#!/usr/bin/env python import numpy as np import cv2 as cv import os from tests_common import NewOpenCVTests class test_gapi_infer(NewOpenCVTests): def test_getAvailableTargets(self): targets = cv.dnn.getAvailableTargets(cv.dnn.DNN_BACKEND_OPENCV) self.assertTrue(cv.dnn.DNN_TARGET_CPU in targets) def test_age_gender_infer(self): # NB: Check IE if not cv.dnn.DNN_TARGET_CPU in cv.dnn.getAvailableTargets(cv.dnn.DNN_BACKEND_INFERENCE_ENGINE): return root_path = '/omz_intel_models/intel/age-gender-recognition-retail-0013/FP32/age-gender-recognition-retail-0013' model_path = self.find_file(root_path + '.xml', [os.environ.get('OPENCV_DNN_TEST_DATA_PATH')]) weights_path = self.find_file(root_path + '.bin', [os.environ.get('OPENCV_DNN_TEST_DATA_PATH')]) img_path = self.find_file('cv/face/david2.jpg', [os.environ.get('OPENCV_TEST_DATA_PATH')]) device_id = 'CPU' img = cv.resize(cv.imread(img_path), (62,62)) # OpenCV DNN net = cv.dnn.readNetFromModelOptimizer(model_path, weights_path) net.setPreferableBackend(cv.dnn.DNN_BACKEND_INFERENCE_ENGINE) net.setPreferableTarget(cv.dnn.DNN_TARGET_CPU) blob = cv.dnn.blobFromImage(img) net.setInput(blob) dnn_age, dnn_gender = net.forward(net.getUnconnectedOutLayersNames()) # OpenCV G-API g_in = cv.GMat() inputs = cv.GInferInputs() inputs.setInput('data', g_in) outputs = cv.gapi.infer("net", inputs) age_g = outputs.at("age_conv3") gender_g = outputs.at("prob") comp = cv.GComputation(cv.GIn(g_in), cv.GOut(age_g, gender_g)) pp = cv.gapi.ie.params("net", model_path, weights_path, device_id) nets = cv.gapi.networks(pp) args = cv.compile_args(nets) gapi_age, gapi_gender = comp.apply(cv.gin(img), args=cv.compile_args(cv.gapi.networks(pp))) # Check self.assertEqual(0.0, cv.norm(dnn_gender, gapi_gender, cv.NORM_INF)) self.assertEqual(0.0, cv.norm(dnn_age, gapi_age, cv.NORM_INF)) if __name__ == '__main__': NewOpenCVTests.bootstrap()