| | |
| | 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() |
| | |
| | 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] |
| |
|
| | |
| | res_static = fliplr_regression( |
| | coords, flip_pairs, center_mode='static', center_x=root[0, 0]) |
| | assert_array_almost_equal(res_static, coords_flipped) |
| |
|
| | |
| | res_root = fliplr_regression( |
| | coords, flip_pairs, center_mode='root', center_index=0) |
| | assert_array_almost_equal(res_root, coords_flipped) |
| |
|
