Isaac ROS 2.0.0

Author: hemalshahNV

README.md

@@ -1,5 +1,5 @@
 # SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
-# Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# Copyright (c) 2022-2023 NVIDIA CORPORATION & AFFILIATES. 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.
@@ -15,7 +15,7 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-cmake_minimum_required(VERSION 3.23.2)
+cmake_minimum_required(VERSION 3.22.1)
 project(isaac_ros_detectnet LANGUAGES C CXX)
 
 if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang")
@@ -43,6 +43,12 @@ if(BUILD_TESTING)
   find_package(ament_lint_auto REQUIRED)
   ament_lint_auto_find_test_dependencies()
 
+
+  # The FindPythonInterp and FindPythonLibs modules are removed
+  if(POLICY CMP0148)
+    cmake_policy(SET CMP0148 OLD)
+  endif()
+
   find_package(launch_testing_ament_cmake REQUIRED)
   add_launch_test(test/isaac_ros_detectnet_pol_test.py TIMEOUT "600")
 endif()

docs/tutorial-custom-model.md

@@ -24,7 +24,7 @@ find_package(GXF ${ISAAC_ROS_GXF_VERSION} MODULE REQUIRED
     std
 )
 find_package(isaac_ros_nitros_detection2_d_array_type REQUIRED)
-include(YamlCpp)
+find_package(yaml-cpp)
 
 # DetectNet extension
 add_library(gxf_detectnet SHARED

docs/tutorial-isaac-sim.md

@@ -287,11 +287,14 @@ typedef enum
 /**
  * Holds full dimensions (including batch size) for a layer.
  */
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wmissing-field-initializers"
 typedef struct
 {
     int batchSize = 0;
     NvDsInferDims dims = {0};
 } NvDsInferBatchDims;
+#pragma GCC diagnostic pop
 
 /**
  * Extended structure for bound layer information which additionally includes

isaac_ros_detectnet/CMakeLists.txt

@@ -263,18 +263,18 @@ gxf_result_t DetectnetDecoder::tick() noexcept
 
   // TODO(ashwinvk): Do not copy data to host and perform decoding using cuda
   // copy memory to host
-  float cov_tensor_arr[cov_tensor->size() / sizeof(float)]; // since data in tensor is kFloat32
+  std::unique_ptr<float[]> cov_tensor_arr(new float[cov_tensor->element_count()]);
   const cudaError_t cuda_error_cov_tensor = cudaMemcpy(
-    &cov_tensor_arr, cov_tensor->pointer(),
+    cov_tensor_arr.get(), cov_tensor->pointer(),
     cov_tensor->size(), cudaMemcpyDeviceToHost);
   if (cuda_error_cov_tensor != cudaSuccess) {
     GXF_LOG_ERROR("Error while copying kernel: %s", cudaGetErrorString(cuda_error_cov_tensor));
     return GXF_FAILURE;
   }
 
-  float bbox_tensor_arr[bbox_tensor->size() / sizeof(float)]; // since data in tensor is kFloat32
+  std::unique_ptr<float[]> bbox_tensor_arr(new float[bbox_tensor->element_count()]);
   const cudaError_t cuda_error_bbox_tensor = cudaMemcpy(
-    &bbox_tensor_arr, bbox_tensor->pointer(),
+    bbox_tensor_arr.get(), bbox_tensor->pointer(),
     bbox_tensor->size(), cudaMemcpyDeviceToHost);
   if (cuda_error_bbox_tensor != cudaSuccess) {
     GXF_LOG_ERROR("Error while copying kernel: %s", cudaGetErrorString(cuda_error_bbox_tensor));
@@ -342,7 +342,7 @@ gxf_result_t DetectnetDecoder::tick() noexcept
         // check if object_class is out of range for label_list_
         if (static_cast<size_t>(object_class) >= label_list_.get().size()) {
           GXF_LOG_ERROR(
-            "[DetectNet Decoder] object_class %i is out of range for provided label_list_ of size %i", object_class,
+            "[DetectNet Decoder] object_class %i is out of range for provided label_list_ of size %lu", object_class,
             label_list_.get().size());
           return GXF_FAILURE;
         }
@@ -369,7 +369,7 @@ gxf_result_t DetectnetDecoder::tick() noexcept
     } else {
       GXF_LOG_ERROR(
         "Invalid value for dbscan_clustering_algorithm: %i",
-        dbscan_clustering_algorithm_);
+        dbscan_clustering_algorithm_.get());
       return GXF_FAILURE;
     }
     NvDsInferDBScanDestroy(dbscan_hdl);

isaac_ros_detectnet/gxf/detectnet/CMakeLists.txt

@@ -1,5 +1,5 @@
 // SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
-// Copyright (c) 2021-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+// Copyright (c) 2021-2023 NVIDIA CORPORATION & AFFILIATES. 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.

isaac_ros_detectnet/gxf/detectnet/deepstream_utils/nvdsinfer/include/nvdsinfer.h

@@ -0,0 +1,16 @@
+# SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
+# Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. 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.
+#
+# SPDX-License-Identifier: Apache-2.0

isaac_ros_detectnet/gxf/detectnet/detectnet_decoder.cpp

@@ -1,5 +1,5 @@
 # SPDX-FileCopyrightText: NVIDIA CORPORATION & AFFILIATES
-# Copyright (c) 2021-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# Copyright (c) 2021-2023 NVIDIA CORPORATION & AFFILIATES. 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.
@@ -35,11 +35,16 @@ def generate_launch_description():
 
     encoder_node = ComposableNode(
         name='dnn_image_encoder',
-        package='isaac_ros_dnn_encoders',
+        package='isaac_ros_dnn_image_encoder',
         plugin='nvidia::isaac_ros::dnn_inference::DnnImageEncoderNode',
         parameters=[{
+            'input_image_width': 1200,
+            'input_image_height': 632,
             'network_image_width': 1200,
-            'network_image_height': 632
+            'network_image_height': 632,
+            'image_mean': [0.0, 0.0, 0.0],
+            'image_stddev': [1.0, 1.0, 1.0],
+            'enable_padding': False
         }],
         remappings=[('encoded_tensor', 'tensor_pub')]
     )