From 17c42bdfea8507533b4b1bc10addbde6edf12943 Mon Sep 17 00:00:00 2001 From: zhangyang0701 Date: Mon, 4 Mar 2019 11:12:36 +0800 Subject: [PATCH] change format --- test/fpga/test_rfcn_api.cpp | 124 ++++++++++++++++++------------------ 1 file changed, 62 insertions(+), 62 deletions(-) diff --git a/test/fpga/test_rfcn_api.cpp b/test/fpga/test_rfcn_api.cpp index 5cd910080d..2f6f23d34d 100644 --- a/test/fpga/test_rfcn_api.cpp +++ b/test/fpga/test_rfcn_api.cpp @@ -12,8 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ -#include #include +#include #include "../../src/io/paddle_inference_api.h" using namespace paddle_mobile; @@ -39,68 +39,68 @@ void readStream(std::string filename, char *buf) { } PaddleMobileConfig GetConfig() { - PaddleMobileConfig config; - config.precision = PaddleMobileConfig::FP32; - config.device = PaddleMobileConfig::kFPGA; - config.prog_file = g_model; - config.param_file = g_param; - config.thread_num = 1; - config.batch_size = 1; - config.optimize = true; - config.lod_mode = true; - config.quantification = false; - return config; + PaddleMobileConfig config; + config.precision = PaddleMobileConfig::FP32; + config.device = PaddleMobileConfig::kFPGA; + config.prog_file = g_model; + config.param_file = g_param; + config.thread_num = 1; + config.batch_size = 1; + config.optimize = true; + config.lod_mode = true; + config.quantification = false; + return config; } int main() { - open_device(); - PaddleMobileConfig config = GetConfig(); - auto predictor = - CreatePaddlePredictor(config); - - std::cout << "after loading model" << std::endl; - - float img_info[3] = {768, 1536, 768.0f / 960.0f}; - int img_length = 768 * 1536 * 3; - auto img = reinterpret_cast(fpga_malloc(img_length * sizeof(float))); - readStream(g_image, reinterpret_cast(img)); - - std::cout << "after initializing data" << std::endl; -/* - predictor->FeedData({img_info, img}); - predictor->Predict_From_To(0, -1); - std::cout << " Finishing predicting " << std::endl; - std::vector v(3, nullptr); - predictor->GetResults(&v); - int post_nms = 300; - for (int num = 0; num < post_nms; num ++){ - for (int i = 0; i < 8; i ++){ - std:: cout << ((float*)(v[0]))[num * 8 + i] << std::endl; + open_device(); + PaddleMobileConfig config = GetConfig(); + auto predictor = + CreatePaddlePredictor(config); + + std::cout << "after loading model" << std::endl; + + float img_info[3] = {768, 1536, 768.0f / 960.0f}; + int img_length = 768 * 1536 * 3; + auto img = reinterpret_cast(fpga_malloc(img_length * sizeof(float))); + readStream(g_image, reinterpret_cast(img)); + + std::cout << "after initializing data" << std::endl; + /* + predictor->FeedData({img_info, img}); + predictor->Predict_From_To(0, -1); + std::cout << " Finishing predicting " << std::endl; + std::vector v(3, nullptr); + predictor->GetResults(&v); + int post_nms = 300; + for (int num = 0; num < post_nms; num ++){ + for (int i = 0; i < 8; i ++){ + std:: cout << ((float*)(v[0]))[num * 8 + i] << std::endl; + } } - } - for (int num = 0; num < post_nms; num ++){ - for (int i = 0; i < 8; i ++){ - std:: cout << ((float*)(v[1]))[num * 8 + i] << std::endl; + for (int num = 0; num < post_nms; num ++){ + for (int i = 0; i < 8; i ++){ + std:: cout << ((float*)(v[1]))[num * 8 + i] << std::endl; + } } - } - for (int num = 0; num < post_nms; num ++){ - for (int i = 0; i < 4; i ++){ - std:: cout << ((float*)(v[2]))[num * 4 + i] << std::endl; + for (int num = 0; num < post_nms; num ++){ + for (int i = 0; i < 4; i ++){ + std:: cout << ((float*)(v[2]))[num * 4 + i] << std::endl; + } } - } -*/ + */ struct PaddleTensor t_img_info, t_img; t_img_info.dtype = FLOAT32; t_img_info.layout = LAYOUT_HWC; - t_img_info.shape = std::vector({1,3}); + t_img_info.shape = std::vector({1, 3}); t_img_info.name = "Image information"; t_img_info.data.Reset(img_info, 3 * sizeof(float)); t_img.dtype = FLOAT32; t_img.layout = LAYOUT_HWC; - t_img.shape = std::vector({1,768, 1536, 3}); + t_img.shape = std::vector({1, 768, 1536, 3}); t_img.name = "Image information"; t_img.data.Reset(img, img_length * sizeof(float)); predictor->FeedPaddleTensors({t_img_info, t_img}); @@ -112,24 +112,24 @@ int main() { std::vector v(3, PaddleTensor()); predictor->FetchPaddleTensors(&v); - auto post_nms = v[0].data.length()/sizeof(float)/8; - for (int num = 0; num < post_nms; num ++){ - for (int i = 0; i < 8; i ++){ - auto p = reinterpret_cast(v[0].data.data()); - std:: cout << p[num * 8 + i] << std::endl; + auto post_nms = v[0].data.length() / sizeof(float) / 8; + for (int num = 0; num < post_nms; num++) { + for (int i = 0; i < 8; i++) { + auto p = reinterpret_cast(v[0].data.data()); + std::cout << p[num * 8 + i] << std::endl; } } - for (int num = 0; num < post_nms; num ++){ - for (int i = 0; i < 8; i ++){ - auto p = reinterpret_cast(v[1].data.data()); - std:: cout << p[num * 8 + i] << std::endl; + for (int num = 0; num < post_nms; num++) { + for (int i = 0; i < 8; i++) { + auto p = reinterpret_cast(v[1].data.data()); + std::cout << p[num * 8 + i] << std::endl; } } - for (int num = 0; num < post_nms; num ++){ - for (int i = 0; i < 4; i ++){ - auto p = reinterpret_cast(v[2].data.data()); - std:: cout << p[num * 4 + i] << std::endl; + for (int num = 0; num < post_nms; num++) { + for (int i = 0; i < 4; i++) { + auto p = reinterpret_cast(v[2].data.data()); + std::cout << p[num * 4 + i] << std::endl; } } - return 0; + return 0; } -- GitLab