File size: 4,847 Bytes
a6dd040 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 |
import numpy as np
import unittest
import time
import torch
import MinkowskiEngineTest._C
from utils import load_file, batched_coordinates
class KernelRegionTestCase(unittest.TestCase):
def test(self):
coordinates = torch.IntTensor(
[[0, 1, -1], [0, 1, 0], [0, 1, 1], [0, 2, -1], [0, 2, 0], [0, 2, 1]]
)
kernel_size = torch.IntTensor([3, 3])
(in_maps, out_maps), N, t = MinkowskiEngineTest._C.kernel_map_test(
coordinates, coordinates, kernel_size
)
def test2(self):
coordinates = torch.IntTensor([[0, 1, -1], [0, 2, 1]])
kernel_size = torch.IntTensor([3, 3])
regions = MinkowskiEngineTest._C.region_iterator_test(coordinates, kernel_size)
self.assertEqual(
len(regions), len(coordinates) * torch.prod(kernel_size).item()
)
self.assertEqual(regions[0], [0, 0, -2])
self.assertEqual(regions[1], [0, 1, -2])
self.assertEqual(regions[2], [0, 2, -2])
self.assertEqual(regions[3], [0, 0, -1])
self.assertEqual(regions[4], [0, 1, -1])
self.assertEqual(regions[5], [0, 2, -1])
self.assertEqual(regions[6], [0, 0, 0])
self.assertEqual(regions[7], [0, 1, 0])
self.assertEqual(regions[8], [0, 2, 0])
def test_even(self):
coordinates = torch.IntTensor([[0, 1, -1], [0, 2, 1]])
kernel_size = torch.IntTensor([3, 2])
regions = MinkowskiEngineTest._C.region_iterator_test(coordinates, kernel_size)
self.assertEqual(
len(regions), len(coordinates) * torch.prod(kernel_size).item()
)
self.assertEqual(regions[0], [0, 0, -1])
self.assertEqual(regions[1], [0, 1, -1])
self.assertEqual(regions[2], [0, 2, -1])
self.assertEqual(regions[3], [0, 0, 0])
self.assertEqual(regions[4], [0, 1, 0])
self.assertEqual(regions[5], [0, 2, 0])
def test_even3(self):
coordinates = torch.IntTensor([[0, 1, -1, 3], [0, 2, 1, -2]])
kernel_size = torch.IntTensor([3, 2, 2])
regions = MinkowskiEngineTest._C.region_iterator_test(coordinates, kernel_size)
self.assertEqual(
len(regions), len(coordinates) * torch.prod(kernel_size).item()
)
self.assertEqual(regions[0], [0, 0, -1, 3])
self.assertEqual(regions[1], [0, 1, -1, 3])
self.assertEqual(regions[2], [0, 2, -1, 3])
self.assertEqual(regions[3], [0, 0, 0, 3])
self.assertEqual(regions[4], [0, 1, 0, 3])
self.assertEqual(regions[5], [0, 2, 0, 3])
self.assertEqual(regions[6], [0, 0, -1, 4])
self.assertEqual(regions[7], [0, 1, -1, 4])
self.assertEqual(regions[8], [0, 2, -1, 4])
self.assertEqual(regions[9], [0, 0, 0, 4])
self.assertEqual(regions[10], [0, 1, 0, 4])
self.assertEqual(regions[11], [0, 2, 0, 4])
def test_kernel_map1(self):
in_coordinates = torch.IntTensor([[0, 1, -1], [0, 2, 1]])
out_coordinates = torch.IntTensor([[0, 1, -1], [0, 2, 1], [1, 2, 1]])
kernel_size = torch.IntTensor([1, 1])
(in_maps, out_maps), num, t = MinkowskiEngineTest._C.kernel_map_test(
in_coordinates, out_coordinates, kernel_size
)
self.assertEqual(in_maps[0], [0, 1])
self.assertEqual(out_maps[0], [0, 1])
def test_kernel_map(self):
in_coordinates = torch.IntTensor([[0, 1, -1], [0, 2, 1]])
out_coordinates = torch.IntTensor([[0, 1, 0], [0, 1, 2], [1, 2, 1]])
kernel_size = torch.IntTensor([3, 3])
kernel_map, num, t = MinkowskiEngineTest._C.kernel_map_test(
in_coordinates, out_coordinates, kernel_size
)
in_maps = kernel_map[0]
out_maps = kernel_map[1]
self.assertEqual(len(in_maps), torch.prod(kernel_size).item())
self.assertEqual(in_maps[1], [0])
self.assertEqual(out_maps[1], [0])
self.assertEqual(in_maps[2], [1])
self.assertEqual(out_maps[2], [1])
def test_pcd(self):
coords, colors, pcd = load_file("1.ply")
kernel_size = torch.IntTensor([3, 3, 3])
for batch_size in [1, 5, 10, 20, 40]:
for voxel_size in [0.05, 0.035, 0.02]:
min_time = 100000
dcoords = torch.from_numpy(np.floor(coords / voxel_size)).int()
bcoords = batched_coordinates([dcoords for i in range(batch_size)])
for i in range(10):
kernel_map, num, t = MinkowskiEngineTest._C.kernel_map_test(
bcoords, bcoords, kernel_size
)
min_time = min(t, min_time)
num_kernels = np.sum([len(a) for a in kernel_map[0]])
print(f"{batch_size}\t{voxel_size}\t{num}\t{num_kernels}\t{min_time}")
|