mmpose/tests/test_datasets/test_transforms/test_converting.py

110 lines
5.1 KiB
Python

# Copyright (c) OpenMMLab. All rights reserved.
from unittest import TestCase
import numpy as np
from mmpose.datasets.transforms import KeypointConverter
from mmpose.testing import get_coco_sample
class TestKeypointConverter(TestCase):
def setUp(self):
# prepare dummy bottom-up data sample with COCO metainfo
self.data_info = get_coco_sample(
img_shape=(240, 320), num_instances=4, with_bbox_cs=True)
def test_transform(self):
# 1-to-1 mapping
mapping = [(3, 0), (6, 1), (16, 2), (5, 3)]
transform = KeypointConverter(num_keypoints=5, mapping=mapping)
results = transform(self.data_info.copy())
# check shape
self.assertEqual(results['keypoints'].shape[0],
self.data_info['keypoints'].shape[0])
self.assertEqual(results['keypoints'].shape[1], 5)
self.assertEqual(results['keypoints'].shape[2], 2)
self.assertEqual(results['keypoints_visible'].shape[0],
self.data_info['keypoints_visible'].shape[0])
self.assertEqual(results['keypoints_visible'].shape[1], 5)
# check value
for source_index, target_index in mapping:
self.assertTrue((results['keypoints'][:, target_index] ==
self.data_info['keypoints'][:,
source_index]).all())
self.assertEqual(results['keypoints_visible'].ndim, 3)
self.assertEqual(results['keypoints_visible'].shape[2], 2)
self.assertTrue(
(results['keypoints_visible'][:, target_index, 0] ==
self.data_info['keypoints_visible'][:, source_index]).all())
# 2-to-1 mapping
mapping = [((3, 5), 0), (6, 1), (16, 2), (5, 3)]
transform = KeypointConverter(num_keypoints=5, mapping=mapping)
results = transform(self.data_info.copy())
# check shape
self.assertEqual(results['keypoints'].shape[0],
self.data_info['keypoints'].shape[0])
self.assertEqual(results['keypoints'].shape[1], 5)
self.assertEqual(results['keypoints'].shape[2], 2)
self.assertEqual(results['keypoints_visible'].shape[0],
self.data_info['keypoints_visible'].shape[0])
self.assertEqual(results['keypoints_visible'].shape[1], 5)
# check value
for source_index, target_index in mapping:
if isinstance(source_index, tuple):
source_index, source_index2 = source_index
self.assertTrue(
(results['keypoints'][:, target_index] == 0.5 *
(self.data_info['keypoints'][:, source_index] +
self.data_info['keypoints'][:, source_index2])).all())
self.assertEqual(results['keypoints_visible'].ndim, 3)
self.assertEqual(results['keypoints_visible'].shape[2], 2)
self.assertTrue(
(results['keypoints_visible'][:, target_index, 0] ==
self.data_info['keypoints_visible'][:, source_index] *
self.data_info['keypoints_visible'][:,
source_index2]).all())
else:
self.assertTrue(
(results['keypoints'][:, target_index] ==
self.data_info['keypoints'][:, source_index]).all())
self.assertEqual(results['keypoints_visible'].ndim, 3)
self.assertEqual(results['keypoints_visible'].shape[2], 2)
self.assertTrue(
(results['keypoints_visible'][:, target_index, 0] ==
self.data_info['keypoints_visible'][:,
source_index]).all())
# check 3d keypoint
self.data_info['keypoints_3d'] = np.random.random((4, 17, 3))
self.data_info['target_idx'] = [-1]
mapping = [(3, 0), (6, 1), (16, 2), (5, 3)]
transform = KeypointConverter(num_keypoints=5, mapping=mapping)
results = transform(self.data_info.copy())
# check shape
self.assertEqual(results['keypoints_3d'].shape[0],
self.data_info['keypoints_3d'].shape[0])
self.assertEqual(results['keypoints_3d'].shape[1], 5)
self.assertEqual(results['keypoints_3d'].shape[2], 3)
self.assertEqual(results['keypoints_visible'].shape[0],
self.data_info['keypoints_visible'].shape[0])
self.assertEqual(results['keypoints_visible'].shape[1], 5)
# check value
for source_index, target_index in mapping:
self.assertTrue(
(results['keypoints_3d'][:, target_index] ==
self.data_info['keypoints_3d'][:, source_index]).all())
self.assertEqual(results['keypoints_visible'].ndim, 3)
self.assertEqual(results['keypoints_visible'].shape[2], 2)
self.assertTrue(
(results['keypoints_visible'][:, target_index, 0] ==
self.data_info['keypoints_visible'][:, source_index]).all())