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Diffstat (limited to 'source/use_case/object_detection/src/UseCaseHandler.cc')
| -rw-r--r-- | source/use_case/object_detection/src/UseCaseHandler.cc | 162 |
1 files changed, 162 insertions, 0 deletions
diff --git a/source/use_case/object_detection/src/UseCaseHandler.cc b/source/use_case/object_detection/src/UseCaseHandler.cc new file mode 100644 index 0000000..45df4f8 --- /dev/null +++ b/source/use_case/object_detection/src/UseCaseHandler.cc @@ -0,0 +1,162 @@ +/* + * Copyright (c) 2022 Arm Limited. All rights reserved. + * SPDX-License-Identifier: Apache-2.0 + * + * 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 "UseCaseHandler.hpp" +#include "InputFiles.hpp" +#include "YoloFastestModel.hpp" +#include "UseCaseCommonUtils.hpp" +#include "DetectionUseCaseUtils.hpp" +#include "DetectorPostProcessing.hpp" +#include "hal.h" + +#include <inttypes.h> + + +/* used for presentation, original images are read-only"*/ +static uint8_t g_image_buffer[INPUT_IMAGE_WIDTH*INPUT_IMAGE_HEIGHT*FORMAT_MULTIPLY_FACTOR] IFM_BUF_ATTRIBUTE = {}; + +namespace arm { +namespace app { + + + /* Object detection classification handler. */ + bool ObjectDetectionHandler(ApplicationContext& ctx, uint32_t imgIndex, bool runAll) + { + auto& platform = ctx.Get<hal_platform&>("platform"); + auto& profiler = ctx.Get<Profiler&>("profiler"); + + constexpr uint32_t dataPsnImgDownscaleFactor = 1; + constexpr uint32_t dataPsnImgStartX = 10; + constexpr uint32_t dataPsnImgStartY = 35; + + constexpr uint32_t dataPsnTxtInfStartX = 150; + constexpr uint32_t dataPsnTxtInfStartY = 40; + + platform.data_psn->clear(COLOR_BLACK); + + auto& model = ctx.Get<Model&>("model"); + + /* If the request has a valid size, set the image index. */ + if (imgIndex < NUMBER_OF_FILES) { + if (!SetAppCtxIfmIdx(ctx, imgIndex, "imgIndex")) { + return false; + } + } + if (!model.IsInited()) { + printf_err("Model is not initialised! Terminating processing.\n"); + return false; + } + + auto curImIdx = ctx.Get<uint32_t>("imgIndex"); + + TfLiteTensor* inputTensor = model.GetInputTensor(0); + + if (!inputTensor->dims) { + printf_err("Invalid input tensor dims\n"); + return false; + } else if (inputTensor->dims->size < 3) { + printf_err("Input tensor dimension should be >= 3\n"); + return false; + } + + TfLiteIntArray* inputShape = model.GetInputShape(0); + + const uint32_t nCols = inputShape->data[arm::app::YoloFastestModel::ms_inputColsIdx]; + const uint32_t nRows = inputShape->data[arm::app::YoloFastestModel::ms_inputRowsIdx]; + const uint32_t nPresentationChannels = FORMAT_MULTIPLY_FACTOR; + + std::vector<DetectionResult> results; + + do { + /* Strings for presentation/logging. */ + std::string str_inf{"Running inference... "}; + + const uint8_t* curr_image = get_img_array(ctx.Get<uint32_t>("imgIndex")); + + /* Copy over the data and convert to gryscale */ +#if DISPLAY_RGB_IMAGE + memcpy(g_image_buffer,curr_image, INPUT_IMAGE_WIDTH*INPUT_IMAGE_HEIGHT*FORMAT_MULTIPLY_FACTOR); +#else + RgbToGrayscale(curr_image,g_image_buffer,INPUT_IMAGE_WIDTH,INPUT_IMAGE_HEIGHT); +#endif /*DISPLAY_RGB_IMAGE*/ + + RgbToGrayscale(curr_image,inputTensor->data.uint8,INPUT_IMAGE_WIDTH,INPUT_IMAGE_HEIGHT); + + + /* Display this image on the LCD. */ + platform.data_psn->present_data_image( + g_image_buffer, + nCols, nRows, nPresentationChannels, + dataPsnImgStartX, dataPsnImgStartY, dataPsnImgDownscaleFactor); + + /* If the data is signed. */ + if (model.IsDataSigned()) { + image::ConvertImgToInt8(inputTensor->data.data, inputTensor->bytes); + } + + /* Display message on the LCD - inference running. */ + platform.data_psn->present_data_text(str_inf.c_str(), str_inf.size(), + dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0); + + /* Run inference over this image. */ + info("Running inference on image %" PRIu32 " => %s\n", ctx.Get<uint32_t>("imgIndex"), + get_filename(ctx.Get<uint32_t>("imgIndex"))); + + if (!RunInference(model, profiler)) { + return false; + } + + /* Erase. */ + str_inf = std::string(str_inf.size(), ' '); + platform.data_psn->present_data_text(str_inf.c_str(), str_inf.size(), + dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0); + + /* Detector post-processing*/ + TfLiteTensor* output_arr[2] = {nullptr,nullptr}; + output_arr[0] = model.GetOutputTensor(0); + output_arr[1] = model.GetOutputTensor(1); + RunPostProcessing(g_image_buffer,output_arr,results); + + platform.data_psn->present_data_image( + g_image_buffer, + nCols, nRows, nPresentationChannels, + dataPsnImgStartX, dataPsnImgStartY, dataPsnImgDownscaleFactor); + + /*Detector post-processing*/ + + + /* Add results to context for access outside handler. */ + ctx.Set<std::vector<DetectionResult>>("results", results); + +#if VERIFY_TEST_OUTPUT + arm::app::DumpTensor(outputTensor); +#endif /* VERIFY_TEST_OUTPUT */ + + if (!image::PresentInferenceResult(platform, results)) { + return false; + } + + profiler.PrintProfilingResult(); + + IncrementAppCtxIfmIdx(ctx,"imgIndex"); + + } while (runAll && ctx.Get<uint32_t>("imgIndex") != curImIdx); + + return true; + } + +} /* namespace app */ +} /* namespace arm */ |