[GitHub] nswamy commented on a change in pull request #12930: [MXNET-1083] Add the example to demonstrate the inference workflow using C++ API.

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nswamy commented on a change in pull request #12930: [MXNET-1083] Add the example to demonstrate the inference workflow using C++ API.
URL: https://github.com/apache/incubator-mxnet/pull/12930#discussion_r231725815
 
 

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 File path: cpp-package/example/inference/inception_inference.cpp
 ##########
 @@ -0,0 +1,380 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you 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.
+ */
+
+/*
+ * This example demonstrates image classification workflow with pre-trained models using MXNet C++ API.
+ * The example performs following tasks.
+ * 1. Load the pre-trained model,
+ * 2. Load the parameters of pre-trained model,
+ * 3. Load the image to be classified  in to NDArray.
+ * 4. Normalize the image using the mean of images that were used for training.
+ * 5. Run the forward pass and predict the input image.
+ */
+
+#include <iostream>
+#include <fstream>
+#include <map>
+#include <string>
+#include <vector>
+#include "mxnet-cpp/MxNetCpp.h"
+#include <opencv2/opencv.hpp>
+using namespace std;
+using namespace mxnet::cpp;
+
+
+/*
+ * class Predictor
+ *
+ * This class encapsulates the functionality to load the model, process input image and run the forward pass.
+ */
+
+class Predictor {
+ public:
+    Predictor() {}
+    Predictor(const std::string model_json,
+              const std::string model_params,
+              const Shape& input_shape,
 
 Review comment:
   is this Predictor specific to this example? if not there might be models that take more than one input, you should keep it generic

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