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Merge branch 4.x

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This commit is contained in:
Alexander Smorkalov
2026-02-11 13:54:39 +03:00
committed by Alexander Smorkalov
parent 1719aa1339 a6c10358a4
commit 82ff8e45e9
468 changed files with 16647 additions and 11284 deletions
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modules/python/package/setup.py
+2
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@@ -67,6 +67,8 @@ def main():
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
"Programming Language :: C++",
"Programming Language :: Python :: Implementation :: CPython",
"Topic :: Scientific/Engineering",
modules/python/standalone.cmake
+3
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@@ -29,6 +29,9 @@ if(NOT PYTHON_NUMPY_INCLUDE_DIRS)
message(FATAL_ERROR "Can't find Python 'numpy' development files")
endif()
include("${OpenCV_SOURCE_DIR}/cmake/OpenCVInstallLayout.cmake")
include("${OpenCV_SOURCE_DIR}/cmake/OpenCVDetectDLPack.cmake")
status("-----------------------------------------------------------------")
status(" Python:")
status(" Interpreter:" "${PYTHON_EXECUTABLE} (ver ${PYTHON_VERSION_STRING})")
modules/python/test/test_cuda.py
+1 -3
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@@ -52,9 +52,9 @@ class cuda_test(NewOpenCVTests):
self.assertTrue(asyncstream.cudaPtr() != 0)
def test_cuda_buffer_pool(self):
stream_a = cv.cuda.Stream()
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)
@@ -70,7 +70,6 @@ class cuda_test(NewOpenCVTests):
self.assertTrue(cuMat.step == 0)
self.assertTrue(cuMat.size() == (0, 0))
@unittest.skip("failed test")
def test_cuda_convertTo(self):
# setup
npMat_8UC4 = (np.random.random((128, 128, 4)) * 255).astype(np.uint8)
@@ -106,7 +105,6 @@ class cuda_test(NewOpenCVTests):
stream.waitForCompletion()
self.assertTrue(np.array_equal(npMat_32FC4, npMat_32FC4_out))
@unittest.skip("failed test")
def test_cuda_copyTo(self):
# setup
npMat_8UC4 = (np.random.random((128, 128, 4)) * 255).astype(np.uint8)