Face detection demo from Emza Visual Sense

Signed-off-by: Michael Levit michaell@emza-vs.com

Change-Id: I7958b05b5dbe9a785e0f8a241b716c17a9ca976f

5 files changed, 369 insertions, 0 deletions

diff --git a/tests/use_case/object_detection/ExpectedObjectDetectionResults.cpp b/tests/use_case/object_detection/ExpectedObjectDetectionResults.cpp
new file mode 100644
index 0000000..2c69057
--- /dev/null
+++ b/tests/use_case/object_detection/ExpectedObjectDetectionResults.cpp
@@ -0,0 +1,66 @@
+/*
+ * 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.
+ */
+#include "ExpectedObjectDetectionResults.hpp"
+
+
+/*
+//Reference results
+Got 2 boxes
+0)  (0.999246) -> Detection box: {x=89,y=17,w=41,h=56}
+1)  (0.995367) -> Detection box: {x=27,y=81,w=48,h=53}
+Entering TestInference
+Got 1 boxes
+0)  (0.998107) -> Detection box: {x=87,y=35,w=53,h=64}
+Entering TestInference
+Got 2 boxes
+0)  (0.999244) -> Detection box: {x=105,y=73,w=58,h=66}
+1)  (0.985984) -> Detection box: {x=34,y=40,w=70,h=95}
+Entering TestInference
+Got 2 boxes
+0)  (0.993294) -> Detection box: {x=22,y=43,w=39,h=53}
+1)  (0.992021) -> Detection box: {x=63,y=60,w=38,h=45}
+
+*/
+
+void get_expected_ut_results(std::vector<std::vector<arm::app::DetectionResult>> &expected_results)
+{
+
+    expected_results.resize(4);
+
+    std::vector<arm::app::DetectionResult> img_1(2);
+    std::vector<arm::app::DetectionResult> img_2(1);
+    std::vector<arm::app::DetectionResult> img_3(2);
+    std::vector<arm::app::DetectionResult> img_4(2);
+
+    img_1[0] = arm::app::DetectionResult(0.99,89,17,41,56);
+    img_1[1] = arm::app::DetectionResult(0.99,27,81,48,53);
+
+    img_2[0] = arm::app::DetectionResult(0.99,87,35,53,64);
+
+    img_3[0] = arm::app::DetectionResult(0.99,105,73,58,66);
+    img_3[1] = arm::app::DetectionResult(0.98,34,40,70,95);
+
+    img_4[0] = arm::app::DetectionResult(0.99,22,43,39,53);
+    img_4[1] = arm::app::DetectionResult(0.99,63,60,38,45);
+
+    expected_results[0] = img_1;
+    expected_results[1] = img_2;
+    expected_results[2] = img_3;
+    expected_results[3] = img_4;
+
+
+}
diff --git a/tests/use_case/object_detection/InferenceTestYoloFastest.cc b/tests/use_case/object_detection/InferenceTestYoloFastest.cc
new file mode 100644
index 0000000..e6ae573
--- /dev/null
+++ b/tests/use_case/object_detection/InferenceTestYoloFastest.cc
@@ -0,0 +1,124 @@
+/*
+ * 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.
+ */
+#include "hal.h"
+#include "ImageUtils.hpp"
+#include "YoloFastestModel.hpp"
+#include "TensorFlowLiteMicro.hpp"
+#include "DetectorPostProcessing.hpp"
+#include "InputFiles.hpp"
+#include "UseCaseCommonUtils.hpp"
+#include "DetectionUseCaseUtils.hpp"
+#include "ExpectedObjectDetectionResults.hpp"
+
+#include <catch.hpp>
+
+
+bool RunInference(arm::app::Model& model, const uint8_t imageData[])
+{
+    TfLiteTensor* inputTensor = model.GetInputTensor(0);
+    REQUIRE(inputTensor);
+
+    const size_t copySz = inputTensor->bytes < (INPUT_IMAGE_WIDTH*INPUT_IMAGE_HEIGHT) ?
+                            inputTensor->bytes :
+                            (INPUT_IMAGE_WIDTH*INPUT_IMAGE_HEIGHT);
+
+    arm::app::RgbToGrayscale(imageData,inputTensor->data.uint8,INPUT_IMAGE_WIDTH,INPUT_IMAGE_HEIGHT);            
+
+    if(model.IsDataSigned()){
+        convertImgIoInt8(inputTensor->data.data, copySz);
+    }
+
+    return model.RunInference();
+}
+
+template<typename T>
+void TestInference(int imageIdx, arm::app::Model& model, T tolerance) {
+
+    info("Entering TestInference for image %d \n", imageIdx);
+
+    std::vector<arm::app::DetectionResult> results;
+    auto image = get_img_array(imageIdx);
+
+    REQUIRE(RunInference(model, image));
+
+
+    TfLiteTensor* output_arr[2] = {nullptr,nullptr};
+    output_arr[0] = model.GetOutputTensor(0);
+    output_arr[1] = model.GetOutputTensor(1);
+    
+    for (int i =0; i < 2; i++) {
+        REQUIRE(output_arr[i]);    
+        REQUIRE(tflite::GetTensorData<T>(output_arr[i]));
+    }
+
+    RunPostProcessing(NULL,output_arr,results);
+    
+    info("Got %ld boxes \n",results.size());
+      
+    std::vector<std::vector<arm::app::DetectionResult>> expected_results;
+    get_expected_ut_results(expected_results);
+    
+    /*validate got the same number of boxes */
+    REQUIRE(results.size() == expected_results[imageIdx].size());
+    
+    
+    for (int i=0; i < (int)results.size(); i++) {
+    
+        info("%" PRIu32 ")  (%f) -> %s {x=%d,y=%d,w=%d,h=%d}\n", (int)i, 
+                 results[i].m_normalisedVal, "Detection box:",
+               results[i].m_x0, results[i].m_y0, results[i].m_w, results[i].m_h );
+
+        /*validate confidence and box dimensions */
+        REQUIRE(fabs(results[i].m_normalisedVal - expected_results[imageIdx][i].m_normalisedVal) < 0.1);
+        REQUIRE(static_cast<int>(results[i].m_x0) == Approx(static_cast<int>((T)expected_results[imageIdx][i].m_x0)).epsilon(tolerance));
+        REQUIRE(static_cast<int>(results[i].m_y0) == Approx(static_cast<int>((T)expected_results[imageIdx][i].m_y0)).epsilon(tolerance));
+        REQUIRE(static_cast<int>(results[i].m_w) == Approx(static_cast<int>((T)expected_results[imageIdx][i].m_w)).epsilon(tolerance));
+        REQUIRE(static_cast<int>(results[i].m_h) == Approx(static_cast<int>((T)expected_results[imageIdx][i].m_h)).epsilon(tolerance));
+    }
+    
+    
+}
+
+
+TEST_CASE("Running inference with TensorFlow Lite Micro and YoloFastest", "[YoloFastest]")
+{
+    SECTION("Executing inferences sequentially")
+    {
+        arm::app::YoloFastestModel model{};
+
+        REQUIRE_FALSE(model.IsInited());
+        REQUIRE(model.Init());
+        REQUIRE(model.IsInited());
+
+        for (uint32_t i = 0 ; i < NUMBER_OF_FILES; ++i) {
+            TestInference<uint8_t>(i, model, 1);
+        }
+    }
+
+    for (uint32_t i = 0 ; i < NUMBER_OF_FILES; ++i) {
+        DYNAMIC_SECTION("Executing inference with re-init")
+        {
+            arm::app::YoloFastestModel model{};
+
+            REQUIRE_FALSE(model.IsInited());
+            REQUIRE(model.Init());
+            REQUIRE(model.IsInited());
+
+            TestInference<uint8_t>(i, model, 1);
+        }
+    }
+}
diff --git a/tests/use_case/object_detection/ObjectDetectionTests.cc b/tests/use_case/object_detection/ObjectDetectionTests.cc
new file mode 100644
index 0000000..dd2d707
--- /dev/null
+++ b/tests/use_case/object_detection/ObjectDetectionTests.cc
@@ -0,0 +1,18 @@
+/*
+ * 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.
+ */
+#define CATCH_CONFIG_MAIN
+#include <catch.hpp>
diff --git a/tests/use_case/object_detection/ObjectDetectionUCTest.cc b/tests/use_case/object_detection/ObjectDetectionUCTest.cc
new file mode 100644
index 0000000..0a0486e
--- /dev/null
+++ b/tests/use_case/object_detection/ObjectDetectionUCTest.cc
@@ -0,0 +1,135 @@
+/*
+ * 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.
+ */
+#include "DetectionResult.hpp"
+//include "Detector.hpp"
+#include "hal.h"
+#include "YoloFastestModel.hpp"
+#include "UseCaseHandler.hpp"
+#include "UseCaseCommonUtils.hpp"
+
+#include <catch.hpp>
+
+TEST_CASE("Model info")
+{
+printf("Entering Model info \n");
+    /* Model wrapper object. */
+    arm::app::YoloFastestModel model;
+
+    /* Load the model. */
+    REQUIRE(model.Init());
+
+    /* Instantiate application context. */
+    arm::app::ApplicationContext caseContext;
+
+    caseContext.Set<arm::app::Model&>("model", model);
+
+    REQUIRE(model.ShowModelInfoHandler());
+}
+
+
+TEST_CASE("Inference by index")
+{
+printf("Entering Inference by index \n");
+    hal_platform    platform;
+    data_acq_module data_acq;
+    data_psn_module data_psn;
+    platform_timer  timer;
+
+    /* Initialise the HAL and platform. */
+    hal_init(&platform, &data_acq, &data_psn, &timer);
+    hal_platform_init(&platform);
+
+    /* Model wrapper object. */
+    arm::app::YoloFastestModel model;
+
+    /* Load the model. */
+    REQUIRE(model.Init());
+
+    /* Instantiate application context. */
+    arm::app::ApplicationContext caseContext;
+
+    arm::app::Profiler profiler{&platform, "object_detection"};
+    caseContext.Set<arm::app::Profiler&>("profiler", profiler);
+    caseContext.Set<hal_platform&>("platform", platform);
+    caseContext.Set<arm::app::Model&>("model", model);
+    caseContext.Set<uint32_t>("imgIndex", 0);
+
+    REQUIRE(arm::app::ObjectDetectionHandler(caseContext, 0, false));
+
+    auto results = caseContext.Get<std::vector<arm::app::DetectionResult>>("results");
+
+}
+
+
+TEST_CASE("Inference run all images")
+{
+    printf("Entering Inference run all images \n");
+    hal_platform    platform;
+    data_acq_module data_acq;
+    data_psn_module data_psn;
+    platform_timer  timer;
+
+    /* Initialise the HAL and platform. */
+    hal_init(&platform, &data_acq, &data_psn, &timer);
+    hal_platform_init(&platform);
+
+    /* Model wrapper object. */
+    arm::app::YoloFastestModel model;
+
+    /* Load the model. */
+    REQUIRE(model.Init());
+
+    /* Instantiate application context. */
+    arm::app::ApplicationContext caseContext;
+
+    arm::app::Profiler profiler{&platform, "object_detection"};
+    caseContext.Set<arm::app::Profiler&>("profiler", profiler);
+    caseContext.Set<hal_platform&>("platform", platform);
+    caseContext.Set<arm::app::Model&>("model", model);
+    caseContext.Set<uint32_t>("imgIndex", 0);
+
+    REQUIRE(arm::app::ObjectDetectionHandler(caseContext, 0, true));
+    
+}
+
+
+TEST_CASE("List all images")
+{
+printf("Entering List all images \n");
+    hal_platform    platform;
+    data_acq_module data_acq;
+    data_psn_module data_psn;
+    platform_timer  timer;
+
+    /* Initialise the HAL and platform. */
+    hal_init(&platform, &data_acq, &data_psn, &timer);
+    hal_platform_init(&platform);
+
+    /* Model wrapper object. */
+    arm::app::YoloFastestModel model;
+
+    /* Load the model. */
+    REQUIRE(model.Init());
+
+    /* Instantiate application context. */
+    arm::app::ApplicationContext caseContext;
+
+    caseContext.Set<hal_platform&>("platform", platform);
+    caseContext.Set<arm::app::Model&>("model", model);
+
+    REQUIRE(arm::app::ListFilesHandler(caseContext));
+}
diff --git a/tests/use_case/object_detection/include/ExpectedObjectDetectionResults.hpp b/tests/use_case/object_detection/include/ExpectedObjectDetectionResults.hpp
new file mode 100644
index 0000000..09edc00
--- /dev/null
+++ b/tests/use_case/object_detection/include/ExpectedObjectDetectionResults.hpp
@@ -0,0 +1,26 @@
+/*
+ * 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 EXPECTED_OBJECT_DETECTION_RESULTS_H
+#define EXPECTED_OBJECT_DETECTION_RESULTS_H
+
+#include "DetectionResult.hpp"
+#include <vector>
+
+void get_expected_ut_results(std::vector<std::vector<arm::app::DetectionResult>> &expected_results);
+
+
+#endif /* EXPECTED_OBJECT_DETECTION_RESULTS_H */