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| # Copyright (c) OpenMMLab. All rights reserved. | |
| import numpy as np | |
| from numpy.testing import assert_array_almost_equal | |
| from mmpose.core import (affine_transform, flip_back, fliplr_joints, | |
| fliplr_regression, get_affine_transform, rotate_point, | |
| transform_preds) | |
| def test_affine_transform(): | |
| pt = np.array([0, 1]) | |
| trans = np.array([[1, 0, 1], [0, 1, 0]]) | |
| result = affine_transform(pt, trans) | |
| assert_array_almost_equal(result, np.array([1, 1]), decimal=4) | |
| assert isinstance(result, np.ndarray) | |
| def test_rotate_point(): | |
| src_point = np.array([0, 1]) | |
| rot_rad = np.pi / 2. | |
| result = rotate_point(src_point, rot_rad) | |
| assert_array_almost_equal(result, np.array([-1, 0]), decimal=4) | |
| assert isinstance(result, list) | |
| def test_fliplr_joints(): | |
| joints = np.array([[0, 0, 0], [1, 1, 0]]) | |
| joints_vis = np.array([[1], [1]]) | |
| joints_flip, _ = fliplr_joints(joints, joints_vis, 5, [[0, 1]]) | |
| res = np.array([[3, 1, 0], [4, 0, 0]]) | |
| assert_array_almost_equal(joints_flip, res) | |
| def test_flip_back(): | |
| heatmaps = np.random.random([1, 2, 32, 32]) | |
| flipped_heatmaps = flip_back(heatmaps, [[0, 1]]) | |
| heatmaps_new = flip_back(flipped_heatmaps, [[0, 1]]) | |
| assert_array_almost_equal(heatmaps, heatmaps_new) | |
| heatmaps = np.random.random([1, 2, 32, 32]) | |
| flipped_heatmaps = flip_back(heatmaps, [[0, 1]]) | |
| heatmaps_new = flipped_heatmaps[..., ::-1] | |
| assert_array_almost_equal(heatmaps[:, 0], heatmaps_new[:, 1]) | |
| assert_array_almost_equal(heatmaps[:, 1], heatmaps_new[:, 0]) | |
| ori_heatmaps = heatmaps.copy() | |
| # test in-place flip | |
| heatmaps = heatmaps[:, :, :, ::-1] | |
| assert_array_almost_equal(ori_heatmaps[:, :, :, ::-1], heatmaps) | |
| def test_transform_preds(): | |
| coords = np.random.random([2, 2]) | |
| center = np.array([50, 50]) | |
| scale = np.array([100 / 200.0, 100 / 200.0]) | |
| size = np.array([100, 100]) | |
| result = transform_preds(coords, center, scale, size) | |
| assert_array_almost_equal(coords, result) | |
| coords = np.random.random([2, 2]) | |
| center = np.array([50, 50]) | |
| scale = np.array([100 / 200.0, 100 / 200.0]) | |
| size = np.array([101, 101]) | |
| result = transform_preds(coords, center, scale, size, use_udp=True) | |
| assert_array_almost_equal(coords, result) | |
| def test_get_affine_transform(): | |
| center = np.array([50, 50]) | |
| scale = np.array([100 / 200.0, 100 / 200.0]) | |
| size = np.array([100, 100]) | |
| result = get_affine_transform(center, scale, 0, size) | |
| trans = np.array([[1, 0, 0], [0, 1, 0]]) | |
| assert_array_almost_equal(trans, result) | |
| def test_flip_regression(): | |
| coords = np.random.rand(3, 3) | |
| flip_pairs = [[1, 2]] | |
| root = coords[:1] | |
| coords_flipped = coords.copy() | |
| coords_flipped[1] = coords[2] | |
| coords_flipped[2] = coords[1] | |
| coords_flipped[..., 0] = 2 * root[..., 0] - coords_flipped[..., 0] | |
| # static mode | |
| res_static = fliplr_regression( | |
| coords, flip_pairs, center_mode='static', center_x=root[0, 0]) | |
| assert_array_almost_equal(res_static, coords_flipped) | |
| # root mode | |
| res_root = fliplr_regression( | |
| coords, flip_pairs, center_mode='root', center_index=0) | |
| assert_array_almost_equal(res_root, coords_flipped) | |