wehub-resource-sync
69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
#!/usr/bin/env python
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import numpy as np
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import cv2 as cv
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import os
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import sys
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import unittest
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from tests_common import NewOpenCVTests
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try:
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if sys.version_info[:2] < (3, 0):
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raise unittest.SkipTest('Python 2.x is not supported')
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CLASSIFICATION_MODEL_PATH = "vision/classification/squeezenet/model/squeezenet1.0-9.onnx"
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class test_gapi_infer(NewOpenCVTests):
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def find_dnn_file(self, filename):
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return self.find_file(filename, [os.environ.get('OPENCV_GAPI_ONNX_MODEL_PATH')], False)
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def test_onnx_classification(self):
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model_path = self.find_dnn_file(CLASSIFICATION_MODEL_PATH)
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if model_path is None:
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raise unittest.SkipTest("Missing DNN test file")
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in_mat = cv.imread(
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self.find_file("cv/dpm/cat.png",
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[os.environ.get('OPENCV_TEST_DATA_PATH')]))
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g_in = cv.GMat()
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g_infer_inputs = cv.GInferInputs()
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g_infer_inputs.setInput("data_0", g_in)
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g_infer_out = cv.gapi.infer("squeeze-net", g_infer_inputs)
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g_out = g_infer_out.at("softmaxout_1")
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comp = cv.GComputation(cv.GIn(g_in), cv.GOut(g_out))
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net = cv.gapi.onnx.params("squeeze-net", model_path)
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net.cfgNormalize("data_0", False)
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try:
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out_gapi = comp.apply(cv.gin(in_mat), cv.gapi.compile_args(cv.gapi.networks(net)))
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except cv.error as err:
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if err.args[0] == "G-API has been compiled without ONNX support":
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raise unittest.SkipTest("G-API has been compiled without ONNX support")
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else:
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raise
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self.assertEqual((1, 1000, 1, 1), out_gapi.shape)
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except unittest.SkipTest as e:
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message = str(e)
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class TestSkip(unittest.TestCase):
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def setUp(self):
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self.skipTest('Skip tests: ' + message)
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def test_skip():
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pass
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pass
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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