MLECO-2082: Adding visual wake word use case
MLECO-2083: Refactoring img_class and visual wake word
*Added source files for visual wake word
*Added tests
*Added docs
*Added new images for visual wake word demo
*Refactored common functions in img_class, visual wake word and other usecases
Change-Id: Ibd25854e19a5517f940a8d3086a5d4835fab89e9
Signed-off-by: Éanna Ó Catháin <eanna.ocathain@arm.com>
diff --git a/source/application/main/UseCaseCommonUtils.cc b/source/application/main/UseCaseCommonUtils.cc
index 615f684..9834475 100644
--- a/source/application/main/UseCaseCommonUtils.cc
+++ b/source/application/main/UseCaseCommonUtils.cc
@@ -15,91 +15,230 @@
* limitations under the License.
*/
#include "UseCaseCommonUtils.hpp"
-
#include "InputFiles.hpp"
-
#include <inttypes.h>
+
+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);
+}
+
+void image::ConvertImgToInt8(void* data, const size_t kMaxImageSize)
+{
+ auto* tmp_req_data = (uint8_t*) data;
+ auto* tmp_signed_req_data = (int8_t*) data;
+
+ for (size_t i = 0; i < kMaxImageSize; i++) {
+ tmp_signed_req_data[i] = (int8_t) (
+ (int32_t) (tmp_req_data[i]) - 128);
+ }
+}
+
+bool image::PresentInferenceResult(hal_platform& platform,
+ const std::vector<arm::app::ClassificationResult>& results)
+{
+ return PresentInferenceResult(platform, results, false);
+}
+
+bool image::PresentInferenceResult(hal_platform &platform,
+ const std::vector<arm::app::ClassificationResult> &results,
+ const time_t infTimeMs)
+{
+ return PresentInferenceResult(platform, results, true, infTimeMs);
+}
+
+
+bool image::PresentInferenceResult(hal_platform &platform,
+ const std::vector<arm::app::ClassificationResult> &results,
+ bool profilingEnabled,
+ const time_t infTimeMs)
+{
+ 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. */
+
+ if(profilingEnabled)
+ {
+ platform.data_psn->set_text_color(COLOR_YELLOW);
+
+ /* If profiling is enabled, and the time is valid. */
+ info("Final results:\n");
+ info("Total number of inferences: 1\n");
+ if (infTimeMs)
+ {
+ std::string strInf =
+ std::string{"Inference: "} +
+ std::to_string(infTimeMs) +
+ std::string{"ms"};
+ platform.data_psn->present_data_text(
+ strInf.c_str(), strInf.size(),
+ dataPsnTxtStartX1, dataPsnTxtStartY1, 0);
+ }
+ }
+ platform.data_psn->set_text_color(COLOR_GREEN);
+
+ /* Display each result. */
+ uint32_t rowIdx1 = dataPsnTxtStartY1 + 2 * dataPsnTxtYIncr;
+ uint32_t rowIdx2 = dataPsnTxtStartY2;
+
+ if(!profilingEnabled)
+ {
+ 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) + ")";
+
+ platform.data_psn->present_data_text(
+ resultStr.c_str(), resultStr.size(),
+ dataPsnTxtStartX1, rowIdx1, 0);
+ rowIdx1 += dataPsnTxtYIncr;
+
+ resultStr = std::to_string(i + 1) + ") " + results[i].m_label;
+ platform.data_psn->present_data_text(
+ resultStr.c_str(), resultStr.size(),
+ dataPsnTxtStartX2, rowIdx2, 0);
+ rowIdx2 += dataPsnTxtYIncr;
+
+ if(profilingEnabled)
+ {
+ info("%" PRIu32 ") %" PRIu32 " (%f) -> %s\n", i, results[i].m_labelIdx,
+ results[i].m_normalisedVal, results[i].m_label.c_str());
+ }
+ else
+ {
+ 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, std::string useCase)
+{
+ 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);
+}
+
+bool SetAppCtxIfmIdx(arm::app::ApplicationContext& ctx, uint32_t idx, std::string ctxIfmName)
+{
+ 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;
+}
+
+
namespace arm {
namespace app {
- bool RunInference(arm::app::Model& model, Profiler& profiler)
- {
- profiler.StartProfiling("Inference");
- bool runInf = model.RunInference();
- profiler.StopProfiling();
- return runInf;
+bool RunInference(arm::app::Model& model, Profiler& profiler)
+{
+ profiler.StartProfiling("Inference");
+ bool runInf = model.RunInference();
+ profiler.StopProfiling();
+
+ return runInf;
+}
+
+int ReadUserInputAsInt(hal_platform& platform)
+{
+ char chInput[128];
+ memset(chInput, 0, sizeof(chInput));
+
+ platform.data_acq->get_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);
}
- int ReadUserInputAsInt(hal_platform& platform)
- {
- char chInput[128];
- memset(chInput, 0, sizeof(chInput));
+ if (!strdump.empty()) {
+ printf("%s\n", strdump.c_str());
+ }
+}
- platform.data_acq->get_input(chInput, sizeof(chInput));
- return atoi(chInput);
+void DumpTensor(const TfLiteTensor* tensor, const size_t lineBreakForNumElements)
+{
+ if (!tensor) {
+ printf_err("invalid tensor\n");
+ return;
}
- void DumpTensorData(const uint8_t* tensorData,
- size_t size,
- size_t lineBreakForNumElements)
- {
- char strhex[8];
- std::string strdump;
+ const uint32_t tensorSz = tensor->bytes;
+ const uint8_t* tensorData = tflite::GetTensorData<uint8_t>(tensor);
- 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);
- }
+ DumpTensorData(tensorData, tensorSz, lineBreakForNumElements);
+}
- if (!strdump.empty()) {
- printf("%s\n", strdump.c_str());
- }
- }
+bool ListFilesHandler(ApplicationContext& ctx)
+{
+ auto& model = ctx.Get<Model&>("model");
+ auto& platform = ctx.Get<hal_platform&>("platform");
- void DumpTensor(const TfLiteTensor* tensor, const size_t lineBreakForNumElements)
- {
- if (!tensor) {
- printf_err("invalid tensor\n");
- return;
- }
+ constexpr uint32_t dataPsnTxtStartX = 20;
+ constexpr uint32_t dataPsnTxtStartY = 40;
- const uint32_t tensorSz = tensor->bytes;
- const uint8_t* tensorData = tflite::GetTensorData<uint8_t>(tensor);
-
- DumpTensorData(tensorData, tensorSz, lineBreakForNumElements);
+ if (!model.IsInited()) {
+ printf_err("Model is not initialised! Terminating processing.\n");
+ return false;
}
- bool ListFilesHandler(ApplicationContext& ctx)
- {
- auto& model = ctx.Get<Model&>("model");
- auto& platform = ctx.Get<hal_platform&>("platform");
+ /* Clear the LCD */
+ platform.data_psn->clear(COLOR_BLACK);
- 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 */
- platform.data_psn->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);
- platform.data_psn->present_data_text(strNumFiles.c_str(),
- strNumFiles.size(),
- dataPsnTxtStartX,
- dataPsnTxtStartY,
- false);
+ /* Show the total number of embedded files. */
+ std::string strNumFiles = std::string{"Total Number of Files: "} +
+ std::to_string(NUMBER_OF_FILES);
+ platform.data_psn->present_data_text(strNumFiles.c_str(),
+ strNumFiles.size(),
+ dataPsnTxtStartX,
+ dataPsnTxtStartY,
+ false);
#if NUMBER_OF_FILES > 0
constexpr uint32_t dataPsnTxtYIncr = 16;
@@ -117,7 +256,7 @@
#endif /* NUMBER_OF_FILES > 0 */
return true;
- }
+}
} /* namespace app */
} /* namespace arm */
\ No newline at end of file