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#!/usr/bin/env python
'''
CUDA-accelerated Computer Vision functions
'''
# Python 2/3 compatibility
from __future__ import print_function
import numpy as np
import cv2 as cv
import os
from tests_common import NewOpenCVTests, unittest
class cuda_test(NewOpenCVTests):
def setUp(self):
super(cuda_test, self).setUp()
if not cv.cuda.getCudaEnabledDeviceCount():
self.skipTest("No CUDA-capable device is detected")
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)
if __name__ == '__main__':
NewOpenCVTests.bootstrap()