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/*
* SPDX-FileCopyrightText: Copyright 2021-2022 Arm Limited and/or its affiliates <open-source-office@arm.com>
* 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 "UseCaseCommonUtils.hpp"
#include "ImageUtils.hpp"
#include "InputFiles.hpp"
#include "log_macros.h"
#include <cinttypes>
void DisplayCommonMenu()
{
printf("\n\n");
printf("User input required\n");
printf("Enter option number from:\n\n");
printf(" %u. Classify next ifm\n", common::MENU_OPT_RUN_INF_NEXT);
printf(" %u. Classify ifm at chosen index\n", common::MENU_OPT_RUN_INF_CHOSEN);
printf(" %u. Run classification on all ifm\n", common::MENU_OPT_RUN_INF_ALL);
printf(" %u. Show NN model info\n", common::MENU_OPT_SHOW_MODEL_INFO);
printf(" %u. List ifm\n\n", common::MENU_OPT_LIST_IFM);
printf(" Choice: ");
fflush(stdout);
}
bool PresentInferenceResult(const std::vector<arm::app::ClassificationResult> &results)
{
constexpr uint32_t dataPsnTxtStartX1 = 150;
constexpr uint32_t dataPsnTxtStartY1 = 30;
constexpr uint32_t dataPsnTxtStartX2 = 10;
constexpr uint32_t dataPsnTxtStartY2 = 150;
constexpr uint32_t dataPsnTxtYIncr = 16; /* Row index increment. */
hal_lcd_set_text_color(COLOR_GREEN);
/* Display each result. */
uint32_t rowIdx1 = dataPsnTxtStartY1 + 2 * dataPsnTxtYIncr;
uint32_t rowIdx2 = dataPsnTxtStartY2;
info("Final results:\n");
info("Total number of inferences: 1\n");
for (uint32_t i = 0; i < results.size(); ++i) {
std::string resultStr =
std::to_string(i + 1) + ") " +
std::to_string(results[i].m_labelIdx) +
" (" + std::to_string(results[i].m_normalisedVal) + ")";
hal_lcd_display_text(
resultStr.c_str(), resultStr.size(),
dataPsnTxtStartX1, rowIdx1, false);
rowIdx1 += dataPsnTxtYIncr;
resultStr = std::to_string(i + 1) + ") " + results[i].m_label;
hal_lcd_display_text(
resultStr.c_str(), resultStr.size(),
dataPsnTxtStartX2, rowIdx2, 0);
rowIdx2 += dataPsnTxtYIncr;
info("%" PRIu32 ") %" PRIu32 " (%f) -> %s\n", i,
results[i].m_labelIdx, results[i].m_normalisedVal,
results[i].m_label.c_str());
}
return true;
}
void IncrementAppCtxIfmIdx(arm::app::ApplicationContext& ctx, const std::string& useCase)
{
#if NUMBER_OF_FILES > 0
auto curImIdx = ctx.Get<uint32_t>(useCase);
if (curImIdx + 1 >= NUMBER_OF_FILES) {
ctx.Set<uint32_t>(useCase, 0);
return;
}
++curImIdx;
ctx.Set<uint32_t>(useCase, curImIdx);
#else /* NUMBER_OF_FILES > 0 */
UNUSED(ctx);
UNUSED(useCase);
#endif /* NUMBER_OF_FILES > 0 */
}
bool SetAppCtxIfmIdx(arm::app::ApplicationContext& ctx, uint32_t idx, const std::string& ctxIfmName)
{
#if NUMBER_OF_FILES > 0
if (idx >= NUMBER_OF_FILES) {
printf_err("Invalid idx %" PRIu32 " (expected less than %u)\n",
idx, NUMBER_OF_FILES);
return false;
}
ctx.Set<uint32_t>(ctxIfmName, idx);
return true;
#else /* NUMBER_OF_FILES > 0 */
UNUSED(ctx);
UNUSED(idx);
UNUSED(ctxIfmName);
return false;
#endif /* NUMBER_OF_FILES > 0 */
}
namespace arm {
namespace app {
bool RunInference(arm::app::Model& model, Profiler& profiler)
{
profiler.StartProfiling("Inference");
bool runInf = model.RunInference();
profiler.StopProfiling();
return runInf;
}
int ReadUserInputAsInt()
{
char chInput[128];
memset(chInput, 0, sizeof(chInput));
hal_get_user_input(chInput, sizeof(chInput));
return atoi(chInput);
}
void DumpTensorData(const uint8_t* tensorData,
size_t size,
size_t lineBreakForNumElements)
{
char strhex[8];
std::string strdump;
for (size_t i = 0; i < size; ++i) {
if (0 == i % lineBreakForNumElements) {
printf("%s\n\t", strdump.c_str());
strdump.clear();
}
snprintf(strhex, sizeof(strhex) - 1,
"0x%02x, ", tensorData[i]);
strdump += std::string(strhex);
}
if (!strdump.empty()) {
printf("%s\n", strdump.c_str());
}
}
void DumpTensor(const TfLiteTensor* tensor, const size_t lineBreakForNumElements)
{
if (!tensor) {
printf_err("invalid tensor\n");
return;
}
const uint32_t tensorSz = tensor->bytes;
const auto* tensorData = tflite::GetTensorData<uint8_t>(tensor);
DumpTensorData(tensorData, tensorSz, lineBreakForNumElements);
}
bool ListFilesHandler(ApplicationContext& ctx)
{
auto& model = ctx.Get<Model&>("model");
constexpr uint32_t dataPsnTxtStartX = 20;
constexpr uint32_t dataPsnTxtStartY = 40;
if (!model.IsInited()) {
printf_err("Model is not initialised! Terminating processing.\n");
return false;
}
/* Clear the LCD */
hal_lcd_clear(COLOR_BLACK);
/* Show the total number of embedded files. */
std::string strNumFiles = std::string{"Total Number of Files: "} +
std::to_string(NUMBER_OF_FILES);
hal_lcd_display_text(strNumFiles.c_str(),
strNumFiles.size(),
dataPsnTxtStartX,
dataPsnTxtStartY,
false);
#if NUMBER_OF_FILES > 0
constexpr uint32_t dataPsnTxtYIncr = 16;
info("List of Files:\n");
uint32_t yVal = dataPsnTxtStartY + dataPsnTxtYIncr;
for (uint32_t i = 0; i < NUMBER_OF_FILES; ++i, yVal += dataPsnTxtYIncr) {
std::string currentFilename{get_filename(i)};
hal_lcd_display_text(currentFilename.c_str(),
currentFilename.size(),
dataPsnTxtStartX, yVal, false);
info("\t%" PRIu32 " => %s\n", i, currentFilename.c_str());
}
#endif /* NUMBER_OF_FILES > 0 */
return true;
}
} /* namespace app */
} /* namespace arm */
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