MLECO-3079: Implement image classification API
All ML related work for image classification seperated out and accessed via new Runner
Further work to improve profiling integration to be done in follow up ticket: MLECO-3154
Signed-off-by: Richard Burton <richard.burton@arm.com>
Change-Id: I0fe0550c932241a2d335a560ecb7abc329c934e9
diff --git a/source/use_case/img_class/src/ImgClassProcessing.cc b/source/use_case/img_class/src/ImgClassProcessing.cc
new file mode 100644
index 0000000..e33e3c1
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+++ b/source/use_case/img_class/src/ImgClassProcessing.cc
@@ -0,0 +1,66 @@
+/*
+ * Copyright (c) 2022 Arm Limited. All rights reserved.
+ * 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 "ImgClassProcessing.hpp"
+#include "ImageUtils.hpp"
+#include "log_macros.h"
+
+namespace arm {
+namespace app {
+
+ ImgClassPreProcess::ImgClassPreProcess(Model* model)
+ {
+ this->m_model = model;
+ }
+
+ bool ImgClassPreProcess::DoPreProcess(const void* data, size_t inputSize)
+ {
+ if (data == nullptr) {
+ printf_err("Data pointer is null");
+ }
+
+ auto input = static_cast<const uint8_t*>(data);
+ TfLiteTensor* inputTensor = this->m_model->GetInputTensor(0);
+
+ memcpy(inputTensor->data.data, input, inputSize);
+ debug("Input tensor populated \n");
+
+ if (this->m_model->IsDataSigned()) {
+ image::ConvertImgToInt8(inputTensor->data.data, inputTensor->bytes);
+ }
+
+ return true;
+ }
+
+ ImgClassPostProcess::ImgClassPostProcess(Classifier& classifier, Model* model,
+ const std::vector<std::string>& labels,
+ std::vector<ClassificationResult>& results)
+ :m_imgClassifier{classifier},
+ m_labels{labels},
+ m_results{results}
+ {
+ this->m_model = model;
+ }
+
+ bool ImgClassPostProcess::DoPostProcess()
+ {
+ return this->m_imgClassifier.GetClassificationResults(
+ this->m_model->GetOutputTensor(0), this->m_results,
+ this->m_labels, 5, false);
+ }
+
+} /* namespace app */
+} /* namespace arm */
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