Update evaluation function to support calculate average inference time (#106)

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* Add evaluation calculate time and fix some bugs

* Update classification __init__

* Move to ppseg

Co-authored-by: Jason <jiangjiajun@baidu.com>

csrc/fastdeploy/vision/segmentation/ppseg/FDTensor2CVMat.cc

@@ -0,0 +1,59 @@
+// Copyright (c) 2022 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 "fastdeploy/vision/segmentation/ppseg/model.h"
+
+namespace fastdeploy {
+namespace vision {
+namespace segmentation {
+
+void FDTensor2FP32CVMat(cv::Mat& mat, FDTensor& infer_result,
+                        bool contain_score_map) {
+  // output with argmax channel is 1
+  int channel = 1;
+  int height = infer_result.shape[1];
+  int width = infer_result.shape[2];
+
+  if (contain_score_map) {
+    // output without argmax and convent to NHWC
+    channel = infer_result.shape[3];
+  }
+  // create FP32 cvmat
+  if (infer_result.dtype == FDDataType::INT64) {
+    FDWARNING << "The PaddleSeg model is exported with argmax. Inference "
+                 "result type is " +
+                     Str(infer_result.dtype) +
+                     ". If you want the edge of segmentation image more "
+                     "smoother. Please export model with --without_argmax "
+                     "--with_softmax."
+              << std::endl;
+    int64_t chw = channel * height * width;
+    int64_t* infer_result_buffer = static_cast<int64_t*>(infer_result.Data());
+    std::vector<float_t> float_result_buffer(chw);
+    mat = cv::Mat(height, width, CV_32FC(channel));
+    int index = 0;
+    for (int i = 0; i < height; i++) {
+      for (int j = 0; j < width; j++) {
+        mat.at<float_t>(i, j) =
+            static_cast<float_t>(infer_result_buffer[index++]);
+      }
+    }
+  } else if (infer_result.dtype == FDDataType::FP32) {
+    mat = cv::Mat(height, width, CV_32FC(channel), infer_result.Data());
+  }
+}
+
+}  // namespace segmentation
+}  // namespace vision
+}  // namespace fastdeploy

csrc/fastdeploy/vision/segmentation/ppseg/model.cc

@@ -143,8 +143,7 @@ bool PaddleSegModel::Postprocess(
   Mat* mat = nullptr;
   if (is_resized) {
     cv::Mat temp_mat;
-    utils::FDTensor2FP32CVMat(temp_mat, infer_result,
-                              result->contain_score_map);
+    FDTensor2FP32CVMat(temp_mat, infer_result, result->contain_score_map);
 
     // original image shape
     auto iter_ipt = (*im_info).find("input_shape");

csrc/fastdeploy/vision/segmentation/ppseg/model.h

@@ -38,6 +38,9 @@ class FASTDEPLOY_DECL PaddleSegModel : public FastDeployModel {
   std::vector<std::shared_ptr<Processor>> processors_;
   std::string config_file_;
 };
+
+void FDTensor2FP32CVMat(cv::Mat& mat, FDTensor& infer_result,
+                        bool contain_score_map);
 }  // namespace segmentation
 }  // namespace vision
 }  // namespace fastdeploy