ChingT

import numpy as np

from scipy.spatial.distance import cdist
import camera_models as cm

CORE = "Pupil Cam1 ID2"
PI = "PI world v1"

FHD = 1920, 1080
HD = 1280, 720

ChingT

import PIL.Image as Image
import cv2
import numpy as np


def main(data, image, n_bins, sigma_percentage):
    height, width, *_ = ref_image.shape
    if width > height:
        n_bins_x = int(n_bins)
        n_bins_y = int(n_bins * height / width)

ChingT

import cv2
import numpy as np

paper_size = 2100, 2100
cross_len = 20
center = paper_size[0] // 2, paper_size[1] // 2

marker = np.ones(paper_size) * 255
cv2.circle(marker, center, 940, (180, 180, 180), thickness=2)
cv2.circle(marker, center, 600, (0, 0, 0), thickness=-1)

ChingT

import cv2
import numpy as np


def rvec_to_yawpitchroll(rvec):
    """
    Convert rotation vector to yaw, pitch, roll
    Args:
        rvec: pose rotation vector (rvec can be obtained by
        [rotation_x, rotation_y, rotation_z] in head_pose_tacker_poses.csv)

ChingT

import cv2
import numpy as np

paper_size = 2100, 2100
cross_len = 20
center = paper_size[0] // 2, paper_size[1] // 2

marker = np.ones(paper_size) * 255
cv2.circle(marker, center, 940, (180, 180, 180), thickness=2)
cv2.circle(marker, center, 600, (0, 0, 0), thickness=-1)

ChingT

import json
import os

import cv2
import numpy as np


def calculate_matrix_diff_to_golden(scene_sn, rotation_matrix_scene):
    golden_scene_sn = "p69tb"
    if scene_sn in ("6tgbx", "rylzd", "vtukq"):

ChingT

import cv2
import numpy as np

import file_methods as fm


class Transformation:
    def __init__(self):
        self._all_extrinsic_eye1_world = fm.load_object(
            "/cluster/users/Ching/datasets/camera_extrinsics_measurement/all_extrinsic/"

ChingT

import cv2
import numpy as np
from scipy.optimize import least_squares

from head_pose_tracker.function import utils

np.set_printoptions(precision=4, suppress=True)


def get_camera_pose_gt(world, eye0, eye1):

ChingT

import cv2
import numpy as np
from PIL import Image

import file_methods as fm


def draw_apriltag(canvas, tag_id, pos, size):
    tag = cv2.resize(apriltags[tag_id], (size, size), interpolation=cv2.INTER_NEAREST)
    canvas[pos[1] : pos[1] + size, pos[0] : pos[0] + size, :] = tag