TEST(hole_filling_test, elliptical_hole_on_repeated_texture_should_give_good_result) { Mat img = imread("test_images/brick_pavement.jpg"); convert_for_computation(img, 0.5f); // Add some hole Mat hole_mask = Mat::zeros(img.size(), CV_8U); Point center(100, 110); Size axis(20, 5); float angle = 20; ellipse(hole_mask, center, axis, angle, 0, 360, Scalar(255), -1); int patch_size = 7; HoleFilling hf(img, hole_mask, patch_size); // Dump image with hole as black region. Mat img_with_hole_bgr; cvtColor(img, img_with_hole_bgr, CV_Lab2BGR); img_with_hole_bgr.setTo(Scalar(0,0,0), hole_mask); imwrite("brick_pavement_hole.exr", img_with_hole_bgr); // Dump reconstructed image Mat filled = hf.run(); cvtColor(filled, filled, CV_Lab2BGR); imwrite("brick_pavement_hole_filled.exr", filled); // The reconstructed image should be close to the original one, in this very simple case. Mat img_bgr; cvtColor(img, img_bgr, CV_Lab2BGR); double ssd = norm(img_bgr, filled, cv::NORM_L2SQR); EXPECT_LT(ssd, 0.2); }
/* * Class: io_github_melvincabatuan_fullbodydetection_MainActivity * Method: predict * Signature: (Landroid/graphics/Bitmap;[B)V */ JNIEXPORT void JNICALL Java_io_github_melvincabatuan_fullbodydetection_MainActivity_predict (JNIEnv * pEnv, jobject clazz, jobject pTarget, jbyteArray pSource){ AndroidBitmapInfo bitmapInfo; uint32_t* bitmapContent; // Links to Bitmap content if(AndroidBitmap_getInfo(pEnv, pTarget, &bitmapInfo) < 0) abort(); if(bitmapInfo.format != ANDROID_BITMAP_FORMAT_RGBA_8888) abort(); if(AndroidBitmap_lockPixels(pEnv, pTarget, (void**)&bitmapContent) < 0) abort(); /// Access source array data... OK jbyte* source = (jbyte*)pEnv->GetPrimitiveArrayCritical(pSource, 0); if (source == NULL) abort(); /// cv::Mat for YUV420sp source and output BGRA Mat srcGray(bitmapInfo.height, bitmapInfo.width, CV_8UC1, (unsigned char *)source); Mat mbgra(bitmapInfo.height, bitmapInfo.width, CV_8UC4, (unsigned char *)bitmapContent); /***********************************************************************************************/ /// Native Image Processing HERE... if(DEBUG){ LOGI("Starting native image processing..."); } if (full_body_cascade.empty()){ t = (double)getTickCount(); sprintf( full_body_cascade_path, "%s/%s", getenv("ASSETDIR"), "haarcascade_fullbody.xml"); /* Load the face cascades */ if( !full_body_cascade.load(full_body_cascade_path) ){ LOGE("Error loading cat face cascade"); abort(); }; t = 1000*((double)getTickCount() - t)/getTickFrequency(); if(DEBUG){ LOGI("Loading full body cascade took %lf milliseconds.", t); } } std::vector<Rect> fbody; //-- Detect full body t = (double)getTickCount(); /// Detection took cat_face_cascade.detectMultiScale() time = 655.334471 ms // cat_face_cascade.detectMultiScale( srcGray, faces, 1.1, 2 , 0 , Size(30, 30) ); // Scaling factor = 1.1; minNeighbors = 2 ; flags = 0; minimumSize = 30,30 // cat_face_cascade.detectMultiScale() time = 120.117185 ms // cat_face_cascade.detectMultiScale( srcGray, faces, 1.2, 3 , 0 , Size(64, 64)); full_body_cascade.detectMultiScale( srcGray, fbody, 1.2, 2 , 0 , Size(14, 28)); // Size(double width, double height) // scalingFactor parameters determine how much the classifier will be scaled up after each run. // minNeighbors parameter specifies how many positive neighbors a positive face rectangle should have to be considered a possible match; // when a potential face rectangle is moved a pixel and does not trigger the classifier any more, it is most likely that it’s a false positive. // Face rectangles with fewer positive neighbors than minNeighbors are rejected. // If minNeighbors is set to zero, all potential face rectangles are returned. // The flags parameter is from the OpenCV 1.x API and should always be 0. // minimumSize specifies the smallest face rectangle we’re looking for. t = 1000*((double)getTickCount() - t)/getTickFrequency(); if(DEBUG){ LOGI("full_body_cascade.detectMultiScale() time = %lf milliseconds.", t); } // Iterate through all faces and detect eyes t = (double)getTickCount(); for( size_t i = 0; i < fbody.size(); i++ ) { Point center(fbody[i].x + fbody[i].width / 2, fbody[i].y + fbody[i].height / 2); ellipse(srcGray, center, Size(fbody[i].width / 2, fbody[i].height / 2), 0, 0, 360, Scalar(255, 0, 255), 4, 8, 0); }//endfor t = 1000*((double)getTickCount() - t)/getTickFrequency(); if(DEBUG){ LOGI("Iterate through all faces and detecting eyes took %lf milliseconds.", t); } /// Display to Android cvtColor(srcGray, mbgra, CV_GRAY2BGRA); if(DEBUG){ LOGI("Successfully finished native image processing..."); } /************************************************************************************************/ /// Release Java byte buffer and unlock backing bitmap pEnv-> ReleasePrimitiveArrayCritical(pSource,source,0); if (AndroidBitmap_unlockPixels(pEnv, pTarget) < 0) abort(); }