                cv2.line(frame, tuple(pts68[i]), tuple(pts68[i + 1]), color_lines, 2, lineType=cv2.LINE_AA)
                cv2.circle(frame, tuple(pts68[i]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.line(frame, tuple(pts68[47]), tuple(pts68[42]), color_lines, 2, lineType=cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[47]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[42]), 1, color_keypoints, 1, cv2.LINE_AA)

            # Lips outer
            for i in range(48, 60):
                cv2.line(frame, tuple(pts68[i]), tuple(pts68[i + 1]), color_lines, 2, lineType=cv2.LINE_AA)
                cv2.circle(frame, tuple(pts68[i]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.line(frame, tuple(pts68[48]), tuple(pts68[60]), color_lines, 2, lineType=cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[60]), 1, color_keypoints, 1, cv2.LINE_AA)
            cv2.circle(frame, tuple(pts68[48]), 1, color_keypoints, 1, cv2.LINE_AA)

    YAW_THD = 45
    SIN_LEFT_THETA = 2 * sin(pi / 4)
    SIN_UP_THETA = sin(pi / 6)

         while capture.isOpened():
                ret, frame = capture.read()
                if not ret:
                    break

                bboxes, _ = fd.inference(frame)

                detections = []
                for landmarks in fa.get_landmarks(frame, bboxes):
                    euler_angle = hp.get_head_pose(landmarks)
                    pitch, yaw, roll = euler_angle[:, 0]

                    eye_markers = np.take(landmarks, fa.eye_bound, axis=0)

                    eye_centers = np.average(eye_markers, axis=1)

                    eye_lengths = (landmarks[[39, 93]] - landmarks[[35, 89]])[:, 0]

                    iris_left = gs.get_mesh(frame, eye_lengths[0], eye_centers[0])
                    pupil_left, _ = gs.draw_pupil(iris_left, frame, thickness=1)

                    iris_right = gs.get_mesh(frame, eye_lengths[1], eye_centers[1])
                    pupil_right, _ = gs.draw_pupil(iris_right, frame, thickness=1)

                    pupils = np.array([pupil_left, pupil_right])

                    poi = landmarks[[35, 89]], landmarks[[39, 93]], pupils, eye_centers
                    theta, pha, delta = calculate_3d_gaze(frame, poi)

                    if yaw > 30:
                        end_mean = delta[0]
                    elif yaw < -30:
                        end_mean = delta[1]
                    else:
                        end_mean = np.average(delta, axis=0)

                    if end_mean[0] < 0:
                        zeta = arctan(end_mean[1] / end_mean[0]) + pi
                    else:
                        zeta = arctan(end_mean[1] / (end_mean[0] + 1e-7))

                    if roll < 0:
                        roll += 180
                    else:
                        roll -= 180

                    real_angle = zeta + roll * pi / 180

                    R = norm(end_mean)
                    offset = R * cos(real_angle), R * sin(real_angle)

                    landmarks[[38, 92]] = landmarks[[34, 88]] = eye_centers

                    draw_sticker(frame, offset, pupils, landmarks)
                    detections.append({
                        'landmarks': [lm.tolist() for lm in landmarks],
                        'offset': offset,
                        'pupils': [p.tolist() for p in pupils],
                        'iris_left': [il.tolist() for il in iris_left],
                        'iris_right': [ir.tolist() for ir in iris_right]
                    })

                json_result[frame_id] = detections
                sink.write(frame)
                frame_id += 1

def draw_sticker(src, offset, pupils, landmarks,
                 blink_thd=0.22,
                 arrow_color=(0, 125, 255), copy=False):
    if copy:
        src = src.copy()

    left_eye_hight = landmarks[33, 1] - landmarks[40, 1]
    left_eye_width = landmarks[39, 0] - landmarks[35, 0]

    right_eye_hight = landmarks[87, 1] - landmarks[94, 1]
    right_eye_width = landmarks[93, 0] - landmarks[89, 0]

    for mark in landmarks.reshape(-1, 2).astype(int):
        cv2.circle(src, tuple(mark), radius=1,
                   color=(0, 0, 255), thickness=-1)

    if left_eye_hight / left_eye_width > blink_thd:
        cv2.arrowedLine(src, tuple(pupils[0].astype(int)),
                        tuple((offset+pupils[0]).astype(int)), arrow_color, 2)

    if right_eye_hight / right_eye_width > blink_thd:
        cv2.arrowedLine(src, tuple(pupils[1].astype(int)),
                        tuple((offset+pupils[1]).astype(int)), arrow_color, 2)

    return src

INFO: Initialized TensorFlow Lite runtime.
Traceback (most recent call last):
  File "vtuber_link_start.py", line 38, in <module>
    sio.connect("http://192.168.14.131:6789")
  File "/home/charmve/.local/lib/python3.6/site-packages/socketio/client.py", line 282, in connect
    six.raise_from(exceptions.ConnectionError(exc.args[0]), None)
  File "<string>", line 3, in raise_from
socketio.exceptions.ConnectionError: Connection refused by the server

# ======================================================

sio = socketio.Client()

@sio.on('connect', namespace='/kizuna')
def on_connect():
    sio.emit('result_data', 0, namespace='/kizuna')

# sio.connect("http://127.0.0.1:6789")
sio.connect("192.168.14.131:6789")
sio.wait()

# ======================================================