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authorThéo de la Hogue2023-02-28 09:41:15 +0100
committerThéo de la Hogue2023-02-28 09:41:15 +0100
commitddd417ca84c5e16ba30c441598d209d190bf4ad3 (patch)
treead75ba24d856f21d13efd460594b00e576deb322 /src/argaze.test
parentb6c9eb85ab587766f4658e0ef75039f9094a9620 (diff)
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Adding test for opencv cuda
Diffstat (limited to 'src/argaze.test')
-rw-r--r--src/argaze.test/OpenCVCuda.py80
1 files changed, 80 insertions, 0 deletions
diff --git a/src/argaze.test/OpenCVCuda.py b/src/argaze.test/OpenCVCuda.py
new file mode 100644
index 0000000..fd28abf
--- /dev/null
+++ b/src/argaze.test/OpenCVCuda.py
@@ -0,0 +1,80 @@
+#!/usr/bin/env python
+
+import unittest
+
+import numpy as np
+import cv2 as cv
+import os
+
+class cuda_test(unittest.TestCase):
+ """Test Cuda-accelerated OpenCV functions class."""
+
+ def test_setup(self):
+
+ self.assertGreater(cv.cuda.getCudaEnabledDeviceCount(), 0)
+
+ def test_cuda_upload_download(self):
+
+ npMat = (np.random.random((128, 128, 3)) * 255).astype(np.uint8)
+ cuMat = cv.cuda_GpuMat()
+ cuMat.upload(npMat)
+
+ self.assertTrue(np.allclose(cuMat.download(), npMat))
+
+ def test_cuda_upload_download_stream(self):
+
+ stream = cv.cuda_Stream()
+ npMat = (np.random.random((128, 128, 3)) * 255).astype(np.uint8)
+ cuMat = cv.cuda_GpuMat(128,128, cv.CV_8UC3)
+ cuMat.upload(npMat, stream)
+ npMat2 = cuMat.download(stream=stream)
+ stream.waitForCompletion()
+
+ self.assertTrue(np.allclose(npMat2, npMat))
+
+ def test_cuda_interop(self):
+
+ npMat = (np.random.random((128, 128, 3)) * 255).astype(np.uint8)
+ cuMat = cv.cuda_GpuMat()
+ cuMat.upload(npMat)
+
+ self.assertTrue(cuMat.cudaPtr() != 0)
+
+ stream = cv.cuda_Stream()
+ self.assertTrue(stream.cudaPtr() != 0)
+
+ asyncstream = cv.cuda_Stream(1) # cudaStreamNonBlocking
+ self.assertTrue(asyncstream.cudaPtr() != 0)
+
+ def test_cuda_buffer_pool(self):
+
+ cv.cuda.setBufferPoolUsage(True)
+ cv.cuda.setBufferPoolConfig(cv.cuda.getDevice(), 1024 * 1024 * 64, 2)
+ stream_a = cv.cuda.Stream()
+ pool_a = cv.cuda.BufferPool(stream_a)
+ cuMat = pool_a.getBuffer(1024, 1024, cv.CV_8UC3)
+ cv.cuda.setBufferPoolUsage(False)
+
+ self.assertEqual(cuMat.size(), (1024, 1024))
+ self.assertEqual(cuMat.type(), cv.CV_8UC3)
+
+ def test_cuda_release(self):
+
+ npMat = (np.random.random((128, 128, 3)) * 255).astype(np.uint8)
+ cuMat = cv.cuda_GpuMat()
+ cuMat.upload(npMat)
+ cuMat.release()
+
+ self.assertTrue(cuMat.cudaPtr() == 0)
+ self.assertTrue(cuMat.step == 0)
+ self.assertTrue(cuMat.size() == (0, 0))
+
+ def test_cuda_denoising(self):
+
+ self.assertEqual(True, hasattr(cv.cuda, 'fastNlMeansDenoising'))
+ self.assertEqual(True, hasattr(cv.cuda, 'fastNlMeansDenoisingColored'))
+ self.assertEqual(True, hasattr(cv.cuda, 'nonLocalMeans'))
+
+if __name__ == '__main__':
+
+ unittest.main() \ No newline at end of file