def demo_for_kinect():
# data_dir = "E:/git/python-learning-notes/tutorial/kinect2/dataset/kitnect3d"
data_dir = "/media/dm/dm/X2/Pose/dataset/kitnet_data/panjinquan"
image, joint_world = load_data(data_dir, flag=5)
joint_world = -joint_world * 1000
kps_lines = [
[0, 1],
[1, 20],
[20, 2],
[2, 3], # Spine
[20, 4],
[4, 5],
[5, 6],
[6, 7],
[7, 21],
[7, 22], # Left arm and hand
[20, 8],
[8, 9],
[9, 10],
[10, 11],
[11, 23],
[11, 24], # Right arm and hand
[0, 12],
[12, 13],
[13, 14],
[14, 15], # Left leg
[0, 16],
[16, 17],
[17, 18],
[18, 19]
] # Right leg
# show in 世界坐标系
vis.vis_3d(joint_world, kps_lines, coordinate="WC", title="WC")
kp_vis = CameraTools()
# show in 相机坐标系
joint_cam = kp_vis.convert_wc_to_cc(joint_world)
vis.vis_3d(joint_cam, kps_lines, coordinate="CC", title="CC")
joint_img = kp_vis.convert_cc_to_ic(joint_cam)
# show in 像素坐标系
kpt_2d = joint_img[:, 0:2]
image = image_processing.draw_key_point_in_image(image,
key_points=[kpt_2d],
pointline=kps_lines)
image_processing.cv_show_image("image_dict", image)
def demo_for_human36m():
joint_world = [[-91.679, 154.404, 907.261],
[-223.23566, 163.80551, 890.5342],
[-188.4703, 14.077106, 475.1688],
[-261.84055, 186.55286, 61.438915],
[39.877888, 145.00247, 923.98785],
[-11.675994, 160.89919, 484.39148],
[-51.550297, 220.14624, 35.834396],
[-132.34781, 215.73018, 1128.8396],
[-97.1674, 202.34435, 1383.1466],
[-112.97073, 127.96946, 1477.4457],
[-120.03289, 190.96477, 1573.4],
[25.895456, 192.35947, 1296.1571],
[107.10581, 116.050285, 1040.5062],
[129.8381, -48.024918, 850.94806],
[-230.36955, 203.17923, 1311.9639],
[-315.40536, 164.55284, 1049.1747],
[-350.77136, 43.442127, 831.3473],
[-102.237045, 197.76935, 1304.0605]]
joint_world = np.asarray(joint_world)
# 关节点连接线
kps_lines = ((0, 7), (7, 8), (8, 9), (9, 10), (8, 11), (11, 12), (12, 13),
(8, 14), (14, 15), (15, 16), (0, 1), (1, 2), (2, 3), (0, 4),
(4, 5), (5, 6))
# show in 世界坐标系
vis.vis_3d(joint_world,
kps_lines,
coordinate="WC",
title="WC",
set_lim=True,
isshow=True)
kp_vis = CameraTools()
# show in 相机坐标系
joint_cam = kp_vis.convert_wc_to_cc(joint_world)
vis.vis_3d(joint_cam,
kps_lines,
coordinate="CC",
title="CC",
set_lim=True,
isshow=True)
joint_img = kp_vis.convert_cc_to_ic(joint_cam)
joint_world1 = kp_vis.convert_cc_to_wc(joint_cam)
vis.vis_3d(joint_world1,
kps_lines,
coordinate="WC",
title="WC",
set_lim=True,
isshow=True)
# show in 像素坐标系
kpt_2d = joint_img[:, 0:2]
image_path = "./data/s_01_act_02_subact_01_ca_02_000001.jpg"
image = image_processing.read_image(image_path)
image = image_processing.draw_key_point_in_image(image,
key_points=[kpt_2d],
pointline=kps_lines)
image_processing.cv_show_image("image_dict", image)
def demo_for_kinect():
flip_transform = np.asarray([[1, 0, 0],
[0, -1, 0],
[0, 0, -1]])
# flip_transform = np.linalg.inv(flip_transform)
# data_dir = "E:/git/python-learning-notes/tutorial/kinect2/dataset/kitnect3d"
data_dir = "/media/dm/dm/X2/Pose/dataset/kitnet_data/panjinquan" # flag= 5
# data_dir = "/media/dm/dm/X2/Pose/dataset/kitnet_data/dengjianxiang" # 241,245,348
image, joint_world = load_data(data_dir, flag=503)
h, w, d = image.shape
joint_world = convert_kinect2h36m(joint_world)
joint_world = joint_world * 1000
joint_world = np.dot(-flip_transform, joint_world.T).T # R * (pt - T)
# kps_lines = [[0, 1], [1, 20], [20, 2], [2, 3], # Spine
# [20, 4], [4, 5], [5, 6], [6, 7], [7, 21], [7, 22], # Left arm and hand
# [20, 8], [8, 9], [9, 10], [10, 11], [11, 23], [11, 24], # Right arm and hand
# [0, 12], [12, 13], [13, 14], [14, 15], # Left leg
# [0, 16], [16, 17], [17, 18], [18, 19]] # Right leg
kps_lines = ((0, 7), (7, 8), (8, 9), (9, 10), (8, 11), (11, 12), (12, 13), (8, 14), (14, 15),
(15, 16), (0, 1), (1, 2), (2, 3), (0, 4), (4, 5), (5, 6))
# show in 世界坐标系
vis.vis_3d(joint_world, kps_lines, coordinate="WC", title="WC", set_lim=True)
kp_vis = KeyPointsVisual()
# show in 相机坐标系
joint_cam = kp_vis.convert_wc_to_cc(joint_world)
vis.vis_3d(joint_cam, kps_lines, coordinate="CC", title="CC", set_lim=True)
joint_cam = np.dot(flip_transform, joint_cam.T).T # R * (pt - T)
joint_img = kp_vis.convert_cc_to_ic(joint_cam)
# show in 像素坐标系
kpt_2d = joint_img[:, 0:2]
image = image_processing.draw_key_point_in_image(image, key_points=[kpt_2d], pointline=kps_lines)
image_processing.cv_show_image("image_dict", image)
def demo_for_human36m():
from modules.utils_3d.data import human36m_data
# x,y,z
# joint_world = human36m_data.data0
joint_world = human36m_data.data2 * 1000
# joint_world = human36m_data.data1*1000
joint_world = np.asarray(joint_world)
kps_lines = human36m_data.kps_lines
# show in 世界坐标系
vis.vis_3d(joint_world, kps_lines, coordinate="WC", title="WC", set_lim=True)
kp_vis = KeyPointsVisual()
# show in 相机坐标系
joint_cam = kp_vis.convert_wc_to_cc(joint_world)
vis.vis_3d(joint_cam, kps_lines, coordinate="CC", title="CC", set_lim=True)
joint_img = kp_vis.convert_cc_to_ic(joint_cam)
# show in 像素坐标系
kpt_2d = joint_img[:, 0:2]
image_path = "/media/dm/dm1/git/python-learning-notes/modules/utils_3d/data/s_01_act_02_subact_01_ca_02_000001.jpg"
image = image_processing.read_image(image_path)
image = image_processing.draw_key_point_in_image(image, key_points=[kpt_2d], pointline=kps_lines)
image_processing.cv_show_image("image_dict", image)
[-132.34781, 215.73018, 1128.8396],
[-97.1674, 202.34435, 1383.1466],
[-112.97073, 127.96946, 1477.4457],
[-120.03289, 190.96477, 1573.4],
[25.895456, 192.35947, 1296.1571],
[107.10581, 116.050285, 1040.5062],
[129.8381, -48.024918, 850.94806],
[-230.36955, 203.17923, 1311.9639],
[-315.40536, 164.55284, 1049.1747],
[-350.77136, 43.442127, 831.3473],
[-102.237045, 197.76935, 1304.0605]]
joint_world = np.asarray(joint_world)
kps_lines = ((0, 7), (7, 8), (8, 9), (9, 10), (8, 11), (11, 12), (12, 13), (8, 14), (14, 15),
(15, 16), (0, 1), (1, 2), (2, 3), (0, 4), (4, 5), (5, 6))
# show in 世界坐标系
vis.vis_3d(joint_world, kps_lines, coordinate="WC", title="WC")
human36m = Human36M()
# show in 相机坐标系
joint_cam = human36m.convert_wc_to_cc(joint_world)
vis.vis_3d(joint_cam, kps_lines, coordinate="CC", title="CC")
joint_img = human36m.convert_cc_to_ic(joint_cam)
# show in 像素坐标系
kpt_2d = joint_img[:, 0:2]
image_path = "data/s_01_act_02_subact_01_ca_02_000001.jpg"
image = image_processing.read_image(image_path)
image = image_processing.draw_key_point_in_image(image, key_points=[kpt_2d], pointline=kps_lines)
image_processing.cv_show_image("image_dict", image)