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63 lines
2.2 KiB
Python
63 lines
2.2 KiB
Python
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#!/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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from tests_common import NewOpenCVTests
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class test_gapi_infer(NewOpenCVTests):
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def test_getAvailableTargets(self):
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targets = cv.dnn.getAvailableTargets(cv.dnn.DNN_BACKEND_OPENCV)
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self.assertTrue(cv.dnn.DNN_TARGET_CPU in targets)
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def test_age_gender_infer(self):
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# NB: Check IE
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if not cv.dnn.DNN_TARGET_CPU in cv.dnn.getAvailableTargets(cv.dnn.DNN_BACKEND_INFERENCE_ENGINE):
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return
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root_path = '/omz_intel_models/intel/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013'
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model_path = self.find_file(root_path + '.xml', [os.environ.get('OPENCV_DNN_TEST_DATA_PATH')])
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weights_path = self.find_file(root_path + '.bin', [os.environ.get('OPENCV_DNN_TEST_DATA_PATH')])
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img_path = self.find_file('cv/face/david2.jpg', [os.environ.get('OPENCV_TEST_DATA_PATH')])
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device_id = 'CPU'
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img = cv.resize(cv.imread(img_path), (62,62))
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# OpenCV DNN
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net = cv.dnn.readNetFromModelOptimizer(model_path, weights_path)
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net.setPreferableBackend(cv.dnn.DNN_BACKEND_INFERENCE_ENGINE)
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net.setPreferableTarget(cv.dnn.DNN_TARGET_CPU)
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blob = cv.dnn.blobFromImage(img)
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net.setInput(blob)
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dnn_age, dnn_gender = net.forward(net.getUnconnectedOutLayersNames())
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# OpenCV G-API
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g_in = cv.GMat()
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inputs = cv.GInferInputs()
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inputs.setInput('data', g_in)
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outputs = cv.gapi.infer("net", inputs)
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age_g = outputs.at("age_conv3")
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gender_g = outputs.at("prob")
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comp = cv.GComputation(cv.GIn(g_in), cv.GOut(age_g, gender_g))
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pp = cv.gapi.ie.params("net", model_path, weights_path, device_id)
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nets = cv.gapi.networks(pp)
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args = cv.compile_args(nets)
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gapi_age, gapi_gender = comp.apply(cv.gin(img), args=cv.compile_args(cv.gapi.networks(pp)))
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# Check
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self.assertEqual(0.0, cv.norm(dnn_gender, gapi_gender, cv.NORM_INF))
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self.assertEqual(0.0, cv.norm(dnn_age, gapi_age, cv.NORM_INF))
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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