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