MLECO-2946: Draw boxes directly on the LCD
* No longer copy the source image
* Boxes are drawn directly to LCD rather than on source image
* Change c style casts to static casts
Signed-off-by: Richard Burton <richard.burton@arm.com>
Change-Id: Ib8e926cb1a87bc2c40424eb5aace40170c526f1d
diff --git a/source/use_case/object_detection/src/UseCaseHandler.cc b/source/use_case/object_detection/src/UseCaseHandler.cc
index 620ce6c..257da4f 100644
--- a/source/use_case/object_detection/src/UseCaseHandler.cc
+++ b/source/use_case/object_detection/src/UseCaseHandler.cc
@@ -35,7 +35,21 @@
* @return true if successful, false otherwise.
**/
static bool PresentInferenceResult(hal_platform& platform,
- const std::vector<arm::app::object_detection::DetectionResult>& results);
+ const std::vector<arm::app::object_detection::DetectionResult>& results);
+
+ /**
+ * @brief Draw boxes directly on the LCD for all detected objects.
+ * @param[in] platform Reference to the hal platform object.
+ * @param[in] results Vector of detection results to be displayed.
+ * @param[in] imageStartX X coordinate where the image starts on the LCD.
+ * @param[in] imageStartY Y coordinate where the image starts on the LCD.
+ * @param[in] imgDownscaleFactor How much image has been downscaled on LCD.
+ **/
+ static void DrawDetectionBoxes(hal_platform& platform,
+ const std::vector<arm::app::object_detection::DetectionResult>& results,
+ uint32_t imgStartX,
+ uint32_t imgStartY,
+ uint32_t imgDownscaleFactor);
/* Object detection classification handler. */
bool ObjectDetectionHandler(ApplicationContext& ctx, uint32_t imgIndex, bool runAll)
@@ -97,18 +111,12 @@
const size_t copySz = inputTensor->bytes < IMAGE_DATA_SIZE ?
inputTensor->bytes : IMAGE_DATA_SIZE;
- /* Copy of the image used for presentation, original images are read-only */
- std::vector<uint8_t> g_image_buffer(nCols*nRows*channelsImageDisplayed);
- if (nPresentationChannels == 3) {
- memcpy(g_image_buffer.data(),curr_image, nCols * nRows * channelsImageDisplayed);
- } else {
- image::RgbToGrayscale(curr_image, g_image_buffer.data(), nCols * nRows);
- }
+ /* Convert to gray scale and populate input tensor. */
image::RgbToGrayscale(curr_image, dstPtr, copySz);
- /* Display this image on the LCD. */
+ /* Display original image on the LCD. */
platform.data_psn->present_data_image(
- g_image_buffer.data(),
+ curr_image,
nCols, nRows, nPresentationChannels,
dataPsnImgStartX, dataPsnImgStartY, dataPsnImgDownscaleFactor);
@@ -119,7 +127,7 @@
/* Display message on the LCD - inference running. */
platform.data_psn->present_data_text(str_inf.c_str(), str_inf.size(),
- dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0);
+ dataPsnTxtInfStartX, dataPsnTxtInfStartY, false);
/* Run inference over this image. */
info("Running inference on image %" PRIu32 " => %s\n", ctx.Get<uint32_t>("imgIndex"),
@@ -132,24 +140,21 @@
/* Erase. */
str_inf = std::string(str_inf.size(), ' ');
platform.data_psn->present_data_text(str_inf.c_str(), str_inf.size(),
- dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0);
+ dataPsnTxtInfStartX, dataPsnTxtInfStartY, false);
/* Detector post-processing*/
std::vector<object_detection::DetectionResult> results;
TfLiteTensor* modelOutput0 = model.GetOutputTensor(0);
TfLiteTensor* modelOutput1 = model.GetOutputTensor(1);
postp.RunPostProcessing(
- g_image_buffer.data(),
nRows,
nCols,
modelOutput0,
modelOutput1,
results);
- platform.data_psn->present_data_image(
- g_image_buffer.data(),
- nCols, nRows, nPresentationChannels,
- dataPsnImgStartX, dataPsnImgStartY, dataPsnImgDownscaleFactor);
+ /* Draw boxes. */
+ DrawDetectionBoxes(platform, results, dataPsnImgStartX, dataPsnImgStartY, dataPsnImgDownscaleFactor);
#if VERIFY_TEST_OUTPUT
arm::app::DumpTensor(modelOutput0);
@@ -188,5 +193,34 @@
return true;
}
+ static void DrawDetectionBoxes(hal_platform& platform,
+ const std::vector<arm::app::object_detection::DetectionResult>& results,
+ uint32_t imgStartX,
+ uint32_t imgStartY,
+ uint32_t imgDownscaleFactor)
+ {
+ uint32_t lineThickness = 1;
+
+ for (const auto& result: results) {
+ /* Top line. */
+ platform.data_psn->present_box(imgStartX + result.m_x0/imgDownscaleFactor,
+ imgStartY + result.m_y0/imgDownscaleFactor,
+ result.m_w/imgDownscaleFactor, lineThickness, COLOR_GREEN);
+ /* Bot line. */
+ platform.data_psn->present_box(imgStartX + result.m_x0/imgDownscaleFactor,
+ imgStartY + (result.m_y0 + result.m_h)/imgDownscaleFactor - lineThickness,
+ result.m_w/imgDownscaleFactor, lineThickness, COLOR_GREEN);
+
+ /* Left line. */
+ platform.data_psn->present_box(imgStartX + result.m_x0/imgDownscaleFactor,
+ imgStartY + result.m_y0/imgDownscaleFactor,
+ lineThickness, result.m_h/imgDownscaleFactor, COLOR_GREEN);
+ /* Right line. */
+ platform.data_psn->present_box(imgStartX + (result.m_x0 + result.m_w)/imgDownscaleFactor - lineThickness,
+ imgStartY + result.m_y0/imgDownscaleFactor,
+ lineThickness, result.m_h/imgDownscaleFactor, COLOR_GREEN);
+ }
+ }
+
} /* namespace app */
} /* namespace arm */