update

Author: PINTO0309

test/enet/external_libs/tensorflow_prebuilt/linux-cpu-x86_64/libtensorflowlite.so__

@@ -33,11 +33,9 @@ int main()
     auto num_of_threads = 4;
 
     cv::resize(image, image, cv::Size(480, 360));
-    //image = ~image;
     cv::imshow("InputImage for CNN", image);
     image.convertTo(image, CV_32FC1, 1.0 / 255);
-    //cv::waitKey(0);
-    //return 0;
+
     // TFLite
     std::unique_ptr<tflite::FlatBufferModel> model = tflite::FlatBufferModel::BuildFromFile(MODEL_FILENAME);
     TFLITE_MINIMAL_CHECK(model != nullptr);
@@ -66,37 +64,25 @@ int main()
     std::cout << "input shape: " << input_string_stream.str() << std::endl;
     std::cout << "input array size: " << input_array_size << std::endl;
     printf("=== Got model input size ===\n");
-    cv::waitKey(0);
-    //return 0;
 
     // Allocate tensor buffers.
     interpreter->SetNumThreads(num_of_threads);
     TFLITE_MINIMAL_CHECK(interpreter->AllocateTensors() == kTfLiteOk);
     printf("=== Pre-invoke Interpreter State ===\n");
     tflite::PrintInterpreterState(interpreter.get());
-    cv::waitKey(0);
-    //return 0;
 
     // Set data to input tensor
-    //float* input = interpreter->typed_input_tensor<float>(0);
+    float* input = interpreter->typed_input_tensor<float>(0);
     //memcpy(input, image.reshape(0, 1).data, sizeof(float) * 1 * 360 * 480 * 3);
-    //memcpy(input, image.data, sizeof(float) * input_array_size);
-
-    uint8_t* input = interpreter->typed_input_tensor<uint8_t>(0);
-    std::vector<uint8_t> input_data(image.data,
-                                    image.data + (image.cols * image.rows * image.elemSize()));
-    memcpy(input, input_data.data(), input_data.size());
-
+    memcpy(input, image.data, sizeof(float) * input_array_size);
     printf("\n\n=== MEM copied ===\n");
-    cv::waitKey(0);
 
     // Run inference
     printf("\n\n=== Pre-invoke Interpreter State ===\n");
     TFLITE_MINIMAL_CHECK(interpreter->Invoke() == kTfLiteOk);
     printf("\n\n=== Post-invoke Interpreter State ===\n");
     tflite::PrintInterpreterState(interpreter.get());
-    //cv::waitKey(0);
-    //return 0;
+
     // Get data from output tensor
     float* probs = interpreter->typed_output_tensor<float>(0);
     for (int i = 0; i < 10; i++) {