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

1 files changed, 73 insertions, 0 deletions

diff --git a/source/application/main/include/BaseProcessing.hpp b/source/application/main/include/BaseProcessing.hpp
new file mode 100644
index 0000000..c1c3255
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+++ b/source/application/main/include/BaseProcessing.hpp
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+/*
+ * 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.
+ */
+#ifndef BASE_PROCESSING_HPP
+#define BASE_PROCESSING_HPP
+
+#include "Model.hpp"
+
+namespace arm {
+namespace app {
+
+    /**
+     * @brief   Base class exposing pre-processing API.
+     *          Use cases should provide their own PreProcessing class that inherits from this one.
+     *          All steps required to take raw input data and populate tensors ready for inference
+     *          should be handled.
+     */
+    class BasePreProcess {
+
+    public:
+        virtual ~BasePreProcess() = default;
+
+        /**
+         * @brief       Should perform pre-processing of 'raw' input data and load it into
+         *              TFLite Micro input tensors ready for inference
+         * @param[in]   input      Pointer to the data that pre-processing will work on.
+         * @param[in]   inputSize  Size of the input data.
+         * @return      true if successful, false otherwise.
+         **/
+        virtual bool DoPreProcess(const void* input, size_t inputSize) = 0;
+
+    protected:
+        Model* m_model = nullptr;
+    };
+
+    /**
+     * @brief   Base class exposing post-processing API.
+     *          Use cases should provide their own PostProcessing class that inherits from this one.
+     *          All steps required to take inference output and populate results vectors should be handled.
+     */
+    class BasePostProcess {
+
+    public:
+        virtual ~BasePostProcess() = default;
+
+        /**
+         * @brief       Should perform post-processing of the result of inference then populate
+         *              populate result data for any later use.
+         * @return      true if successful, false otherwise.
+         **/
+        virtual bool DoPostProcess() = 0;
+
+    protected:
+        Model* m_model = nullptr;
+    };
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* BASE_PROCESSING_HPP */
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