[TEST] Add gesture model for test (#1670)

* [TEST] add gesture model for test

test/CMakeLists.txt

@@ -459,6 +459,10 @@ if (NOT FOUND_MATCH)
     ADD_EXECUTABLE(test-ocr net/test_ocr.cpp test_helper.h test_include.h)
     target_link_libraries(test-ocr paddle-mobile)
 
+    ADD_EXECUTABLE(test-gesture net/test_gesture.cpp test_helper.h test_include.h)
+    target_link_libraries(test-gesture paddle-mobile)
+  
+
     ADD_EXECUTABLE(test-sequence-expand-op operators/test_sequence_expand_op.cpp test_helper.h test_include.h)
     target_link_libraries(test-sequence-expand-op paddle-mobile)
 

test/net/test_gesture.cpp

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+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 <fstream>
+#include <iostream>
+#include "../test_helper.h"
+#include "../test_include.h"
+
+const int max_run_times = 10;
+
+int main(int argc, char **argv) {
+  if (argc < 3) {
+    std::cerr
+        << "Usage: ./test_ocr [detect_model_dir|recog_model_dir] image_path"
+        << std::endl;
+    return 1;
+  }
+  std::string model_dir = argv[1];
+  std::string image_path = argv[2];
+
+  // init input, output params
+  std::vector<float> input_vec;
+  std::vector<int64_t> input_shape;
+  std::vector<std::string> output_fetch_nodes;
+  int PRINT_NODE_ELEM_NUM = 10;
+
+  input_shape.emplace_back(1);
+  input_shape.emplace_back(3);
+  input_shape.emplace_back(192);
+  input_shape.emplace_back(192);
+  output_fetch_nodes.emplace_back("detection_output_0.tmp_0");
+  std::shared_ptr<framework::LoDTensor> outputs[output_fetch_nodes.size()];
+
+  // init paddle instance
+  paddle_mobile::PaddleMobile<paddle_mobile::CPU> paddle_mobile;
+  paddle_mobile.SetThreadNum(1);
+  std::cout << "start load " << std::endl;
+  auto load_success = paddle_mobile.Load(std::string(model_dir) + "/model",
+                                         std::string(model_dir) + "/params",
+                                         true, false, 1, true);
+  std::cout << "load_success:" << load_success << std::endl;
+  // input image raw tensor, generated by
+  // [scripts](tools/python/imagetools/img2nchw.py)
+  std::cout << "image_path: " << image_path << std::endl;
+  std::cout << "input_shape: " << input_shape[0] << ", " << input_shape[1]
+            << ", " << input_shape[2] << ", " << input_shape[3] << std::endl;
+  GetInput<float>(image_path, &input_vec, input_shape);
+
+  // model predict
+  auto pred_start_time = paddle_mobile::time();
+  for (int run_idx = 0; run_idx < max_run_times; ++run_idx) {
+    paddle_mobile.Predict(input_vec, input_shape);
+    for (int out_idx = 0; out_idx < output_fetch_nodes.size(); ++out_idx) {
+      auto fetch_name = output_fetch_nodes[out_idx];
+      outputs[out_idx] = paddle_mobile.Fetch(fetch_name);
+    }
+  }
+  auto pred_end_time = paddle_mobile::time();
+
+  // inference time
+  double pred_time =
+      paddle_mobile::time_diff(pred_start_time, pred_end_time) / max_run_times;
+  std::cout << "predict time(ms): " << pred_time << std::endl;
+
+  // output result
+  for (int out_idx = 0; out_idx < output_fetch_nodes.size(); ++out_idx) {
+    std::string node_id = output_fetch_nodes[out_idx];
+    auto node_lod_tensor = outputs[out_idx];
+    int node_elem_num = node_lod_tensor->numel();
+    float *node_ptr = node_lod_tensor->data<float>();
+    std::cout << "==== output_fetch_nodes[" << out_idx
+              << "] =====" << std::endl;
+    std::cout << "node_id: " << node_id << std::endl;
+    std::cout << "node_elem_num: " << node_elem_num << std::endl;
+    std::cout << "PRINT_NODE_ELEM_NUM: " << PRINT_NODE_ELEM_NUM << std::endl;
+    PRINT_NODE_ELEM_NUM =
+        (node_elem_num > PRINT_NODE_ELEM_NUM) ? PRINT_NODE_ELEM_NUM : 0;
+    for (int eidx = 0; eidx < PRINT_NODE_ELEM_NUM; ++eidx) {
+      std::cout << node_id << "[" << eidx << "]: " << node_ptr[eidx]
+                << std::endl;
+    }
+    std::cout << std::endl;
+  }
+
+  return 0;
+}

test/net/test_ocr.cpp

@@ -56,10 +56,11 @@ int main(int argc, char **argv) {
   // init paddle instance
   paddle_mobile::PaddleMobile<paddle_mobile::CPU> paddle_mobile;
   paddle_mobile.SetThreadNum(1);
+  std::cout << "start load " << std::endl;
   auto load_success = paddle_mobile.Load(std::string(model_dir) + "/model",
                                          std::string(model_dir) + "/params",
                                          true, false, 1, true);
-
+  std::cout << "load_success:" << load_success << std::endl;
   // input image raw tensor, generated by
   // [scripts](tools/python/imagetools/img2nchw.py)
   std::cout << "image_path: " << image_path << std::endl;