introduce rgbPixelBytes

Author: jonpsy

tensorflow_lite_support/cc/task/vision/image_transformer.cc

@@ -154,6 +154,7 @@ StatusOr<FrameBuffer> ImageTransformer::Transform(
 
 StatusOr<std::unique_ptr<FrameBuffer>> ImageTransformer::Postprocess() {
   std::unique_ptr<FrameBuffer> postprocessed_frame_buffer;
+  const int kRgbPixelBytes = 3;
   const TfLiteTensor* output_tensor =
       TfLiteEngine::GetOutput(GetTfLiteEngine()->interpreter(), 0);
 
@@ -187,19 +188,19 @@ StatusOr<std::unique_ptr<FrameBuffer>> ImageTransformer::Postprocess() {
     const tflite::task::vision::NormalizationOptions& normalization_options =
         GetInputSpecs().normalization_options.value();
 
-    if (normalization_options.size() == 1) {
+    if (normalization_options.num_values == 1) {
       float mean_value = normalization_options.mean_values[0];
       float std_value = normalization_options.std_values[0];
 
       for (size_t i = 0; i < output_byte_size / sizeof(uint8);
            ++i, ++denormalized_output_data, ++output_data) {
-        denormalized_output_data = static_cast<uint8>(std::round(std::min(
+        *denormalized_output_data = static_cast<uint8>(std::round(std::min(
             255.f, std::max(0.f, (*output_data) * std_value + mean_value))));
       }
     } else {
       for (size_t i = 0; i < output_byte_size / sizeof(uint8);
            ++i, ++denormalized_output_data, ++output_data) {
-        denormalized_output_data = static_cast<uint8>(std::round(std::min(
+        *denormalized_output_data = static_cast<uint8>(std::round(std::min(
             255.f,
             std::max(0.f,
                      (*output_data) * normalization_options.std_values[i % 3] +
@@ -210,7 +211,7 @@ StatusOr<std::unique_ptr<FrameBuffer>> ImageTransformer::Postprocess() {
 
   FrameBuffer::Plane postprocessed_plane = {
       /*buffer=*/postprocessed_data.data(),
-      /*stride=*/{output_tensor->dims->data[1] * kRgbPixelBytes,
+      /*stride=*/{output_tensor->dims->data[2] * kRgbPixelBytes,
                   kRgbPixelBytes}};
   postprocessed_frame_buffer = FrameBuffer::Create(
       {postprocessed_plane}, to_buffer_dimension, FrameBuffer::Format::kRGB,

tensorflow_lite_support/cc/task/vision/image_transformer.h

@@ -24,7 +24,7 @@ limitations under the License.
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 #include "tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h"
-#include "tensorflow_lite_support/cc/task/vision/proto/image_transformer_options.proto"
+#include "tensorflow_lite_support/cc/task/vision/proto/image_transformer_options_proto_inc.h"
 
 namespace tflite {
 namespace task {
@@ -61,7 +61,7 @@ namespace vision {
 // A CLI demo tool is available for easily trying out this API, and provides
 // example usage. See:
 // examples/task/vision/desktop/image_classifier_demo.cc
-class ImageTransformer : public BaseVisionTaskApi<tflite::task::vision::FrameBuffer> {
+class ImageTransformer : public BaseVisionTaskApi<::tflite::task::vision::FrameBuffer> {
  public:
   using BaseVisionTaskApi::BaseVisionTaskApi;
 
@@ -85,7 +85,7 @@ class ImageTransformer : public BaseVisionTaskApi<tflite::task::vision::FrameBuf
   //   only supported colorspace for now),
   // - rotate it according to its `Orientation` so that inference is performed
   //   on an "upright" image.
-  tflite::support::StatusOr<tflite::task::vision::FrameBuffer> Transform(
+  tflite::support::StatusOr<::tflite::task::vision::FrameBuffer> Transform(
       const FrameBuffer& frame_buffer);
 
   // Same as above, except that the transformation is performed based on the
@@ -99,15 +99,15 @@ class ImageTransformer : public BaseVisionTaskApi<tflite::task::vision::FrameBuf
   // `frame_buffer` data before any `Orientation` flag gets applied. Also, the
   // region of interest is not clamped, so this method will return a non-ok
   // status if the region is out of these bounds.
-  tflite::support::StatusOr<tflite::task::vision::FrameBuffer> Transform(
+  tflite::support::StatusOr<::tflite::task::vision::FrameBuffer> Transform(
       const FrameBuffer& frame_buffer, const BoundingBox& roi);
 
  protected:
   // The options used to build this ImageTransformer.
   std::unique_ptr<ImageTransformerOptions> options_;
 
   // Post-processing to transform the raw model outputs into image results.
-  tflite::support::StatusOr<std::unique_ptr<tflite::task::vision::FrameBuffer>> Postprocess();
+  tflite::support::StatusOr<std::unique_ptr<::tflite::task::vision::FrameBuffer>> Postprocess();
 
   // Performs sanity checks on the provided ImageTransformerOptions.
   static absl::Status SanityCheckOptions(const ImageTransformerOptions& options);