// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // 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 #include "lite/core/context.h" #include "lite/core/profile/timer.h" #include "lite/tests/cv/cv_basic.h" #include "lite/utils/cv/paddle_image_preprocess.h" #include "time.h" // NOLINT DEFINE_int32(cluster, 3, "cluster id"); DEFINE_int32(threads, 1, "threads num"); DEFINE_int32(warmup, 0, "warmup times"); DEFINE_int32(repeats, 1, "repeats times"); DEFINE_bool(basic_test, false, "do all tests"); DEFINE_bool(check_result, true, "check the result"); DEFINE_int32(srcFormat, 0, "input image format RGBA"); DEFINE_int32(dstFormat, 2, "output image format RGB"); DEFINE_int32(srch, 1920, "input height"); DEFINE_int32(srcw, 1080, "input width"); DEFINE_int32(dsth, 960, "output height"); DEFINE_int32(dstw, 540, "output width"); DEFINE_int32(angle, 90, "rotate angel"); DEFINE_int32(flip_num, 0, "flip x"); DEFINE_int32(layout, 1, "layout nchw"); typedef paddle::lite::utils::cv::ImageFormat ImageFormat; typedef paddle::lite::utils::cv::FlipParam FlipParam; typedef paddle::lite_api::DataLayoutType LayoutType; typedef paddle::lite::utils::cv::TransParam TransParam; typedef paddle::lite::utils::cv::ImagePreprocess ImagePreprocess; typedef paddle::lite_api::Tensor Tensor_api; typedef paddle::lite::Tensor Tensor; using paddle::lite::profile::Timer; void fill_tensor_host_rand(uint8_t* dio, int64_t size) { uint seed = 256; for (int64_t i = 0; i < size; ++i) { dio[i] = rand_r(&seed) % 256; // -128; } } void print_int8(uint8_t* ptr, int size, int width) { for (int i = 0; i < size; i++) { printf("%d ", *ptr++); if ((i + 1) % width == 0) { printf("\n"); } } printf("\n"); } void print_int(int* ptr, int size, int width) { int j = 0; for (int i = 0; i < size; i++) { printf("%d ", *ptr++); if ((i + 1) % width == 0) { printf("\n"); } } printf("\n"); } void print_ff(const float* ptr, int size, int width) { int j = 0; for (int i = 0; i < size; i++) { printf("%f ", *ptr++); if ((i + 1) % width == 0) { printf("\n"); } } printf("\n"); } #ifdef LITE_WITH_ARM void test_img(const std::vector& cluster_id, const std::vector& thread_num, int srcw, int srch, int dstw, int dsth, ImageFormat srcFormat, ImageFormat dstFormat, float rotate, FlipParam flip, LayoutType layout, int test_iter = 10) { #ifdef LITE_WITH_ARM paddle::lite::DeviceInfo::Init(); #endif for (auto& cls : cluster_id) { for (auto& th : thread_num) { std::unique_ptr ctx1( new paddle::lite::KernelContext); auto& ctx = ctx1->As(); ctx.SetRunMode(static_cast(cls), th); LOG(INFO) << "cluster: " << cls << ", threads: " << th; LOG(INFO) << " input tensor size, num= " << 1 << ", channel= " << 1 << ", height= " << srch << ", width= " << srcw << ", srcFormat= " << (ImageFormat)srcFormat; // RGBA = 0, BGRA, RGB, BGR, GRAY, NV21 = 11, NV12, if (srcFormat == ImageFormat::NV21) { LOG(INFO) << "srcFormat: NV21"; } if (srcFormat == ImageFormat::NV12) { LOG(INFO) << "srcFormat: NV12"; } if (srcFormat == ImageFormat::GRAY) { LOG(INFO) << "srcFormat: GRAY"; } if (srcFormat == ImageFormat::BGRA) { LOG(INFO) << "srcFormat: BGRA"; } if (srcFormat == ImageFormat::BGR) { LOG(INFO) << "srcFormat: BGR"; } if (srcFormat == ImageFormat::RGBA) { LOG(INFO) << "srcFormat: RGBA"; } if (srcFormat == ImageFormat::RGB) { LOG(INFO) << "srcFormat: RGB"; } LOG(INFO) << " output tensor size, num=" << 1 << ", channel=" << 1 << ", height=" << dsth << ", width=" << dstw << ", dstFormat= " << (ImageFormat)dstFormat; if (dstFormat == ImageFormat::NV21) { LOG(INFO) << "dstFormat: NV21"; } if (dstFormat == ImageFormat::NV12) { LOG(INFO) << "dstFormat: NV12"; } if (dstFormat == ImageFormat::GRAY) { LOG(INFO) << "dstFormat: GRAY"; } if (dstFormat == ImageFormat::BGRA) { LOG(INFO) << "dstFormat: BGRA"; } if (dstFormat == ImageFormat::BGR) { LOG(INFO) << "dstFormat: BGR"; } if (dstFormat == ImageFormat::RGBA) { LOG(INFO) << "dstFormat: RGBA"; } if (dstFormat == ImageFormat::RGB) { LOG(INFO) << "dstFormat: RGB"; } LOG(INFO) << "Rotate = " << rotate << ", Flip = " << flip << ", Layout = " << static_cast(layout); int size = 3 * srch * srcw; if (srcFormat == ImageFormat::NV12 || srcFormat == ImageFormat::NV21) { size = ceil(1.5 * srch) * srcw; } else if (srcFormat == ImageFormat::BGRA || srcFormat == ImageFormat::RGBA) { size = 4 * srch * srcw; } else if (srcFormat == ImageFormat::GRAY) { size = srch * srcw; } uint8_t* src = new uint8_t[size]; fill_tensor_host_rand(src, size); int out_size = srch * srcw; int resize = dstw * dsth; if (dstFormat == ImageFormat::NV12 || dstFormat == ImageFormat::NV21) { out_size = ceil(1.5 * srch) * srcw; resize = ceil(1.5 * dsth) * dstw; } else if (dstFormat == ImageFormat::BGR || dstFormat == ImageFormat::RGB) { out_size = 3 * srch * srcw; resize = 3 * dsth * dstw; } else if (dstFormat == ImageFormat::BGRA || dstFormat == ImageFormat::RGBA) { out_size = 4 * srch * srcw; resize = 4 * dsth * dstw; } else if (dstFormat == ImageFormat::GRAY) { out_size = srch * srcw; resize = dsth * dstw; } // out uint8_t* basic_dst = new uint8_t[out_size]; uint8_t* lite_dst = new uint8_t[out_size]; // resize uint8_t* resize_basic = new uint8_t[resize]; uint8_t* resize_tmp = new uint8_t[resize]; uint8_t* tv_out_ratote_basic = new uint8_t[resize]; uint8_t* tv_out_ratote = new uint8_t[resize]; uint8_t* tv_out_flip_basic = new uint8_t[resize]; uint8_t* tv_out_flip = new uint8_t[resize]; std::vector shape_out = {1, 3, dsth, dstw}; Tensor tensor; Tensor tensor_basic; tensor.Resize(shape_out); tensor_basic.Resize(shape_out); tensor.set_precision(PRECISION(kFloat)); tensor_basic.set_precision(PRECISION(kFloat)); float means[3] = {127.5f, 127.5f, 127.5f}; float scales[3] = {1 / 127.5f, 1 / 127.5f, 1 / 127.5f}; if (FLAGS_check_result) { // LOG(INFO) << "image convert basic compute"; image_convert_basic(src, basic_dst, (ImageFormat)srcFormat, (ImageFormat)dstFormat, srcw, srch, out_size); // LOG(INFO) << "image resize basic compute"; image_resize_basic(basic_dst, resize_basic, (ImageFormat)dstFormat, srcw, srch, dstw, dsth); // LOG(INFO) << "image rotate basic compute"; image_rotate_basic(resize_basic, tv_out_ratote_basic, (ImageFormat)dstFormat, dstw, dsth, rotate); // LOG(INFO) << "image flip basic compute"; image_flip_basic(resize_basic, tv_out_flip_basic, (ImageFormat)dstFormat, dstw, dsth, flip); // LOG(INFO) << "image to tensor basic compute"; image_to_tensor_basic(resize_basic, &tensor_basic, (ImageFormat)dstFormat, layout, dstw, dsth, means, scales); } Timer t1; Timer t_convert; Timer t_resize; Timer t_flip; Timer t_rotate; Timer t_tensor; LOG(INFO) << "saber cv compute"; TransParam tparam; tparam.ih = srch; tparam.iw = srcw; tparam.oh = dsth; tparam.ow = dstw; tparam.flip_param = flip; tparam.rotate_param = rotate; Tensor_api dst_tensor(&tensor); dst_tensor.Resize(shape_out); ImagePreprocess image_preprocess(srcFormat, dstFormat, tparam); for (int i = 0; i < test_iter; ++i) { t1.Start(); // LOG(INFO) << "image convert saber compute"; t_convert.Start(); // 方法一: image_preprocess.imageCovert(src, lite_dst); image_preprocess.imageConvert( src, lite_dst, (ImageFormat)srcFormat, (ImageFormat)dstFormat); t_convert.Stop(); // LOG(INFO) << "image resize saber compute"; t_resize.Start(); // 方法一:image_preprocess.imageResize(lite_dst, resize_tmp); image_preprocess.imageResize(lite_dst, resize_tmp, (ImageFormat)dstFormat, srcw, srch, dstw, dsth); t_resize.Stop(); // LOG(INFO) << "image rotate saber compute"; t_rotate.Start(); // 方法一: image_preprocess.imageRotate(resize_tmp, tv_out_ratote); image_preprocess.imageRotate(resize_tmp, tv_out_ratote, (ImageFormat)dstFormat, dstw, dsth, rotate); t_rotate.Stop(); // LOG(INFO) << "image flip saber compute"; t_flip.Start(); // 方法一: image_preprocess.imageFlip(resize_tmp, tv_out_flip); image_preprocess.imageFlip( resize_tmp, tv_out_flip, (ImageFormat)dstFormat, dstw, dsth, flip); t_flip.Stop(); // LOG(INFO) << "image to tensor compute"; t_tensor.Start(); // 方法一: image_preprocess.image2Tensor( // resize_tmp, &dst_tensor, layout, means, scales); image_preprocess.image2Tensor(resize_tmp, &dst_tensor, (ImageFormat)dstFormat, dstw, dsth, layout, means, scales); t_tensor.Stop(); t1.Stop(); } LOG(INFO) << "image convert avg time : " << t_convert.LapTimes().Avg() << ", min time: " << t_convert.LapTimes().Min() << ", max time: " << t_convert.LapTimes().Max(); LOG(INFO) << "image resize avg time : " << t_resize.LapTimes().Avg() << ", min time: " << t_resize.LapTimes().Min() << ", max time: " << t_resize.LapTimes().Max(); LOG(INFO) << "image rotate avg time : " << t_rotate.LapTimes().Avg() << ", min time: " << t_rotate.LapTimes().Min() << ", max time: " << t_rotate.LapTimes().Max(); LOG(INFO) << "image flip avg time : " << t_flip.LapTimes().Avg() << ", min time: " << t_flip.LapTimes().Min() << ", max time: " << t_flip.LapTimes().Max(); LOG(INFO) << "image tensor avg time : " << t_tensor.LapTimes().Avg() << ", min time: " << t_tensor.LapTimes().Min() << ", max time: " << t_tensor.LapTimes().Max(); LOG(INFO) << "image trans total avg time : " << t1.LapTimes().Avg() << ", min time: " << t1.LapTimes().Min() << ", max time: " << t1.LapTimes().Max(); double max_ratio = 0; double max_diff = 0; const double eps = 1e-6f; if (FLAGS_check_result) { LOG(INFO) << "diff, image convert size: " << out_size; uint8_t* diff_v = new uint8_t[out_size]; for (int i = 0; i < out_size; i++) { uint8_t a = lite_dst[i]; uint8_t b = basic_dst[i]; uint8_t diff1 = a - b; uint8_t diff = diff1 > 0 ? diff1 : -diff1; diff_v[i] = diff; if (max_diff < diff) { max_diff = diff; max_ratio = 2.0 * max_diff / (a + b + eps); } } if (std::abs(max_ratio) >= 1e-5f) { int width = size / srch; printf("din: \n"); print_int8(src, size, width); width = out_size / srch; printf("saber result: \n"); print_int8(lite_dst, out_size, width); printf("basic result: \n"); print_int8(basic_dst, out_size, width); printf("diff result: \n"); print_int8(diff_v, out_size, width); } delete[] diff_v; LOG(INFO) << "compare result, max diff: " << max_diff << ", max ratio: " << max_ratio; bool rst = std::abs(max_ratio) < 1e-5f; CHECK_EQ(rst, true) << "compute result error"; } LOG(INFO) << "image convert end"; if (FLAGS_check_result) { max_ratio = 0; max_diff = 0; // const double eps = 1e-6f; int* diff_v = new int[resize]; LOG(INFO) << "diff, image resize size: " << resize; for (int i = 0; i < resize; i++) { uint8_t a = resize_tmp[i]; uint8_t b = resize_basic[i]; int diff1 = a - b; int diff = 0; // basic resize and saber resize 在float -> // int转换时存在误差,误差范围是{-1, 1} if (diff1 < -1 || diff1 > 1) diff = diff1 < 0 ? -diff1 : diff1; diff_v[i] = diff; if (max_diff < diff) { max_diff = diff; max_ratio = 2.0 * max_diff / (a + b + eps); } } if (std::abs(max_ratio) >= 1e-5f) { int width = out_size / srch; printf("din: \n"); print_int8(lite_dst, out_size, width); width = resize / dsth; printf("saber result: \n"); print_int8(resize_tmp, resize, width); printf("basic result: \n"); print_int8(resize_basic, resize, width); printf("diff result: \n"); print_int(diff_v, resize, width); } delete[] diff_v; // printf("\n"); LOG(INFO) << "compare result, max diff: " << max_diff << ", max ratio: " << max_ratio; bool rst = std::abs(max_ratio) < 1e-5f; CHECK_EQ(rst, true) << "compute result error"; } delete[] lite_dst; delete[] basic_dst; LOG(INFO) << "image resize end"; if (FLAGS_check_result) { max_ratio = 0; max_diff = 0; int* diff_v = new int[resize]; LOG(INFO) << "diff, image rotate size: " << resize; for (int i = 0; i < resize; i++) { int a = tv_out_ratote[i]; int b = tv_out_ratote_basic[i]; int diff1 = a - b; int diff = 0; if (diff1 < -1 || diff1 > 1) diff = diff1 < 0 ? -diff1 : diff1; diff_v[i] = diff; if (max_diff < diff) { max_diff = diff; max_ratio = 2.0 * max_diff / (a + b + eps); } } if (std::abs(max_ratio) >= 1e-5f) { int width = resize / dsth; printf("din: \n"); print_int8(resize_tmp, resize, width); printf("saber result: \n"); print_int8(tv_out_ratote, resize, width); printf("basic result: \n"); print_int8(tv_out_ratote_basic, resize, width); printf("diff result: \n"); print_int(diff_v, resize, width); } delete[] diff_v; LOG(INFO) << "compare result, max diff: " << max_diff << ", max ratio: " << max_ratio; bool rst = std::abs(max_ratio) < 1e-5f; CHECK_EQ(rst, true) << "compute result error"; } delete[] tv_out_ratote; delete[] tv_out_ratote_basic; LOG(INFO) << "image rotate end"; if (FLAGS_check_result) { max_ratio = 0; max_diff = 0; int* diff_v = new int[resize]; LOG(INFO) << "diff, image flip size: " << resize; for (int i = 0; i < resize; i++) { int a = tv_out_flip[i]; int b = tv_out_flip_basic[i]; int diff1 = a - b; int diff = 0; if (diff1 < -1 || diff1 > 1) diff = diff1 < 0 ? -diff1 : diff1; diff_v[i] = diff; if (max_diff < diff) { max_diff = diff; max_ratio = 2.0 * max_diff / (a + b + eps); } } if (std::abs(max_ratio) >= 1e-5f) { int width = resize / dsth; printf("din: \n"); print_int8(resize_tmp, resize, width); printf("saber result: \n"); print_int8(tv_out_flip, resize, width); printf("basic result: \n"); print_int8(tv_out_flip_basic, resize, width); printf("diff result: \n"); print_int(diff_v, resize, width); } delete[] diff_v; LOG(INFO) << "compare result, max diff: " << max_diff << ", max ratio: " << max_ratio; bool rst = std::abs(max_ratio) < 1e-5f; CHECK_EQ(rst, true) << "compute result error"; } delete[] tv_out_flip; delete[] tv_out_flip_basic; delete[] resize_tmp; delete[] resize_basic; LOG(INFO) << "image flip end"; if (FLAGS_check_result) { max_ratio = 0; max_diff = 0; LOG(INFO) << "diff, iamge to tensor size: " << tensor.numel(); const float* ptr_a = tensor.data(); const float* ptr_b = tensor_basic.data(); int ss = tensor.numel(); float* diff_v = new float[ss]; for (int i = 0; i < ss; i++) { int a = ptr_a[i]; int b = ptr_b[i]; int diff1 = a - b; int diff = 0; if (diff1 < -1 || diff1 > 1) diff = diff1 < 0 ? -diff1 : diff1; diff_v[i] = diff; if (max_diff < diff) { max_diff = diff; max_ratio = 2.0 * max_diff / (a + b + eps); } } if (std::abs(max_ratio) >= 1e-5f) { int width = resize / srch; printf("din: \n"); print_int8(resize_tmp, resize, width); printf("saber result: \n"); print_ff(ptr_a, resize, width); printf("basic result: \n"); print_ff(ptr_b, resize, width); printf("diff result: \n"); print_ff(diff_v, resize, width); } LOG(INFO) << "compare result, max diff: " << max_diff << ", max ratio: " << max_ratio; bool rst = std::abs(max_ratio) < 1e-5f; CHECK_EQ(rst, true) << "compute result error"; LOG(INFO) << "iamge to tensor end"; } } } } #if 1 TEST(TestImageConvertRand, test_func_image_convert_preprocess) { if (FLAGS_basic_test) { for (auto w : {1, 4, 8, 16, 112, 224, 1092}) { for (auto h : {1, 4, 16, 112, 224}) { for (auto ww : {66}) { for (auto hh : {12}) { for (auto rotate : {180}) { for (auto flip : {0}) { for (auto srcFormat : {0, 1, 2, 3, 4, 11, 12}) { for (auto dstFormat : {0, 1, 2, 3, 4}) { for (auto layout : {1}) { if ((srcFormat == ImageFormat::NV12 || srcFormat == ImageFormat::NV21) && (dstFormat == ImageFormat::GRAY)) { continue; } if ((dstFormat == ImageFormat::NV12 || dstFormat == ImageFormat::NV21) && (srcFormat == ImageFormat::GRAY)) { continue; } if (srcFormat == ImageFormat::NV12 || srcFormat == ImageFormat::NV21) { if (w % 2) { // is not ou shu, two line y == one line // uv continue; } } test_img({FLAGS_cluster}, {1}, w, h, ww, hh, (ImageFormat)srcFormat, (ImageFormat)dstFormat, rotate, (FlipParam)flip, (LayoutType)layout); } } } } } } } } } } } #endif #if 1 TEST(TestImageConvertRand, test_func_image_resize_preprocess) { if (FLAGS_basic_test) { for (auto w : {1, 4, 8, 16, 112, 224, 1092}) { for (auto h : {1, 4, 16, 112, 224}) { for (auto ww : {1, 2, 8, 32, 112}) { for (auto hh : {1, 2, 8, 112}) { for (auto rotate : {180}) { for (auto flip : {0}) { for (auto srcFormat : {0, 1, 2, 3, 4, 11, 12}) { for (auto dstFormat : {0, 1, 2, 3, 4, 11}) { for (auto layout : {1}) { if (dstFormat == ImageFormat::NV12 || dstFormat == ImageFormat::NV21 || (srcFormat == ImageFormat::NV12 || srcFormat == ImageFormat::NV21) && dstFormat == ImageFormat::GRAY) { continue; } if (srcFormat == ImageFormat::NV12 || srcFormat == ImageFormat::NV21) { if (w % 2) { // is not ou shu, two line y == one line // uv continue; } } test_img({FLAGS_cluster}, {1, 2, 4}, w, h, ww, hh, (ImageFormat)srcFormat, (ImageFormat)dstFormat, rotate, (FlipParam)flip, (LayoutType)layout); } } } } } } } } } } } #endif #if 1 TEST(TestImageConvertRand, test_func_image_trans_preprocess) { if (FLAGS_basic_test) { for (auto w : {1, 8, 16, 112, 224, 1092}) { for (auto h : {1, 16, 112, 224}) { for (auto ww : {32, 112}) { for (auto hh : {112}) { for (auto rotate : {90, 180, 270}) { for (auto flip : {-1, 0, 1}) { for (auto srcFormat : {0}) { for (auto dstFormat : {0, 1, 2, 3, 4}) { for (auto layout : {1, 3}) { if (srcFormat == ImageFormat::NV12 || srcFormat == ImageFormat::NV21) { if (w % 2) { // is not ou shu, two line y == one line // uv continue; } } test_img({FLAGS_cluster}, {1, 2, 4}, w, h, ww, hh, (ImageFormat)srcFormat, (ImageFormat)dstFormat, rotate, (FlipParam)flip, (LayoutType)layout); } } } } } } } } } } } #endif #if 1 TEST(TestImageConvertCustom, test_func_image_preprocess_custom) { test_img({FLAGS_cluster}, {1, 2, 4}, FLAGS_srcw, FLAGS_srch, FLAGS_dstw, FLAGS_dsth, (ImageFormat)FLAGS_srcFormat, (ImageFormat)FLAGS_dstFormat, FLAGS_angle, (FlipParam)FLAGS_flip_num, (LayoutType)FLAGS_layout, 20); } #endif #endif