1 files changed, 74 insertions, 0 deletions
diff --git a/tests/nnfw_api/src/one_op_tests/DetectionPostProcess.test.cc b/tests/nnfw_api/src/one_op_tests/DetectionPostProcess.test.cc
new file mode 100644
index 000000000..188638bbb
--- /dev/null
+++ b/tests/nnfw_api/src/one_op_tests/DetectionPostProcess.test.cc
@@ -0,0 +1,74 @@
+/*
+ * Copyright (c) 2021 Samsung Electronics Co., Ltd. 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 "GenModelTest.h"
+
+#include <memory>
+
+TEST_F(GenModelTest, OneOp_DetectionPostProcess_SingleBox)
+{
+  CircleGen cgen;
+
+  int boxes = cgen.addTensor({{1, 1, 4}, circle::TensorType::TensorType_FLOAT32});
+  int scores = cgen.addTensor({{1, 1, 2}, circle::TensorType::TensorType_FLOAT32});
+  int anchors = cgen.addTensor({{1, 1, 4}, circle::TensorType::TensorType_FLOAT32});
+
+  int box_coors = cgen.addTensor({{1, 1, 4}, circle::TensorType::TensorType_FLOAT32});
+  int box_classes = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
+  int box_scores = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
+  int num_selected = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
+
+  cgen.addOperatorDetectionPostProcess(
+    {{boxes, scores, anchors}, {box_coors, box_classes, box_scores, num_selected}}, 1, 10, 10, 5, 5,
+    0.8, 0.5, 1, 1, 1);
+  cgen.setInputsAndOutputs({boxes, scores, anchors},
+                           {box_coors, box_classes, box_scores, num_selected});
+
+  _context = std::make_unique<GenModelTestContext>(cgen.finish());
+  _context->addTestCase(uniformTCD<float>({{0, 0, 0, 0}, {0, 0.9}, {0, 0, 1, 1}},
+                                          {{-0.5, -0.5, 0.5, 0.5}, {0}, {0.9}, {1}}));
+  _context->setBackends({"cpu"});
+
+  SUCCEED();
+}
+
+TEST_F(GenModelTest, neg_OneOp_DetectionPostProcess_SinglBox_MultiClasses)
+{
+  CircleGen cgen;
+
+  int boxes = cgen.addTensor({{1, 1, 4}, circle::TensorType::TensorType_FLOAT32});
+  int scores = cgen.addTensor({{1, 1, 3}, circle::TensorType::TensorType_FLOAT32});
+  int anchors = cgen.addTensor({{1, 1, 4}, circle::TensorType::TensorType_FLOAT32});
+
+  int box_coors = cgen.addTensor({{1, 1, 4}, circle::TensorType::TensorType_FLOAT32});
+  int box_classes = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
+  int box_scores = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
+  int num_selected = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
+
+  cgen.addOperatorDetectionPostProcess(
+    {{boxes, scores, anchors}, {box_coors, box_classes, box_scores, num_selected}}, 2, 10, 10, 5, 5,
+    0.8, 0.5, 1, 1, 1);
+  cgen.setInputsAndOutputs({boxes, scores, anchors},
+                           {box_coors, box_classes, box_scores, num_selected});
+
+  _context = std::make_unique<GenModelTestContext>(cgen.finish());
+  _context->addTestCase(uniformTCD<float>({{0, 0, 0, 0}, {0, 0.7, 0.9}, {0, 0, 1, 1}},
+                                          {{-0.5, -0.5, 0.5, 0.5}, {1}, {0.9}, {1}}));
+  _context->setBackends({"cpu"});
+  _context->expectFailModelLoad();
+
+  SUCCEED();
+}