wassname/PointCNN
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Significantly clean and document code base. Project approximately complete.

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Austin J. Garrett
2018-04-08 19:47:11 -04:00
parent 8a4d826f91
commit 4af37be8fd
18 changed files with 497 additions and 472 deletions
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tests/test_basic.py
+38 -3
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@@ -4,14 +4,16 @@ import torch
from torch.autograd import Variable
import numpy as np
from pointcnn.core import XConv, knn_indices_func
from PointCNN import XConv, RandPointCNN, knn_indices_func_cpu
from PointCNN.tests import plot_pts_and_fts
np.random.seed(0)
class BasicTests(unittest.TestCase):
""" Basic test cases """
def test_xconv_shape(self):
self.assertTrue(True)
np.random.seed(0)
N = 4
D = 3
@@ -36,12 +38,45 @@ class BasicTests(unittest.TestCase):
P = Variable(torch.from_numpy(P))
ps = Variable(torch.from_numpy(ps))
out = knn_indices_func(ps, P, 2).numpy()
out = knn_indices_func_cpu(ps, P, 2).numpy()
target = np.array([[[1,2],
[2,1]]])
self.assertTrue(np.array_equal(target, out))
def test_pointcnn_shape(self):
N = 1
num_points = 1000
dims = 2
C_in = 4
K = 10
D = 1
layer1 = RandPointCNN(C_in, 8, dims, K, D, 1000, knn_indices_func_cpu).cuda()
layer2 = RandPointCNN( 8, 16, dims, K, D, 500, knn_indices_func_cpu).cuda()
layer3 = RandPointCNN( 16, 32, dims, K, D, 250, knn_indices_func_cpu).cuda()
layer4 = RandPointCNN( 32, 64, dims, K, D, 125, knn_indices_func_cpu).cuda()
layer5 = RandPointCNN( 64, 128, dims, K, D, 50, knn_indices_func_cpu).cuda()
pts = np.random.rand(N,num_points,dims).astype(np.float32)
fts = np.random.rand(N,num_points,C_in).astype(np.float32)
pts = Variable(torch.from_numpy(pts)).cuda()
fts = Variable(torch.from_numpy(fts)).cuda()
if True:
pts, fts = layer1((pts, fts))
else:
plot_pts_and_fts(pts, fts)
pts, fts = layer1((pts, fts))
plot_pts_and_fts(pts, fts)
pts, fts = layer2((pts, fts))
plot_pts_and_fts(pts, fts)
pts, fts = layer3((pts, fts))
plot_pts_and_fts(pts, fts)
pts, fts = layer4((pts, fts))
plot_pts_and_fts(pts, fts)
pts, fts = layer5((pts, fts))
plot_pts_and_fts(pts, fts)
if __name__ == "__main__":
unittest.main()