From 6092535575892e12d343ae0d31c129c3949fe509 Mon Sep 17 00:00:00 2001 From: Justin Leung Date: Sun, 18 Feb 2024 09:55:22 +0000 Subject: [PATCH 01/12] Add WIP node with working includes --- .../semantic_segmentation.Dockerfile | 33 +- modules/docker-compose.perception.yaml | 162 +- .../semantic_segmentation/CMakeLists.txt | 53 +- .../semantic_segmentation/config/config.yaml | 3 + .../launch/semantic_segmentation.launch.py | 21 + .../semantic_segmentation/package.xml | 13 +- .../resource/deploy.yaml | 12 + .../resource/dynamic_shape.pbtxt | 4836 +++++++++++++++++ .../src/semantic_segmentation_node.cpp | 82 + watod-config.sh | 2 +- 10 files changed, 5120 insertions(+), 97 deletions(-) create mode 100644 src/perception/semantic_segmentation/config/config.yaml create mode 100644 src/perception/semantic_segmentation/launch/semantic_segmentation.launch.py create mode 100644 src/perception/semantic_segmentation/resource/deploy.yaml create mode 100644 src/perception/semantic_segmentation/resource/dynamic_shape.pbtxt create mode 100644 src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp diff --git a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile index 763cb632..d0a777ba 100644 --- a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile +++ b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile @@ -1,10 +1,24 @@ -ARG BASE_IMAGE=ghcr.io/watonomous/wato_monorepo/base:humble-ubuntu22.04 +ARG BASE_BUILD_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04-devel +ARG BASE_PROD_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04 +ARG PADDLE_INFERENCE_BUILD_URL=ghcr.io/watonomous/perception_paddlepaddle_inference_build_cuda-12.0 +################################ Build library ################################ +FROM ${PADDLE_INFERENCE_BUILD_URL} as PADDLE_INFERENCE_BUILD ################################ Source ################################ -FROM ${BASE_IMAGE} as source +FROM ${BASE_BUILD_IMAGE} as source + +# install tensorrt +RUN apt update && apt install -y tensorrt + WORKDIR ${AMENT_WS}/src +# Copy in the paddle inference library +RUN mkdir -p semantic_segmentation/src +COPY --from=PADDLE_INFERENCE_BUILD /paddle/paddle_inference_cuda120_build.tar semantic_segmentation/src/paddle_inference_cuda120_build.tar +RUN tar -xvf semantic_segmentation/src/paddle_inference_cuda120_build.tar -C semantic_segmentation/src +RUN rm semantic_segmentation/src/paddle_inference_cuda120_build.tar + # Copy in source code COPY src/perception/semantic_segmentation semantic_segmentation COPY src/wato_msgs/sample_msgs sample_msgs @@ -17,7 +31,7 @@ RUN apt-get -qq update && rosdep update && \ | sort > /tmp/colcon_install_list ################################# Dependencies ################################ -FROM ${BASE_IMAGE} as dependencies +FROM ${BASE_BUILD_IMAGE} as dependencies # Install Rosdep requirements COPY --from=source /tmp/colcon_install_list /tmp/colcon_install_list @@ -35,6 +49,7 @@ RUN apt-get -qq autoremove -y && apt-get -qq autoclean && apt-get -qq clean && \ ################################ Build ################################ FROM dependencies as build + # Build ROS2 packages WORKDIR ${AMENT_WS} RUN . /opt/ros/$ROS_DISTRO/setup.sh && \ @@ -45,11 +60,11 @@ RUN . /opt/ros/$ROS_DISTRO/setup.sh && \ COPY docker/wato_ros_entrypoint.sh ${AMENT_WS}/wato_ros_entrypoint.sh ENTRYPOINT ["./wato_ros_entrypoint.sh"] -################################ Prod ################################ -FROM build as deploy +# ################################ Prod ################################ +# FROM build as deploy -# Source Cleanup and Security Setup -RUN chown -R $USER:$USER ${AMENT_WS} -RUN rm -rf src/* +# # Source Cleanup and Security Setup +# RUN chown -R $USER:$USER ${AMENT_WS} +# RUN rm -rf src/* -USER ${USER} +# USER ${USER} diff --git a/modules/docker-compose.perception.yaml b/modules/docker-compose.perception.yaml index fd6ce9b3..af96e54b 100644 --- a/modules/docker-compose.perception.yaml +++ b/modules/docker-compose.perception.yaml @@ -1,68 +1,68 @@ version: "3.8" services: - radar_object_detection: - build: - context: .. - dockerfile: docker/perception/radar_object_detection/radar_object_detection.Dockerfile - cache_from: - - "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:${TAG}" - - "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:main" - target: deploy - image: "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:${TAG}" - command: /bin/bash -c "ros2 launch radar_object_detection radar_object_detection.launch.py" + # radar_object_detection: + # build: + # context: .. + # dockerfile: docker/perception/radar_object_detection/radar_object_detection.Dockerfile + # cache_from: + # - "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:${TAG}" + # - "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:main" + # target: deploy + # image: "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:${TAG}" + # command: /bin/bash -c "ros2 launch radar_object_detection radar_object_detection.launch.py" - camera_object_detection: - build: - context: .. - dockerfile: docker/perception/camera_object_detection/camera_object_detection.Dockerfile - cache_from: - - "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:${TAG}" - - "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:main" - target: deploy - image: "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:${TAG}" - deploy: - resources: - reservations: - devices: - - driver: nvidia - count: 1 - capabilities: [ gpu ] - command: /bin/bash -c "ros2 launch camera_object_detection nuscenes_launch.py" - volumes: - - /mnt/wato-drive2/perception_models/yolov8s.pt:/perception_models/yolov8s.pt + # camera_object_detection: + # build: + # context: .. + # dockerfile: docker/perception/camera_object_detection/camera_object_detection.Dockerfile + # cache_from: + # - "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:${TAG}" + # - "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:main" + # target: deploy + # image: "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:${TAG}" + # deploy: + # resources: + # reservations: + # devices: + # - driver: nvidia + # count: 1 + # capabilities: [ gpu ] + # command: /bin/bash -c "ros2 launch camera_object_detection nuscenes_launch.py" + # volumes: + # - /mnt/wato-drive2/perception_models/yolov8s.pt:/perception_models/yolov8s.pt - lidar_object_detection: - build: - context: .. - dockerfile: docker/perception/lidar_object_detection/lidar_object_detection.Dockerfile - cache_from: - - "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:${TAG}" - - "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:main" - target: deploy - image: "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:${TAG}" - command: /bin/bash -c "ros2 launch lidar_object_detection lidar_object_detection.launch.py" - traffic_light_detection: - build: - context: .. - dockerfile: docker/perception/traffic_light_detection/traffic_light_detection.Dockerfile - cache_from: - - "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:${TAG}" - - "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:main" - target: deploy - image: "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:${TAG}" - command: /bin/bash -c "ros2 launch traffic_light_detection traffic_light_detection.launch.py" + # lidar_object_detection: + # build: + # context: .. + # dockerfile: docker/perception/lidar_object_detection/lidar_object_detection.Dockerfile + # cache_from: + # - "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:${TAG}" + # - "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:main" + # target: deploy + # image: "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:${TAG}" + # command: /bin/bash -c "ros2 launch lidar_object_detection lidar_object_detection.launch.py" + # traffic_light_detection: + # build: + # context: .. + # dockerfile: docker/perception/traffic_light_detection/traffic_light_detection.Dockerfile + # cache_from: + # - "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:${TAG}" + # - "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:main" + # target: deploy + # image: "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:${TAG}" + # command: /bin/bash -c "ros2 launch traffic_light_detection traffic_light_detection.launch.py" - traffic_sign_detection: - build: - context: .. - dockerfile: docker/perception/traffic_sign_detection/traffic_sign_detection.Dockerfile - cache_from: - - "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:${TAG}" - - "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:main" - target: deploy - image: "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:${TAG}" - command: /bin/bash -c "ros2 launch traffic_sign_detection traffic_sign_detection.launch.py" + # traffic_sign_detection: + # build: + # context: .. + # dockerfile: docker/perception/traffic_sign_detection/traffic_sign_detection.Dockerfile + # cache_from: + # - "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:${TAG}" + # - "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:main" + # target: deploy + # image: "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:${TAG}" + # command: /bin/bash -c "ros2 launch traffic_sign_detection traffic_sign_detection.launch.py" semantic_segmentation: build: @@ -71,28 +71,30 @@ services: cache_from: - "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:${TAG}" - "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:main" - target: deploy + # target: deploy image: "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:${TAG}" command: /bin/bash -c "ros2 launch semantic_segmentation semantic_segmentation.launch.py" + volumes: + - /mnt/wato-drive2/perception-weights/semantic_segmentation:/perception_models/semantic_segmentation - lane_detection: - build: - context: .. - dockerfile: docker/perception/lane_detection/lane_detection.Dockerfile - cache_from: - - "${PERCEPTION_LANE_DETECTION_IMAGE}:${TAG}" - - "${PERCEPTION_LANE_DETECTION_IMAGE}:main" - target: deploy - image: "${PERCEPTION_LANE_DETECTION_IMAGE}:${TAG}" - command: /bin/bash -c "ros2 launch lane_detection lane_detection.launch.py" + # lane_detection: + # build: + # context: .. + # dockerfile: docker/perception/lane_detection/lane_detection.Dockerfile + # cache_from: + # - "${PERCEPTION_LANE_DETECTION_IMAGE}:${TAG}" + # - "${PERCEPTION_LANE_DETECTION_IMAGE}:main" + # target: deploy + # image: "${PERCEPTION_LANE_DETECTION_IMAGE}:${TAG}" + # command: /bin/bash -c "ros2 launch lane_detection lane_detection.launch.py" - tracking: - build: - context: .. - dockerfile: docker/perception/tracking/tracking.Dockerfile - cache_from: - - "${PERCEPTION_TRACKING_IMAGE}:${TAG}" - - "${PERCEPTION_TRACKING_IMAGE}:main" - target: deploy - image: "${PERCEPTION_TRACKING_IMAGE}:${TAG}" - command: /bin/bash -c "ros2 launch tracking tracking.launch.py" + # tracking: + # build: + # context: .. + # dockerfile: docker/perception/tracking/tracking.Dockerfile + # cache_from: + # - "${PERCEPTION_TRACKING_IMAGE}:${TAG}" + # - "${PERCEPTION_TRACKING_IMAGE}:main" + # target: deploy + # image: "${PERCEPTION_TRACKING_IMAGE}:${TAG}" + # command: /bin/bash -c "ros2 launch tracking tracking.launch.py" diff --git a/src/perception/semantic_segmentation/CMakeLists.txt b/src/perception/semantic_segmentation/CMakeLists.txt index 01396d95..514eaf47 100644 --- a/src/perception/semantic_segmentation/CMakeLists.txt +++ b/src/perception/semantic_segmentation/CMakeLists.txt @@ -1,14 +1,57 @@ cmake_minimum_required(VERSION 3.8) -project(semantic_segmentation) +project(semantic_segmentation LANGUAGES CXX CUDA) +set(PADDLE_LIB "/home/bolty/ament_ws/src/semantic_segmentation/src/paddle_inference_cuda120_build/paddle_inference_install_dir") # Set this path as per your setup + +option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON) +option(WITH_GPU "Compile demo with GPU/CPU, default use CPU." ON) +option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static." ON) +option(USE_TENSORRT "Compile demo with TensorRT." ON) +option(WITH_ROCM "Compile demo with rocm." OFF) + +# Compiler options if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") add_compile_options(-Wall -Wextra -Wpedantic) endif() -# find dependencies +# Default to C++14 +if(NOT CMAKE_CXX_STANDARD) + set(CMAKE_CXX_STANDARD 14) +endif() + +# Platform-independent settings +include_directories("${PADDLE_LIB}/") +set(PADDLE_LIB_THIRD_PARTY_PATH "${PADDLE_LIB}/third_party/install/") +include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/include ${PADDLE_LIB_THIRD_PARTY_PATH}glog/include ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/include ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/include ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/include ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/include ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/include) +link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/lib ${PADDLE_LIB_THIRD_PARTY_PATH}glog/lib ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/lib ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/lib ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/lib ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/lib ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/lib ${PADDLE_LIB}/paddle/lib) + +# Find packages +find_package(rclcpp REQUIRED) +find_package(std_msgs REQUIRED) +find_package(sensor_msgs REQUIRED) +find_package(geometry_msgs REQUIRED) +find_package(image_transport REQUIRED) +find_package(CUDA REQUIRED) find_package(ament_cmake REQUIRED) -# uncomment the following section in order to fill in -# further dependencies manually. -# find_package( REQUIRED) +find_package(yaml-cpp REQUIRED) + +# Include directories +include_directories(include ${rclcpp_INCLUDE_DIRS} ${std_msgs_INCLUDE_DIRS} ${sensor_msgs_INCLUDE_DIRS} ${geometry_msgs_INCLUDE_DIRS} ${image_transport_INCLUDE_DIRS} ${CUDA_INCLUDE_DIRS} ${YAML_CPP_INCLUDE_DIRS} /usr/local/include) + +# Link directories +link_directories(/usr/local/lib ${YAML_CPP_LIBRARIES}) + +# Set additional dependencies +set(EXTRA_LIBS "-lrt -ldl -lpthread") +set(DEPS ${rclcpp_LIBRARIES} ${std_msgs_LIBRARIES} ${sensor_msgs_LIBRARIES} ${geometry_msgs_LIBRARIES} ${image_transport_LIBRARIES} ${CUDA_LIBRARIES} ${YAML_CPP_LIBRARIES} ${EXTRA_LIBS}) + +# Add your executable +add_executable(semantic_segmentation src/semantic_segmentation_node.cpp) +target_link_libraries(semantic_segmentation ${DEPS}) + +# Additional installation commands +install(DIRECTORY launch config resource DESTINATION share/${PROJECT_NAME}/) +install(TARGETS semantic_segmentation DESTINATION lib/${PROJECT_NAME}) +ament_target_dependencies(semantic_segmentation rclcpp std_msgs sensor_msgs geometry_msgs image_transport) ament_package() diff --git a/src/perception/semantic_segmentation/config/config.yaml b/src/perception/semantic_segmentation/config/config.yaml new file mode 100644 index 00000000..44a54fc1 --- /dev/null +++ b/src/perception/semantic_segmentation/config/config.yaml @@ -0,0 +1,3 @@ +lane_detection_node: + ros__parameters: + input_topic: "/CAM_FRONT/image_rect_compressed" \ No newline at end of file diff --git a/src/perception/semantic_segmentation/launch/semantic_segmentation.launch.py b/src/perception/semantic_segmentation/launch/semantic_segmentation.launch.py new file mode 100644 index 00000000..4fb1b34a --- /dev/null +++ b/src/perception/semantic_segmentation/launch/semantic_segmentation.launch.py @@ -0,0 +1,21 @@ +from launch import LaunchDescription +from launch_ros.actions import Node +from ament_index_python.packages import get_package_share_directory +import os + + +def generate_launch_description(): + config = os.path.join( + get_package_share_directory('semantic_segmentation'), + 'config', + 'config.yaml' + ) + + return LaunchDescription([ + Node( + package='semantic_segmentation', + executable='semantic_segmentation', + name='semantic_segmentation', + parameters=[config] + ) + ]) diff --git a/src/perception/semantic_segmentation/package.xml b/src/perception/semantic_segmentation/package.xml index f90d0c8c..25da5ca0 100644 --- a/src/perception/semantic_segmentation/package.xml +++ b/src/perception/semantic_segmentation/package.xml @@ -4,12 +4,21 @@ semantic_segmentation 0.0.0 TODO: Package description - bolty - TODO: License declaration + bolty + Apache-2.0 ament_cmake + ament_lint_auto + ament_lint_common + sensor_msgs + geometry_msgs + std_msgs + image_transport + rosidl_default_generators + rosidl_default_runtime + rosidl_interface_packages ament_cmake diff --git a/src/perception/semantic_segmentation/resource/deploy.yaml b/src/perception/semantic_segmentation/resource/deploy.yaml new file mode 100644 index 00000000..6d33e500 --- /dev/null +++ b/src/perception/semantic_segmentation/resource/deploy.yaml @@ -0,0 +1,12 @@ +Deploy: + input_shape: + - -1 + - 3 + - -1 + - -1 + model: model.pdmodel + output_dtype: int32 + output_op: argmax + params: model.pdiparams + transforms: + - type: Normalize diff --git a/src/perception/semantic_segmentation/resource/dynamic_shape.pbtxt b/src/perception/semantic_segmentation/resource/dynamic_shape.pbtxt new file mode 100644 index 00000000..09347321 --- /dev/null +++ b/src/perception/semantic_segmentation/resource/dynamic_shape.pbtxt @@ -0,0 +1,4836 @@ +shape_range_info { + name: "batch_norm2d_0.b_0" + min_shape: 32 + max_shape: 32 + opt_shape: 32 +} +shape_range_info { + name: "batch_norm2d_0.w_0" + min_shape: 32 + max_shape: 32 + opt_shape: 32 +} +shape_range_info { + name: "batch_norm2d_0.w_1" + min_shape: 32 + max_shape: 32 + opt_shape: 32 +} +shape_range_info { + name: "batch_norm2d_0.w_2" + min_shape: 32 + max_shape: 32 + opt_shape: 32 +} +shape_range_info { + name: "batch_norm2d_1.b_0" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_1.w_0" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_1.w_1" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_1.w_2" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_10.b_0" + min_shape: 32 + max_shape: 32 + opt_shape: 32 +} +shape_range_info { + name: "batch_norm2d_10.w_0" + min_shape: 32 + max_shape: 32 + opt_shape: 32 +} +shape_range_info { + name: "batch_norm2d_10.w_1" + min_shape: 32 + max_shape: 32 + opt_shape: 32 +} +shape_range_info { + name: "batch_norm2d_10.w_2" + min_shape: 32 + max_shape: 32 + opt_shape: 32 +} +shape_range_info { + name: "batch_norm2d_11.b_0" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_11.w_0" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_11.w_1" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_11.w_2" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_12.b_0" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_12.w_0" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_12.w_1" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_12.w_2" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_13.b_0" + min_shape: 128 + max_shape: 128 + opt_shape: 128 +} +shape_range_info { + name: "batch_norm2d_13.w_0" + min_shape: 128 + max_shape: 128 + opt_shape: 128 +} +shape_range_info { + name: "batch_norm2d_13.w_1" + min_shape: 128 + max_shape: 128 + opt_shape: 128 +} +shape_range_info { + name: "batch_norm2d_13.w_2" + min_shape: 128 + max_shape: 128 + opt_shape: 128 +} +shape_range_info { + name: "batch_norm2d_14.b_0" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_14.w_0" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_14.w_1" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_14.w_2" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_15.b_0" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_15.w_0" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_15.w_1" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_15.w_2" + min_shape: 64 + max_shape: 64 + opt_shape: 64 +} +shape_range_info { + name: "batch_norm2d_16.b_0" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_16.w_0" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_16.w_1" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_16.w_2" + min_shape: 256 + max_shape: 256 + opt_shape: 256 +} +shape_range_info { + name: "batch_norm2d_17.b_0" + min_shape: 128 + max_shape: 128 + opt_shape: 128 +} +shape_range_info { + name: "batch_norm2d_17.w_0" + min_shape: 128 + 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opt_shape: 64 + opt_shape: 128 +} +shape_range_info { + name: "sigmoid_2.tmp_0" + min_shape: 1 + min_shape: 1 + min_shape: 128 + min_shape: 256 + max_shape: 1 + max_shape: 1 + max_shape: 128 + max_shape: 256 + opt_shape: 1 + opt_shape: 1 + opt_shape: 128 + opt_shape: 256 +} +shape_range_info { + name: "tmp_0" + min_shape: 1 + min_shape: 128 + min_shape: 32 + min_shape: 64 + max_shape: 1 + max_shape: 128 + max_shape: 32 + max_shape: 64 + opt_shape: 1 + opt_shape: 128 + opt_shape: 32 + opt_shape: 64 +} +shape_range_info { + name: "tmp_1" + min_shape: 1 + min_shape: 128 + min_shape: 32 + min_shape: 64 + max_shape: 1 + max_shape: 128 + max_shape: 32 + max_shape: 64 + opt_shape: 1 + opt_shape: 128 + opt_shape: 32 + opt_shape: 64 +} +shape_range_info { + name: "tmp_10" + min_shape: 1 + min_shape: 64 + min_shape: 128 + min_shape: 256 + max_shape: 1 + max_shape: 64 + max_shape: 128 + max_shape: 256 + opt_shape: 1 + opt_shape: 64 + opt_shape: 128 + opt_shape: 256 +} +shape_range_info { + name: "tmp_11" + min_shape: 1 + min_shape: 1 + min_shape: 128 + min_shape: 256 + max_shape: 1 + max_shape: 1 + max_shape: 128 + max_shape: 256 + opt_shape: 1 + opt_shape: 1 + opt_shape: 128 + opt_shape: 256 +} +shape_range_info { + name: "tmp_12" + min_shape: 1 + min_shape: 64 + min_shape: 128 + min_shape: 256 + max_shape: 1 + max_shape: 64 + max_shape: 128 + max_shape: 256 + opt_shape: 1 + opt_shape: 64 + opt_shape: 128 + opt_shape: 256 +} +shape_range_info { + name: "tmp_13" + min_shape: 1 + min_shape: 64 + min_shape: 128 + min_shape: 256 + max_shape: 1 + max_shape: 64 + max_shape: 128 + max_shape: 256 + opt_shape: 1 + opt_shape: 64 + opt_shape: 128 + opt_shape: 256 +} +shape_range_info { + name: "tmp_2" + min_shape: 1 + min_shape: 128 + min_shape: 32 + min_shape: 64 + max_shape: 1 + max_shape: 128 + max_shape: 32 + max_shape: 64 + opt_shape: 1 + opt_shape: 128 + opt_shape: 32 + opt_shape: 64 +} +shape_range_info { + name: "tmp_3" + min_shape: 1 + min_shape: 1 + min_shape: 32 + min_shape: 64 + max_shape: 1 + max_shape: 1 + max_shape: 32 + max_shape: 64 + opt_shape: 1 + opt_shape: 1 + opt_shape: 32 + opt_shape: 64 +} +shape_range_info { + name: "tmp_4" + min_shape: 1 + min_shape: 128 + min_shape: 32 + min_shape: 64 + max_shape: 1 + max_shape: 128 + max_shape: 32 + max_shape: 64 + opt_shape: 1 + opt_shape: 128 + opt_shape: 32 + opt_shape: 64 +} +shape_range_info { + name: "tmp_5" + min_shape: 1 + min_shape: 128 + min_shape: 32 + min_shape: 64 + max_shape: 1 + max_shape: 128 + max_shape: 32 + max_shape: 64 + opt_shape: 1 + opt_shape: 128 + opt_shape: 32 + opt_shape: 64 +} +shape_range_info { + name: "tmp_6" + min_shape: 1 + min_shape: 128 + min_shape: 64 + min_shape: 128 + max_shape: 1 + max_shape: 128 + max_shape: 64 + max_shape: 128 + opt_shape: 1 + opt_shape: 128 + opt_shape: 64 + opt_shape: 128 +} +shape_range_info { + name: "tmp_7" + min_shape: 1 + min_shape: 1 + min_shape: 64 + min_shape: 128 + max_shape: 1 + max_shape: 1 + max_shape: 64 + max_shape: 128 + opt_shape: 1 + opt_shape: 1 + opt_shape: 64 + opt_shape: 128 +} +shape_range_info { + name: "tmp_8" + min_shape: 1 + min_shape: 128 + min_shape: 64 + min_shape: 128 + max_shape: 1 + max_shape: 128 + max_shape: 64 + max_shape: 128 + opt_shape: 1 + opt_shape: 128 + opt_shape: 64 + opt_shape: 128 +} +shape_range_info { + name: "tmp_9" + min_shape: 1 + min_shape: 128 + min_shape: 64 + min_shape: 128 + max_shape: 1 + max_shape: 128 + max_shape: 64 + max_shape: 128 + opt_shape: 1 + opt_shape: 128 + opt_shape: 64 + opt_shape: 128 +} +shape_range_info { + name: "uafm__sp_atten_0.w_0" + min_shape: 1 + max_shape: 1 + opt_shape: 1 +} +shape_range_info { + name: "uafm__sp_atten_1.w_0" + min_shape: 1 + max_shape: 1 + opt_shape: 1 +} +shape_range_info { + name: "uafm__sp_atten_2.w_0" + min_shape: 1 + max_shape: 1 + opt_shape: 1 +} +shape_range_info { + name: "x" + min_shape: 1 + min_shape: 3 + min_shape: 1024 + min_shape: 2048 + max_shape: 1 + max_shape: 3 + max_shape: 1024 + max_shape: 2048 + opt_shape: 1 + opt_shape: 3 + opt_shape: 1024 + opt_shape: 2048 +} diff --git a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp new file mode 100644 index 00000000..aa8b96ef --- /dev/null +++ b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp @@ -0,0 +1,82 @@ +#include +#include +#include +#include + +#include "paddle/include/paddle_inference_api.h" +#include "yaml-cpp/yaml.h" + +#include "rclcpp/rclcpp.hpp" +#include "std_msgs/msg/string.hpp" + +using namespace std::chrono_literals; + +std::string model_path = "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"; +std::string resource_path = "/home/bolty/ament_ws/src/semantic_segmentation/resource/"; + + + +typedef struct YamlConfig { + std::string model_file; + std::string params_file; + bool is_normalize; + bool is_resize; + int resize_width; + int resize_height; +}YamlConfig; + +YamlConfig load_yaml(const std::string& yaml_path) { + YAML::Node node = YAML::LoadFile(yaml_path); + std::string model_file = node["Deploy"]["model"].as(); + std::string params_file = node["Deploy"]["params"].as(); + YamlConfig yaml_config = {model_file, params_file}; + if (node["Deploy"]["transforms"]) { + const YAML::Node& transforms = node["Deploy"]["transforms"]; + for (size_t i = 0; i < transforms.size(); i++) { + if (transforms[i]["type"].as() == "Normalize") { + yaml_config.is_normalize = true; + } else if (transforms[i]["type"].as() == "Resize") { + yaml_config.is_resize = true; + const YAML::Node& target_size = transforms[i]["target_size"]; + yaml_config.resize_width = target_size[0].as(); + yaml_config.resize_height = target_size[1].as(); + } + } + } + return yaml_config; +} + +/* This example creates a subclass of Node and uses std::bind() to register a + * member function as a callback from the timer. */ + +class SemanticSegmentationNode : public rclcpp::Node { + public: + SemanticSegmentationNode() : Node("semantic_segmentation_node"), count_(0) { + publisher_ = this->create_publisher("topic", 10); + timer_ = this->create_wall_timer(500ms, std::bind(&SemanticSegmentationNode::timer_callback, this)); + YamlConfig yaml_config = load_yaml(resource_path + "deploy.yaml"); + // Print out the yaml config + RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config.model_file.c_str()); + RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config.params_file.c_str()); + RCLCPP_INFO(this->get_logger(), "is_normalize: %d", yaml_config.is_normalize); + RCLCPP_INFO(this->get_logger(), "is_resize: %d", yaml_config.is_resize); + } + + private: + void timer_callback() { + auto message = std_msgs::msg::String(); + message.data = "Hello, world!! " + std::to_string(count_++); + RCLCPP_INFO(this->get_logger(), "Publishing: '%s'", message.data.c_str()); + publisher_->publish(message); + } + rclcpp::TimerBase::SharedPtr timer_; + rclcpp::Publisher::SharedPtr publisher_; + size_t count_; +}; + +int main(int argc, char* argv[]) { + rclcpp::init(argc, argv); + rclcpp::spin(std::make_shared()); + rclcpp::shutdown(); + return 0; +} \ No newline at end of file diff --git a/watod-config.sh b/watod-config.sh index 637c1624..f7f713bf 100755 --- a/watod-config.sh +++ b/watod-config.sh @@ -12,7 +12,7 @@ ## - simulation : starts simulation ## - samples : starts sample ROS2 pubsub nodes -# ACTIVE_MODULES="" +ACTIVE_MODULES="perception" ############################## OPTIONAL CONFIGURATIONS ############################## ## Name to append to docker containers. DEFAULT = "" From 304e0f02c6f7691e8416d462022aa23b72b2ffb9 Mon Sep 17 00:00:00 2001 From: Justin Leung Date: Sun, 18 Feb 2024 10:56:26 +0000 Subject: [PATCH 02/12] Add linking with shared library --- .../semantic_segmentation/CMakeLists.txt | 23 +++++- .../src/semantic_segmentation_node.cpp | 81 ++++++++++++++++++- 2 files changed, 98 insertions(+), 6 deletions(-) diff --git a/src/perception/semantic_segmentation/CMakeLists.txt b/src/perception/semantic_segmentation/CMakeLists.txt index 514eaf47..9b2b0404 100644 --- a/src/perception/semantic_segmentation/CMakeLists.txt +++ b/src/perception/semantic_segmentation/CMakeLists.txt @@ -23,6 +23,8 @@ endif() include_directories("${PADDLE_LIB}/") set(PADDLE_LIB_THIRD_PARTY_PATH "${PADDLE_LIB}/third_party/install/") include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/include ${PADDLE_LIB_THIRD_PARTY_PATH}glog/include ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/include ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/include ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/include ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/include ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/include) + + link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/lib ${PADDLE_LIB_THIRD_PARTY_PATH}glog/lib ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/lib ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/lib ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/lib ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/lib ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/lib ${PADDLE_LIB}/paddle/lib) # Find packages @@ -36,14 +38,31 @@ find_package(ament_cmake REQUIRED) find_package(yaml-cpp REQUIRED) # Include directories -include_directories(include ${rclcpp_INCLUDE_DIRS} ${std_msgs_INCLUDE_DIRS} ${sensor_msgs_INCLUDE_DIRS} ${geometry_msgs_INCLUDE_DIRS} ${image_transport_INCLUDE_DIRS} ${CUDA_INCLUDE_DIRS} ${YAML_CPP_INCLUDE_DIRS} /usr/local/include) +include_directories(include + ${rclcpp_INCLUDE_DIRS} + ${std_msgs_INCLUDE_DIRS} + ${sensor_msgs_INCLUDE_DIRS} + ${geometry_msgs_INCLUDE_DIRS} + ${image_transport_INCLUDE_DIRS} + ${CUDA_INCLUDE_DIRS} + ${YAML_CPP_INCLUDE_DIRS} + /usr/local/include + ${PADDLE_LIB}/paddle/include + ${PADDLE_LIB}/third_party/install/mkldnn/include + ) + # Link directories link_directories(/usr/local/lib ${YAML_CPP_LIBRARIES}) + # Set additional dependencies set(EXTRA_LIBS "-lrt -ldl -lpthread") -set(DEPS ${rclcpp_LIBRARIES} ${std_msgs_LIBRARIES} ${sensor_msgs_LIBRARIES} ${geometry_msgs_LIBRARIES} ${image_transport_LIBRARIES} ${CUDA_LIBRARIES} ${YAML_CPP_LIBRARIES} ${EXTRA_LIBS}) +set(DEPS ${rclcpp_LIBRARIES} ${std_msgs_LIBRARIES} ${sensor_msgs_LIBRARIES} ${geometry_msgs_LIBRARIES} ${image_transport_LIBRARIES} ${CUDA_LIBRARIES} ${YAML_CPP_LIBRARIES} ${EXTRA_LIBS} +${PADDLE_LIB}/paddle/lib/libpaddle_inference.so +${PADDLE_LIB}/third_party/install/mkldnn/lib/libdnnl.so.3 +${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5.so +) # Add your executable add_executable(semantic_segmentation src/semantic_segmentation_node.cpp) diff --git a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp index aa8b96ef..dc7c572d 100644 --- a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp +++ b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp @@ -14,8 +14,6 @@ using namespace std::chrono_literals; std::string model_path = "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"; std::string resource_path = "/home/bolty/ament_ws/src/semantic_segmentation/resource/"; - - typedef struct YamlConfig { std::string model_file; std::string params_file; @@ -23,7 +21,7 @@ typedef struct YamlConfig { bool is_resize; int resize_width; int resize_height; -}YamlConfig; +} YamlConfig; YamlConfig load_yaml(const std::string& yaml_path) { YAML::Node node = YAML::LoadFile(yaml_path); @@ -51,15 +49,89 @@ YamlConfig load_yaml(const std::string& yaml_path) { class SemanticSegmentationNode : public rclcpp::Node { public: + + bool FLAGS_use_mkldnn = true; + bool FLAGS_use_trt = true; + std::string FLAGS_trt_precision = "fp32"; + bool FLAGS_use_trt_dynamic_shape = true; + std::string FLAGS_dynamic_shape_path = resource_path + "dynamic_shape.pbtxt"; + std::string FLAGS_devices = "GPU"; + + std::shared_ptr create_predictor(const YamlConfig& yaml_config) { + paddle_infer::Config infer_config; + infer_config.SetModel(model_path + "/" + yaml_config.model_file, + model_path + "/" + yaml_config.params_file); + infer_config.EnableMemoryOptim(); + + if (FLAGS_devices == "CPU") { + RCLCPP_INFO(this->get_logger(), "Use CPU"); + if (FLAGS_use_mkldnn) { + RCLCPP_INFO(this->get_logger(), "Use MKLDNN"); + infer_config.EnableMKLDNN(); + infer_config.SetCpuMathLibraryNumThreads(5); + } + } else if (FLAGS_devices == "GPU") { + RCLCPP_INFO(this->get_logger(), "Use GPU"); + infer_config.EnableUseGpu(100, 0); + + // TRT config + if (FLAGS_use_trt) { + // LOG(INFO) << "Use TRT"; + // LOG(INFO) << "trt_precision:" << FLAGS_trt_precision; + RCLCPP_INFO(this->get_logger(), "trt_precision: %s", FLAGS_trt_precision.c_str()); + + // TRT precision + if (FLAGS_trt_precision == "fp32") { + infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kFloat32, + false, false); + } else if (FLAGS_trt_precision == "fp16") { + infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kHalf, + false, false); + } else if (FLAGS_trt_precision == "int8") { + infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kInt8, + false, false); + } else { + RCLCPP_ERROR(this->get_logger(), "The trt_precision should be fp32, fp16 or int8."); + } + + // TRT dynamic shape + if (FLAGS_use_trt_dynamic_shape) { + RCLCPP_INFO(this->get_logger(), "Enable TRT dynamic shape"); + RCLCPP_INFO(this->get_logger(), "dynamic_shape_path: %s", + FLAGS_dynamic_shape_path.c_str()); + if (FLAGS_dynamic_shape_path.empty()) { + std::map> min_input_shape = {{"image", {1, 3, 112, 112}}}; + std::map> max_input_shape = { + {"image", {1, 3, 1024, 2048}}}; + std::map> opt_input_shape = { + {"image", {1, 3, 512, 1024}}}; + infer_config.SetTRTDynamicShapeInfo(min_input_shape, max_input_shape, opt_input_shape); + } else { + infer_config.EnableTunedTensorRtDynamicShape(FLAGS_dynamic_shape_path, true); + } + } + } + } else { + RCLCPP_ERROR(this->get_logger(), "The devices should be GPU or CPU"); + } + + auto predictor = paddle_infer::CreatePredictor(infer_config); + return predictor; + } + SemanticSegmentationNode() : Node("semantic_segmentation_node"), count_(0) { publisher_ = this->create_publisher("topic", 10); - timer_ = this->create_wall_timer(500ms, std::bind(&SemanticSegmentationNode::timer_callback, this)); + timer_ = + this->create_wall_timer(500ms, std::bind(&SemanticSegmentationNode::timer_callback, this)); YamlConfig yaml_config = load_yaml(resource_path + "deploy.yaml"); // Print out the yaml config RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config.model_file.c_str()); RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config.params_file.c_str()); RCLCPP_INFO(this->get_logger(), "is_normalize: %d", yaml_config.is_normalize); RCLCPP_INFO(this->get_logger(), "is_resize: %d", yaml_config.is_resize); + + // Create the paddle predictor + predictor_ = create_predictor(yaml_config); } private: @@ -72,6 +144,7 @@ class SemanticSegmentationNode : public rclcpp::Node { rclcpp::TimerBase::SharedPtr timer_; rclcpp::Publisher::SharedPtr publisher_; size_t count_; + std::shared_ptr predictor_; }; int main(int argc, char* argv[]) { From 2de6263ca775f62285700c80b86d202848cc9161 Mon Sep 17 00:00:00 2001 From: Justin Leung Date: Sun, 18 Feb 2024 21:16:13 +0000 Subject: [PATCH 03/12] Add working model loading --- .../semantic_segmentation.Dockerfile | 8 ++++++-- src/perception/semantic_segmentation/CMakeLists.txt | 12 +++++++++++- 2 files changed, 17 insertions(+), 3 deletions(-) diff --git a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile index d0a777ba..ef99a744 100644 --- a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile +++ b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile @@ -7,8 +7,6 @@ FROM ${PADDLE_INFERENCE_BUILD_URL} as PADDLE_INFERENCE_BUILD ################################ Source ################################ FROM ${BASE_BUILD_IMAGE} as source -# install tensorrt -RUN apt update && apt install -y tensorrt WORKDIR ${AMENT_WS}/src @@ -49,6 +47,8 @@ RUN apt-get -qq autoremove -y && apt-get -qq autoclean && apt-get -qq clean && \ ################################ Build ################################ FROM dependencies as build +# install tensorrt +RUN apt update && apt install -y tensorrt # Build ROS2 packages WORKDIR ${AMENT_WS} @@ -58,6 +58,10 @@ RUN . /opt/ros/$ROS_DISTRO/setup.sh && \ # Entrypoint will run before any CMD on launch. Sources ~/opt//setup.bash and ~/ament_ws/install/setup.bash COPY docker/wato_ros_entrypoint.sh ${AMENT_WS}/wato_ros_entrypoint.sh + +# Add /home/bolty/ament_ws/install/semantic_segmentation/lib/semantic_segmentation to LD_LIBRARY_PATH +RUN export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/ +# /home/bolty/ament_ws/install/semantic_segmentation/lib/semantic_segmentation/ ENTRYPOINT ["./wato_ros_entrypoint.sh"] # ################################ Prod ################################ diff --git a/src/perception/semantic_segmentation/CMakeLists.txt b/src/perception/semantic_segmentation/CMakeLists.txt index 9b2b0404..a2d71b99 100644 --- a/src/perception/semantic_segmentation/CMakeLists.txt +++ b/src/perception/semantic_segmentation/CMakeLists.txt @@ -24,7 +24,6 @@ include_directories("${PADDLE_LIB}/") set(PADDLE_LIB_THIRD_PARTY_PATH "${PADDLE_LIB}/third_party/install/") include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/include ${PADDLE_LIB_THIRD_PARTY_PATH}glog/include ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/include ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/include ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/include ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/include ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/include) - link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/lib ${PADDLE_LIB_THIRD_PARTY_PATH}glog/lib ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/lib ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/lib ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/lib ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/lib ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/lib ${PADDLE_LIB}/paddle/lib) # Find packages @@ -60,8 +59,11 @@ link_directories(/usr/local/lib ${YAML_CPP_LIBRARIES}) set(EXTRA_LIBS "-lrt -ldl -lpthread") set(DEPS ${rclcpp_LIBRARIES} ${std_msgs_LIBRARIES} ${sensor_msgs_LIBRARIES} ${geometry_msgs_LIBRARIES} ${image_transport_LIBRARIES} ${CUDA_LIBRARIES} ${YAML_CPP_LIBRARIES} ${EXTRA_LIBS} ${PADDLE_LIB}/paddle/lib/libpaddle_inference.so +${PADDLE_LIB}/paddle/lib/libphi.so +${PADDLE_LIB}/paddle/lib/libcommon.so ${PADDLE_LIB}/third_party/install/mkldnn/lib/libdnnl.so.3 ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5.so +${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel.so ) # Add your executable @@ -71,6 +73,14 @@ target_link_libraries(semantic_segmentation ${DEPS}) # Additional installation commands install(DIRECTORY launch config resource DESTINATION share/${PROJECT_NAME}/) install(TARGETS semantic_segmentation DESTINATION lib/${PROJECT_NAME}) +# Install shared libraries +install(FILES ${PADDLE_LIB}/paddle/lib/libpaddle_inference.so + ${PADDLE_LIB}/paddle/lib/libphi.so + ${PADDLE_LIB}/paddle/lib/libcommon.so + ${PADDLE_LIB}/third_party/install/mkldnn/lib/libdnnl.so.3 + ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5.so + ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel.so + DESTINATION /usr/local/lib) ament_target_dependencies(semantic_segmentation rclcpp std_msgs sensor_msgs geometry_msgs image_transport) ament_package() From f5cc71ea52d33ba1bfce9e71c8ca542f31962774 Mon Sep 17 00:00:00 2001 From: Justin Leung Date: Sun, 18 Feb 2024 21:19:51 +0000 Subject: [PATCH 04/12] Try clang formatter --- .../semantic_segmentation.Dockerfile | 7 +- .../semantic_segmentation/CMakeLists.txt | 12 +- .../semantic_segmentation/package.xml | 2 + .../src/semantic_segmentation_node.cpp | 124 +++++++++++++++++- watod-config.sh | 2 +- 5 files changed, 136 insertions(+), 11 deletions(-) diff --git a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile index ef99a744..1ec7c7df 100644 --- a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile +++ b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile @@ -31,6 +31,11 @@ RUN apt-get -qq update && rosdep update && \ ################################# Dependencies ################################ FROM ${BASE_BUILD_IMAGE} as dependencies +# install tensorrt +RUN apt update && apt install -y tensorrt + +RUN apt install -y ros-humble-cv-bridge libopencv-dev + # Install Rosdep requirements COPY --from=source /tmp/colcon_install_list /tmp/colcon_install_list RUN apt-fast install -qq -y --no-install-recommends $(cat /tmp/colcon_install_list) @@ -47,8 +52,6 @@ RUN apt-get -qq autoremove -y && apt-get -qq autoclean && apt-get -qq clean && \ ################################ Build ################################ FROM dependencies as build -# install tensorrt -RUN apt update && apt install -y tensorrt # Build ROS2 packages WORKDIR ${AMENT_WS} diff --git a/src/perception/semantic_segmentation/CMakeLists.txt b/src/perception/semantic_segmentation/CMakeLists.txt index a2d71b99..8934368b 100644 --- a/src/perception/semantic_segmentation/CMakeLists.txt +++ b/src/perception/semantic_segmentation/CMakeLists.txt @@ -32,6 +32,8 @@ find_package(std_msgs REQUIRED) find_package(sensor_msgs REQUIRED) find_package(geometry_msgs REQUIRED) find_package(image_transport REQUIRED) +find_package(OpenCV REQUIRED) +find_package(cv_bridge REQUIRED) find_package(CUDA REQUIRED) find_package(ament_cmake REQUIRED) find_package(yaml-cpp REQUIRED) @@ -82,5 +84,13 @@ install(FILES ${PADDLE_LIB}/paddle/lib/libpaddle_inference.so ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel.so DESTINATION /usr/local/lib) -ament_target_dependencies(semantic_segmentation rclcpp std_msgs sensor_msgs geometry_msgs image_transport) +ament_target_dependencies(semantic_segmentation + rclcpp + std_msgs + sensor_msgs + cv_bridge + geometry_msgs + image_transport + OpenCV +) ament_package() diff --git a/src/perception/semantic_segmentation/package.xml b/src/perception/semantic_segmentation/package.xml index 25da5ca0..660c0902 100644 --- a/src/perception/semantic_segmentation/package.xml +++ b/src/perception/semantic_segmentation/package.xml @@ -14,6 +14,8 @@ sensor_msgs geometry_msgs std_msgs + OpenCV + cv_bridge image_transport rosidl_default_generators diff --git a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp index dc7c572d..bb8057a5 100644 --- a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp +++ b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp @@ -1,11 +1,15 @@ +#include #include #include #include +#include #include +#include #include "paddle/include/paddle_inference_api.h" #include "yaml-cpp/yaml.h" +#include #include "rclcpp/rclcpp.hpp" #include "std_msgs/msg/string.hpp" @@ -49,7 +53,6 @@ YamlConfig load_yaml(const std::string& yaml_path) { class SemanticSegmentationNode : public rclcpp::Node { public: - bool FLAGS_use_mkldnn = true; bool FLAGS_use_trt = true; std::string FLAGS_trt_precision = "fp32"; @@ -119,19 +122,53 @@ class SemanticSegmentationNode : public rclcpp::Node { return predictor; } + void hwc_img_2_chw_data(const cv::Mat& hwc_img, float* data) { + int rows = hwc_img.rows; + int cols = hwc_img.cols; + int chs = hwc_img.channels(); + for (int i = 0; i < chs; ++i) { + cv::extractChannel(hwc_img, cv::Mat(rows, cols, CV_32FC1, data + i * rows * cols), i); + } + } + + void process_image(cv::Mat& img, const YamlConfig& yaml_config) { + // cv::Mat img = cv::imread(FLAGS_img_path, cv::IMREAD_COLOR); + cv::cvtColor(img, img, cv::COLOR_BGR2RGB); + if (yaml_config.is_resize) { + cv::resize(img, img, cv::Size(yaml_config.resize_width, yaml_config.resize_height)); + } + if (yaml_config.is_normalize) { + img.convertTo(img, CV_32F, 1.0 / 255, 0); + img = (img - 0.5) / 0.5; + } + } + SemanticSegmentationNode() : Node("semantic_segmentation_node"), count_(0) { + // Get the image topic parameter from the launch file) + std::string image_topic = this->declare_parameter("input_topic", "/camera/right/image_color"); + + RCLCPP_INFO(this->get_logger(), "subscribing to image_topic: %s", image_topic.c_str()); + publisher_ = this->create_publisher("topic", 10); timer_ = this->create_wall_timer(500ms, std::bind(&SemanticSegmentationNode::timer_callback, this)); - YamlConfig yaml_config = load_yaml(resource_path + "deploy.yaml"); + yaml_config_ = load_yaml(resource_path + "deploy.yaml"); // Print out the yaml config - RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config.model_file.c_str()); - RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config.params_file.c_str()); - RCLCPP_INFO(this->get_logger(), "is_normalize: %d", yaml_config.is_normalize); - RCLCPP_INFO(this->get_logger(), "is_resize: %d", yaml_config.is_resize); + RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config_.model_file.c_str()); + RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config_.params_file.c_str()); + RCLCPP_INFO(this->get_logger(), "is_normalize: %d", yaml_config_.is_normalize); + RCLCPP_INFO(this->get_logger(), "is_resize: %d", yaml_config_.is_resize); // Create the paddle predictor - predictor_ = create_predictor(yaml_config); + predictor_ = create_predictor(yaml_config_); + + // Subscribe to the image topic + subscription_ = this->create_subscription( + image_topic, 10, + std::bind(&SemanticSegmentationNode::image_callback, this, std::placeholders::_1)); + + image_publisher_ = + this->create_publisher("semantic_segmentation_image", 10); } private: @@ -141,10 +178,83 @@ class SemanticSegmentationNode : public rclcpp::Node { RCLCPP_INFO(this->get_logger(), "Publishing: '%s'", message.data.c_str()); publisher_->publish(message); } + + void image_callback(const sensor_msgs::msg::Image::SharedPtr msg) { + RCLCPP_INFO(this->get_logger(), "Received image"); + cv::Mat img; + + // Convert msg to a cv mat + try { + img = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8)->image; + } catch (cv_bridge::Exception& e) { + RCLCPP_ERROR(this->get_logger(), "Could not convert from '%s' to 'bgr8'.", + msg->encoding.c_str()); + return; + } + + // Process the image according to yaml config + process_image(img, yaml_config_); + + int rows = img.rows; + int cols = img.cols; + int chs = img.channels(); + std::vector input_data(1 * chs * rows * cols, 0.0f); + hwc_img_2_chw_data(img, input_data.data()); + + // Set input + auto input_names = predictor_->GetInputNames(); + auto input_t = predictor_->GetInputHandle(input_names[0]); + std::vector input_shape = {1, chs, rows, cols}; + input_t->Reshape(input_shape); + input_t->CopyFromCpu(input_data.data()); + + // Start timing + auto start = std::chrono::high_resolution_clock::now(); + + // Run + predictor_->Run(); + + // Stop timing + auto end = std::chrono::high_resolution_clock::now(); + + // Calculate elapsed time + std::chrono::duration elapsed = end - start; + RCLCPP_INFO(this->get_logger(), "Inference time: %f ms", elapsed.count()); + + // Get output + auto output_names = predictor_->GetOutputNames(); + auto output_t = predictor_->GetOutputHandle(output_names[0]); + std::vector output_shape = output_t->shape(); + int out_num = + std::accumulate(output_shape.begin(), output_shape.end(), 1, std::multiplies()); + std::vector out_data(out_num); + output_t->CopyToCpu(out_data.data()); + + // Get pseudo image + std::vector out_data_u8(out_num); + for (int i = 0; i < out_num; i++) { + out_data_u8[i] = static_cast(out_data[i]); + } + cv::Mat out_gray_img(output_shape[1], output_shape[2], CV_8UC1, out_data_u8.data()); + cv::Mat out_eq_img; + cv::equalizeHist(out_gray_img, out_eq_img); + cv::imwrite("out_img.jpg", out_eq_img); + + // Publish out_eq_img to a topic + sensor_msgs::msg::Image::SharedPtr out_img_msg = + cv_bridge::CvImage(std_msgs::msg::Header(), "mono8", out_eq_img).toImageMsg(); + + image_publisher_->publish(*out_img_msg); + + RCLCPP_INFO(this->get_logger(), "Finish, the result is saved in out_img.jpg"); + } rclcpp::TimerBase::SharedPtr timer_; rclcpp::Publisher::SharedPtr publisher_; + rclcpp::Subscription::SharedPtr subscription_; + rclcpp::Publisher::SharedPtr image_publisher_; size_t count_; std::shared_ptr predictor_; + YamlConfig yaml_config_; }; int main(int argc, char* argv[]) { diff --git a/watod-config.sh b/watod-config.sh index f7f713bf..4740ee69 100755 --- a/watod-config.sh +++ b/watod-config.sh @@ -12,7 +12,7 @@ ## - simulation : starts simulation ## - samples : starts sample ROS2 pubsub nodes -ACTIVE_MODULES="perception" +ACTIVE_MODULES="perception infrastructure" ############################## OPTIONAL CONFIGURATIONS ############################## ## Name to append to docker containers. DEFAULT = "" From 90e8be006d5175a4aaa7898498737d914f2542c5 Mon Sep 17 00:00:00 2001 From: Justin Leung Date: Thu, 29 Feb 2024 09:35:49 +0000 Subject: [PATCH 05/12] Add colormap and labels --- .../semantic_segmentation.Dockerfile | 6 +- modules/docker-compose.perception.yaml | 8 + .../semantic_segmentation/config/config.yaml | 4 +- .../resource/cityscapes_demo.png | Bin 0 -> 2676718 bytes .../src/semantic_segmentation_node.cpp | 183 +++++++++++++++--- watod-config.sh | 7 +- 6 files changed, 176 insertions(+), 32 deletions(-) create mode 100644 src/perception/semantic_segmentation/resource/cityscapes_demo.png diff --git a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile index 1ec7c7df..9c49d354 100644 --- a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile +++ b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile @@ -34,7 +34,7 @@ FROM ${BASE_BUILD_IMAGE} as dependencies # install tensorrt RUN apt update && apt install -y tensorrt -RUN apt install -y ros-humble-cv-bridge libopencv-dev +RUN apt update && apt install -y ros-humble-cv-bridge libopencv-dev # Install Rosdep requirements COPY --from=source /tmp/colcon_install_list /tmp/colcon_install_list @@ -63,7 +63,9 @@ RUN . /opt/ros/$ROS_DISTRO/setup.sh && \ COPY docker/wato_ros_entrypoint.sh ${AMENT_WS}/wato_ros_entrypoint.sh # Add /home/bolty/ament_ws/install/semantic_segmentation/lib/semantic_segmentation to LD_LIBRARY_PATH -RUN export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/ +ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/ +# Add /usr/local/lib to LD_LIBRARY_PATH +ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib # /home/bolty/ament_ws/install/semantic_segmentation/lib/semantic_segmentation/ ENTRYPOINT ["./wato_ros_entrypoint.sh"] diff --git a/modules/docker-compose.perception.yaml b/modules/docker-compose.perception.yaml index af96e54b..b0f767d2 100644 --- a/modules/docker-compose.perception.yaml +++ b/modules/docker-compose.perception.yaml @@ -76,6 +76,14 @@ services: command: /bin/bash -c "ros2 launch semantic_segmentation semantic_segmentation.launch.py" volumes: - /mnt/wato-drive2/perception-weights/semantic_segmentation:/perception_models/semantic_segmentation + # add gpus all + deploy: + resources: + reservations: + devices: + - driver: nvidia + capabilities: [gpu] + count: 1 # lane_detection: # build: diff --git a/src/perception/semantic_segmentation/config/config.yaml b/src/perception/semantic_segmentation/config/config.yaml index 44a54fc1..96530f84 100644 --- a/src/perception/semantic_segmentation/config/config.yaml +++ b/src/perception/semantic_segmentation/config/config.yaml @@ -1,3 +1,3 @@ -lane_detection_node: +semantic_segmentation_node: ros__parameters: - input_topic: "/CAM_FRONT/image_rect_compressed" \ No newline at end of file + input_topic: 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zHy!r!5Q84{MM<_xrz^Uq8Ge1nD0w}zhotgoN#`Fu-{;9I(u|HjpQ zgL~{7ef^X>^+zm{Nff`u*Qxb?dHu;>KgUh~BTuzI$)$a>C+wedGVo`6;eS@IL6v{G z-9OLkm%#Ps`1*j>{;$1$*^~eI>kla$e)s;>@BM&K%d+49u>lnu%QYLbZ2h{%5qqN4 zK@yvktFfxZapTdu2;Cnu#Sh(sBNx_)L0#yrv8?fB5*X@f8?bvm3OT*HeMHe5$Jx0d z$sv+*uBV2s7@hfGO7hC=cf0?VZi(u7D$vwrP0^!VoL3GFKh#~5K||k#8&4=U^F|O1 zcrEVgJep~An7^=lAZe?8>&C8Wa43m?$-kzct#-{;_wAs$C9QW2X*UmFkKwpE1@idw zb)TLn1S8FZ>_tXExwu@CRtMczPBVrBW~gvDfGfgH1cqGv)p%3} zjn`~msj?6WL(+9VX$Ic>Vsn$|`>Zy_UgXw3R&`q1)MX)-f!}N2-}H9y^p!s>BWqisHBya$Tl`Gz(`eCw_`W)GR;V5EgQTzoMY%K=?T)| zRu)%f2B%td_mIwxxMGnNUp_mF29U5?ZkZX^i`<0mtwG|nU)NA8n)b;~Lmno5c)Hnm zV(_#48_S;mR2SVA>;M1&C3HntbYx+4WjbSWWnpw>05UK!H7zkREif`vF)}(eH##&j zD=;xSFfd{=D{BA%03~!qSaf7zbY(hiZ)9m^c>ppnF*PkQGA%GNR53C-H8(mmGAl4K WIxsL3Z #include #include +#include #include #include "paddle/include/paddle_inference_api.h" @@ -15,8 +16,26 @@ using namespace std::chrono_literals; +std::string resource_path = "/home/bolty/ament_ws/src/semantic_segmentation/resource"; std::string model_path = "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"; -std::string resource_path = "/home/bolty/ament_ws/src/semantic_segmentation/resource/"; +// 19 classes +std::unordered_map cityscapes_labels = { + {0, "road"}, {1, "sidewalk"}, {2, "building"}, {3, "wall"}, {4, "fence"}, + {5, "pole"}, {6, "traffic light"}, {7, "traffic sign"}, {8, "vegetation"}, {9, "terrain"}, + {10, "sky"}, {11, "person"}, {12, "rider"}, {13, "car"}, {14, "truck"}, + {15, "bus"}, {16, "train"}, {17, "motorcycle"}, {18, "bicycle"}}; + +std::unordered_map> cityscapes_label_colormap = { + {0, std::make_tuple(128, 64, 128)}, {1, std::make_tuple(244, 35, 232)}, + {2, std::make_tuple(70, 70, 70)}, {3, std::make_tuple(102, 102, 156)}, + {4, std::make_tuple(190, 153, 153)}, {5, std::make_tuple(153, 153, 153)}, + {6, std::make_tuple(250, 170, 30)}, {7, std::make_tuple(220, 220, 0)}, + {8, std::make_tuple(107, 142, 35)}, {9, std::make_tuple(152, 251, 152)}, + {10, std::make_tuple(70, 130, 180)}, {11, std::make_tuple(220, 20, 60)}, + {12, std::make_tuple(255, 0, 0)}, {13, std::make_tuple(0, 0, 142)}, + {14, std::make_tuple(0, 0, 70)}, {15, std::make_tuple(0, 60, 100)}, + {16, std::make_tuple(0, 80, 100)}, {17, std::make_tuple(0, 0, 230)}, + {18, std::make_tuple(119, 11, 32)}}; typedef struct YamlConfig { std::string model_file; @@ -57,7 +76,8 @@ class SemanticSegmentationNode : public rclcpp::Node { bool FLAGS_use_trt = true; std::string FLAGS_trt_precision = "fp32"; bool FLAGS_use_trt_dynamic_shape = true; - std::string FLAGS_dynamic_shape_path = resource_path + "dynamic_shape.pbtxt"; + std::string FLAGS_dynamic_shape_path = resource_path + "/dynamic_shape.pbtxt"; + std::string FLAGS_img_path = resource_path + "/cityscapes_demo.png"; std::string FLAGS_devices = "GPU"; std::shared_ptr create_predictor(const YamlConfig& yaml_config) { @@ -131,8 +151,105 @@ class SemanticSegmentationNode : public rclcpp::Node { } } + // Function to resize an image while maintaining aspect ratio + cv::Mat resizeImageAspectRatio(const cv::Mat& originalImage, int maxWidth, int maxHeight) { + int originalWidth = originalImage.cols; + int originalHeight = originalImage.rows; + double originalAspectRatio = (double)originalWidth / originalHeight; + + int newWidth, newHeight; + double maxAspectRatio = (double)maxWidth / maxHeight; + + if (originalAspectRatio > maxAspectRatio) { + // Width is the limiting factor + newWidth = maxWidth; + newHeight = static_cast(maxWidth / originalAspectRatio); + } else { + // Height is the limiting factor + newHeight = maxHeight; + newWidth = static_cast(maxHeight * originalAspectRatio); + } + + cv::Mat resizedImage; + cv::resize(originalImage, resizedImage, cv::Size(newWidth, newHeight)); + + return resizedImage; + } + + cv::Mat resizeWithPadding(const cv::Mat& originalImage, int targetWidth, int targetHeight) { + int originalWidth = originalImage.cols; + int originalHeight = originalImage.rows; + + double targetRatio = (double)targetWidth / targetHeight; + double originalRatio = (double)originalWidth / originalHeight; + + int newWidth, newHeight; + + if (originalRatio > targetRatio) { + // Original is wider. Fit to width and pad height. + newWidth = targetWidth; + newHeight = + static_cast(originalHeight * (static_cast(targetWidth) / originalWidth)); + } else { + // Original is taller. Fit to height and pad width. + newHeight = targetHeight; + newWidth = + static_cast(originalWidth * (static_cast(targetHeight) / originalHeight)); + } + + cv::Mat resizedImage; + cv::resize(originalImage, resizedImage, cv::Size(newWidth, newHeight)); + + int top = (targetHeight - newHeight) / 2; + int bottom = targetHeight - newHeight - top; + int left = (targetWidth - newWidth) / 2; + int right = targetWidth - newWidth - left; + + cv::Mat paddedImage; + cv::copyMakeBorder(resizedImage, paddedImage, top, bottom, left, right, cv::BORDER_CONSTANT, + cv::Scalar(0, 0, 0)); + + return paddedImage; + } + + cv::Mat resizeFromCenter(const cv::Mat& originalImage, int targetWidth, int targetHeight) { + int originalWidth = originalImage.cols; + int originalHeight = originalImage.rows; + + // Calculate the new height maintaining the aspect ratio + double targetRatio = (double)targetWidth / targetHeight; + int newHeight = static_cast(originalWidth / targetRatio); + + // Calculate the cropping area + int startY = (originalHeight - newHeight) / 2; + + // Crop the image from the center + cv::Rect roi(0, startY, originalWidth, newHeight); + cv::Mat croppedImage = originalImage(roi); + + // Resize the cropped image + cv::Mat resizedImage; + cv::resize(croppedImage, resizedImage, cv::Size(targetWidth, targetHeight)); + + return resizedImage; + } + void process_image(cv::Mat& img, const YamlConfig& yaml_config) { // cv::Mat img = cv::imread(FLAGS_img_path, cv::IMREAD_COLOR); + // img = resizeWithPadding(img, 2048, 1024); + img = resizeFromCenter(img, 2048, 1024); + cv::cvtColor(img, img, cv::COLOR_BGR2RGB); + if (yaml_config.is_resize) { + cv::resize(img, img, cv::Size(yaml_config.resize_width, yaml_config.resize_height)); + } + if (yaml_config.is_normalize) { + img.convertTo(img, CV_32F, 1.0 / 255, 0); + img = (img - 0.5) / 0.5; + } + } + + cv::Mat read_process_image(const YamlConfig& yaml_config) { + cv::Mat img = cv::imread(FLAGS_img_path, cv::IMREAD_COLOR); cv::cvtColor(img, img, cv::COLOR_BGR2RGB); if (yaml_config.is_resize) { cv::resize(img, img, cv::Size(yaml_config.resize_width, yaml_config.resize_height)); @@ -141,6 +258,7 @@ class SemanticSegmentationNode : public rclcpp::Node { img.convertTo(img, CV_32F, 1.0 / 255, 0); img = (img - 0.5) / 0.5; } + return img; } SemanticSegmentationNode() : Node("semantic_segmentation_node"), count_(0) { @@ -150,9 +268,7 @@ class SemanticSegmentationNode : public rclcpp::Node { RCLCPP_INFO(this->get_logger(), "subscribing to image_topic: %s", image_topic.c_str()); publisher_ = this->create_publisher("topic", 10); - timer_ = - this->create_wall_timer(500ms, std::bind(&SemanticSegmentationNode::timer_callback, this)); - yaml_config_ = load_yaml(resource_path + "deploy.yaml"); + yaml_config_ = load_yaml(resource_path + "/deploy.yaml"); // Print out the yaml config RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config_.model_file.c_str()); RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config_.params_file.c_str()); @@ -172,20 +288,16 @@ class SemanticSegmentationNode : public rclcpp::Node { } private: - void timer_callback() { - auto message = std_msgs::msg::String(); - message.data = "Hello, world!! " + std::to_string(count_++); - RCLCPP_INFO(this->get_logger(), "Publishing: '%s'", message.data.c_str()); - publisher_->publish(message); - } - void image_callback(const sensor_msgs::msg::Image::SharedPtr msg) { RCLCPP_INFO(this->get_logger(), "Received image"); cv::Mat img; + cv::Mat original_img; // Convert msg to a cv mat + try { img = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8)->image; + original_img = img.clone(); } catch (cv_bridge::Exception& e) { RCLCPP_ERROR(this->get_logger(), "Could not convert from '%s' to 'bgr8'.", msg->encoding.c_str()); @@ -193,11 +305,15 @@ class SemanticSegmentationNode : public rclcpp::Node { } // Process the image according to yaml config + RCLCPP_INFO(this->get_logger(), "Image shape before process: %d, %d, %d", img.rows, img.cols, + img.channels()); process_image(img, yaml_config_); + // img = read_process_image(yaml_config_); int rows = img.rows; int cols = img.cols; int chs = img.channels(); + RCLCPP_INFO(this->get_logger(), "Image shape after process: %d, %d, %d", rows, cols, chs); std::vector input_data(1 * chs * rows * cols, 0.0f); hwc_img_2_chw_data(img, input_data.data()); @@ -219,7 +335,6 @@ class SemanticSegmentationNode : public rclcpp::Node { // Calculate elapsed time std::chrono::duration elapsed = end - start; - RCLCPP_INFO(this->get_logger(), "Inference time: %f ms", elapsed.count()); // Get output auto output_names = predictor_->GetOutputNames(); @@ -232,27 +347,45 @@ class SemanticSegmentationNode : public rclcpp::Node { // Get pseudo image std::vector out_data_u8(out_num); - for (int i = 0; i < out_num; i++) { - out_data_u8[i] = static_cast(out_data[i]); - } cv::Mat out_gray_img(output_shape[1], output_shape[2], CV_8UC1, out_data_u8.data()); - cv::Mat out_eq_img; - cv::equalizeHist(out_gray_img, out_eq_img); - cv::imwrite("out_img.jpg", out_eq_img); + cv::Mat colored_img; + // apply cityscapes_labels_colormap to img + cv::cvtColor(out_gray_img, colored_img, cv::COLOR_GRAY2BGR); + for (int i = 0; i < output_shape[1]; i++) { + for (int j = 0; j < output_shape[2]; j++) { + int label = out_data[i * output_shape[2] + j]; + if (cityscapes_labels.find(label) != cityscapes_labels.end()) { + auto [r,g,b] = cityscapes_label_colormap[label]; + colored_img.at(i, j) = cv::Vec3b(b, g, r); + } + } + } + - // Publish out_eq_img to a topic + if (count_ < 1000) { + // write the source image + cv::imwrite("/home/bolty/ament_ws/src/semantic_segmentation/test/src_img" + + std::to_string(count_) + ".jpg", + original_img); + // write the segmentation image + cv::imwrite("/home/bolty/ament_ws/src/semantic_segmentation/test/out_img" + + std::to_string(count_) + ".jpg", + colored_img); + RCLCPP_INFO(this->get_logger(), "Image written to /tmp/out_img%d.jpg, inference took %f ms", + count_, elapsed.count()); + count_++; + } + + // Publish color image to topic sensor_msgs::msg::Image::SharedPtr out_img_msg = - cv_bridge::CvImage(std_msgs::msg::Header(), "mono8", out_eq_img).toImageMsg(); + cv_bridge::CvImage(std_msgs::msg::Header(), "bgr8", colored_img).toImageMsg(); image_publisher_->publish(*out_img_msg); - - RCLCPP_INFO(this->get_logger(), "Finish, the result is saved in out_img.jpg"); } - rclcpp::TimerBase::SharedPtr timer_; rclcpp::Publisher::SharedPtr publisher_; rclcpp::Subscription::SharedPtr subscription_; rclcpp::Publisher::SharedPtr image_publisher_; - size_t count_; + int count_; std::shared_ptr predictor_; YamlConfig yaml_config_; }; diff --git a/watod-config.sh b/watod-config.sh index 4740ee69..b3447bc3 100755 --- a/watod-config.sh +++ b/watod-config.sh @@ -12,15 +12,16 @@ ## - simulation : starts simulation ## - samples : starts sample ROS2 pubsub nodes -ACTIVE_MODULES="perception infrastructure" +ACTIVE_MODULES="infrastructure perception" ############################## OPTIONAL CONFIGURATIONS ############################## ## Name to append to docker containers. DEFAULT = "" -# COMPOSE_PROJECT_NAME="" +COMPOSE_PROJECT_NAME="j89leung" +FOXGLOVE_BRIDGE_PORT="8771" ## Tag to use. Images are formatted as : with forward slashes replaced with dashes. ## DEFAULT = "" -# TAG="" +TAG="latest" # Docker Registry to pull/push images. DEFAULT = "ghcr.io/watonomous/wato_monorepo" # REGISTRY_URL="" From 60069b8836f64858e1d4c8ba883203634a113994 Mon Sep 17 00:00:00 2001 From: Justin Leung Date: Fri, 8 Mar 2024 04:04:53 +0000 Subject: [PATCH 06/12] Clean up dockerfile and docker compose --- .../semantic_segmentation.Dockerfile | 23 +-- modules/docker-compose.perception.yaml | 163 +++++++++--------- .../sample_notebook-checkpoint.ipynb | 74 ++++++++ watod-config.sh | 24 ++- 4 files changed, 180 insertions(+), 104 deletions(-) create mode 100644 src/simulation/carla_notebooks/.ipynb_checkpoints/sample_notebook-checkpoint.ipynb diff --git a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile index 9c49d354..8159b2e2 100644 --- a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile +++ b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile @@ -7,8 +7,6 @@ FROM ${PADDLE_INFERENCE_BUILD_URL} as PADDLE_INFERENCE_BUILD ################################ Source ################################ FROM ${BASE_BUILD_IMAGE} as source - - WORKDIR ${AMENT_WS}/src # Copy in the paddle inference library @@ -31,10 +29,7 @@ RUN apt-get -qq update && rosdep update && \ ################################# Dependencies ################################ FROM ${BASE_BUILD_IMAGE} as dependencies -# install tensorrt -RUN apt update && apt install -y tensorrt - -RUN apt update && apt install -y ros-humble-cv-bridge libopencv-dev +RUN apt update && apt install -y tensorrt ros-humble-cv-bridge libopencv-dev # Install Rosdep requirements COPY --from=source /tmp/colcon_install_list /tmp/colcon_install_list @@ -52,7 +47,6 @@ RUN apt-get -qq autoremove -y && apt-get -qq autoclean && apt-get -qq clean && \ ################################ Build ################################ FROM dependencies as build - # Build ROS2 packages WORKDIR ${AMENT_WS} RUN . /opt/ros/$ROS_DISTRO/setup.sh && \ @@ -62,18 +56,17 @@ RUN . /opt/ros/$ROS_DISTRO/setup.sh && \ # Entrypoint will run before any CMD on launch. Sources ~/opt//setup.bash and ~/ament_ws/install/setup.bash COPY docker/wato_ros_entrypoint.sh ${AMENT_WS}/wato_ros_entrypoint.sh -# Add /home/bolty/ament_ws/install/semantic_segmentation/lib/semantic_segmentation to LD_LIBRARY_PATH +# Add runtime libraries to path ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/ -# Add /usr/local/lib to LD_LIBRARY_PATH ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib -# /home/bolty/ament_ws/install/semantic_segmentation/lib/semantic_segmentation/ + ENTRYPOINT ["./wato_ros_entrypoint.sh"] # ################################ Prod ################################ -# FROM build as deploy +FROM build as deploy -# # Source Cleanup and Security Setup -# RUN chown -R $USER:$USER ${AMENT_WS} -# RUN rm -rf src/* +# Source Cleanup and Security Setup +RUN chown -R $USER:$USER ${AMENT_WS} +RUN rm -rf src/* -# USER ${USER} +USER ${USER} diff --git a/modules/docker-compose.perception.yaml b/modules/docker-compose.perception.yaml index b0f767d2..f3434499 100644 --- a/modules/docker-compose.perception.yaml +++ b/modules/docker-compose.perception.yaml @@ -1,68 +1,68 @@ version: "3.8" services: - # radar_object_detection: - # build: - # context: .. - # dockerfile: docker/perception/radar_object_detection/radar_object_detection.Dockerfile - # cache_from: - # - "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:${TAG}" - # - "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:main" - # target: deploy - # image: "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:${TAG}" - # command: /bin/bash -c "ros2 launch radar_object_detection radar_object_detection.launch.py" + radar_object_detection: + build: + context: .. + dockerfile: docker/perception/radar_object_detection/radar_object_detection.Dockerfile + cache_from: + - "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:build_${TAG}" + - "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:build_main" + target: deploy + image: "${PERCEPTION_RADAR_OBJECT_DETECTION_IMAGE:?}:${TAG}" + command: /bin/bash -c "ros2 launch radar_object_detection radar_object_detection.launch.py" - # camera_object_detection: - # build: - # context: .. - # dockerfile: docker/perception/camera_object_detection/camera_object_detection.Dockerfile - # cache_from: - # - "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:${TAG}" - # - "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:main" - # target: deploy - # image: "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:${TAG}" - # deploy: - # resources: - # reservations: - # devices: - # - driver: nvidia - # count: 1 - # capabilities: [ gpu ] - # command: /bin/bash -c "ros2 launch camera_object_detection nuscenes_launch.py" - # volumes: - # - /mnt/wato-drive2/perception_models/yolov8s.pt:/perception_models/yolov8s.pt + camera_object_detection: + build: + context: .. + dockerfile: docker/perception/camera_object_detection/camera_object_detection.Dockerfile + cache_from: + - "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:build_${TAG}" + - "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:build_main" + target: deploy + image: "${PERCEPTION_CAMERA_OBJECT_DETECTION_IMAGE:?}:${TAG}" + deploy: + resources: + reservations: + devices: + - driver: nvidia + count: 1 + capabilities: [ gpu ] + command: /bin/bash -c "ros2 launch camera_object_detection eve_launch.py" + volumes: + - /mnt/wato-drive2/perception_models/yolov8m.pt:/perception_models/yolov8m.pt - # lidar_object_detection: - # build: - # context: .. - # dockerfile: docker/perception/lidar_object_detection/lidar_object_detection.Dockerfile - # cache_from: - # - "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:${TAG}" - # - "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:main" - # target: deploy - # image: "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:${TAG}" - # command: /bin/bash -c "ros2 launch lidar_object_detection lidar_object_detection.launch.py" - # traffic_light_detection: - # build: - # context: .. - # dockerfile: docker/perception/traffic_light_detection/traffic_light_detection.Dockerfile - # cache_from: - # - "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:${TAG}" - # - "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:main" - # target: deploy - # image: "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:${TAG}" - # command: /bin/bash -c "ros2 launch traffic_light_detection traffic_light_detection.launch.py" + lidar_object_detection: + build: + context: .. + dockerfile: docker/perception/lidar_object_detection/lidar_object_detection.Dockerfile + cache_from: + - "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:build_${TAG}" + - "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:build_main" + target: deploy + image: "${PERCEPTION_LIDAR_OBJECT_DETECTION_IMAGE}:${TAG}" + command: /bin/bash -c "ros2 launch lidar_object_detection lidar_object_detection.launch.py" + traffic_light_detection: + build: + context: .. + dockerfile: docker/perception/traffic_light_detection/traffic_light_detection.Dockerfile + cache_from: + - "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:build_${TAG}" + - "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:build_main" + target: deploy + image: "${PERCEPTION_TRAFFIC_LIGHT_DETECTION_IMAGE}:${TAG}" + command: /bin/bash -c "ros2 launch traffic_light_detection traffic_light_detection.launch.py" - # traffic_sign_detection: - # build: - # context: .. - # dockerfile: docker/perception/traffic_sign_detection/traffic_sign_detection.Dockerfile - # cache_from: - # - "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:${TAG}" - # - "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:main" - # target: deploy - # image: "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:${TAG}" - # command: /bin/bash -c "ros2 launch traffic_sign_detection traffic_sign_detection.launch.py" + traffic_sign_detection: + build: + context: .. + dockerfile: docker/perception/traffic_sign_detection/traffic_sign_detection.Dockerfile + cache_from: + - "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:build_${TAG}" + - "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:build_main" + target: deploy + image: "${PERCEPTION_TRAFFIC_SIGN_DETECTION_IMAGE}:${TAG}" + command: /bin/bash -c "ros2 launch traffic_sign_detection traffic_sign_detection.launch.py" semantic_segmentation: build: @@ -71,38 +71,37 @@ services: cache_from: - "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:${TAG}" - "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:main" - # target: deploy + target: deploy image: "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:${TAG}" command: /bin/bash -c "ros2 launch semantic_segmentation semantic_segmentation.launch.py" volumes: - /mnt/wato-drive2/perception-weights/semantic_segmentation:/perception_models/semantic_segmentation - # add gpus all deploy: resources: reservations: devices: - driver: nvidia - capabilities: [gpu] count: 1 + capabilities: [ gpu ] - # lane_detection: - # build: - # context: .. - # dockerfile: docker/perception/lane_detection/lane_detection.Dockerfile - # cache_from: - # - "${PERCEPTION_LANE_DETECTION_IMAGE}:${TAG}" - # - "${PERCEPTION_LANE_DETECTION_IMAGE}:main" - # target: deploy - # image: "${PERCEPTION_LANE_DETECTION_IMAGE}:${TAG}" - # command: /bin/bash -c "ros2 launch lane_detection lane_detection.launch.py" + lane_detection: + build: + context: .. + dockerfile: docker/perception/lane_detection/lane_detection.Dockerfile + cache_from: + - "${PERCEPTION_LANE_DETECTION_IMAGE}:build_${TAG}" + - "${PERCEPTION_LANE_DETECTION_IMAGE}:build_main" + target: deploy + image: "${PERCEPTION_LANE_DETECTION_IMAGE}:${TAG}" + command: /bin/bash -c "ros2 launch lane_detection lane_detection.launch.py" - # tracking: - # build: - # context: .. - # dockerfile: docker/perception/tracking/tracking.Dockerfile - # cache_from: - # - "${PERCEPTION_TRACKING_IMAGE}:${TAG}" - # - "${PERCEPTION_TRACKING_IMAGE}:main" - # target: deploy - # image: "${PERCEPTION_TRACKING_IMAGE}:${TAG}" - # command: /bin/bash -c "ros2 launch tracking tracking.launch.py" + tracking: + build: + context: .. + dockerfile: docker/perception/tracking/tracking.Dockerfile + cache_from: + - "${PERCEPTION_TRACKING_IMAGE}:build_${TAG}" + - "${PERCEPTION_TRACKING_IMAGE}:build_main" + target: deploy + image: "${PERCEPTION_TRACKING_IMAGE}:${TAG}" + command: /bin/bash -c "ros2 launch tracking tracking.launch.py" diff --git a/src/simulation/carla_notebooks/.ipynb_checkpoints/sample_notebook-checkpoint.ipynb b/src/simulation/carla_notebooks/.ipynb_checkpoints/sample_notebook-checkpoint.ipynb new file mode 100644 index 00000000..1e270af5 --- /dev/null +++ b/src/simulation/carla_notebooks/.ipynb_checkpoints/sample_notebook-checkpoint.ipynb @@ -0,0 +1,74 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Setup Code\n", + "**DO NOT CHANGE THIS!!**\n", + "**RUN THE CELL BELOW FIRST!!**" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import carla\n", + "import os\n", + "\n", + "client_name = os.environ.get(\"CLIENT_NAME\", \"DOES NOT EXIST\")\n", + "if client_name == \"DOES NOT EXIST\":\n", + " raise Exception(\"The environment variable for the container name of the carla server has not been set\")\n", + "\n", + "# Connect to the client and retrieve the world object\n", + "client = carla.Client(client_name, 2000)\n", + "world = client.get_world()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Start Adding Code or Markdown Cells Below\n", + "Some helpful code cells are provided below that you may choose to use" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#### SPAWN VEHICLES ####\n", + "\"\"\"\n", + "# Get the blueprint library and filter for the vehicle blueprints\n", + "vehicle_blueprints = world.get_blueprint_library().filter('*vehicle*')\n", + "# Get the map's spawn points\n", + "spawn_points = world.get_map().get_spawn_points()\n", + "\n", + "# Spawn 50 vehicles randomly distributed throughout the map \n", + "# for each spawn point, we choose a random vehicle from the blueprint library\n", + "for i in range(0,50):\n", + " world.try_spawn_actor(random.choice(vehicle_blueprints), random.choice(spawn_points)))\n", + "\"\"\"\n", + "#### SET ALL VEHICLES TO AUTOPILOT\n", + "\"\"\"\n", + "for vehicle in world.get_actors().filter('*vehicle*'):\n", + " vehicle.set_autopilot(True)\n", + "\"\"\"" + ] + } + ], + "metadata": { + "language_info": { + "name": "python" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} \ No newline at end of file diff --git a/watod-config.sh b/watod-config.sh index b3447bc3..3255dd40 100755 --- a/watod-config.sh +++ b/watod-config.sh @@ -1,8 +1,11 @@ ## ----------------------- watod Configuration File Override ---------------------------- -############################ ACTIVE MODULE CONFIGURATION ############################ -## List of active modules to run, defined in docker-compose.yaml. ## +## HINT: You can copy the contents of this file to a watod-config.local.sh +## file that is untrackable by git and readable by watod. +## + +############################ ACTIVE MODULE CONFIGURATION ############################ ## List of active modules to run, defined in docker-compose.yaml. ## Possible values: ## - infrastructure : starts visualization tools (foxglove and/or vnc and/or data_stream) @@ -12,16 +15,23 @@ ## - simulation : starts simulation ## - samples : starts sample ROS2 pubsub nodes -ACTIVE_MODULES="infrastructure perception" +# ACTIVE_MODULES="" + +################################# MODE OF OPERATION ################################# +## Possible modes of operation when running watod. +## Possible values: +## - deploy (default) : runs production-grade containers (non-editable) +## - develop : runs developer containers (editable) + +# MODE_OF_OPERATION="" -############################## OPTIONAL CONFIGURATIONS ############################## +############################## ADVANCED CONFIGURATIONS ############################## ## Name to append to docker containers. DEFAULT = "" -COMPOSE_PROJECT_NAME="j89leung" -FOXGLOVE_BRIDGE_PORT="8771" +# COMPOSE_PROJECT_NAME="" ## Tag to use. Images are formatted as : with forward slashes replaced with dashes. ## DEFAULT = "" -TAG="latest" +# TAG="" # Docker Registry to pull/push images. DEFAULT = "ghcr.io/watonomous/wato_monorepo" # REGISTRY_URL="" From 7e16490dd6427b0ae4de5683c59e67c81fa0255d Mon Sep 17 00:00:00 2001 From: Justin Leung Date: Sun, 10 Mar 2024 01:10:17 +0000 Subject: [PATCH 07/12] Add space optimized prod image stage --- .../semantic_segmentation.Dockerfile | 34 +++++++++++++++++-- .../src/semantic_segmentation_node.cpp | 3 +- watod-config.sh | 2 +- 3 files changed, 35 insertions(+), 4 deletions(-) diff --git a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile index 8159b2e2..e1d9bce5 100644 --- a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile +++ b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile @@ -1,6 +1,7 @@ ARG BASE_BUILD_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04-devel ARG BASE_PROD_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04 ARG PADDLE_INFERENCE_BUILD_URL=ghcr.io/watonomous/perception_paddlepaddle_inference_build_cuda-12.0 +ARG RUNTIME_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04 ################################ Build library ################################ FROM ${PADDLE_INFERENCE_BUILD_URL} as PADDLE_INFERENCE_BUILD @@ -63,10 +64,39 @@ ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib ENTRYPOINT ["./wato_ros_entrypoint.sh"] # ################################ Prod ################################ -FROM build as deploy +FROM ${RUNTIME_IMAGE} as deploy + + +# Install runtime libs +RUN apt-get update && apt-get install -y \ + ros-humble-cv-bridge \ + tensorrt + +# Copy the compiled binary to the runtime image +COPY --from=build ${AMENT_WS} ${AMENT_WS} + +WORKDIR ${AMENT_WS} + +# Copy in the paddle inference library +RUN mkdir -p install/semantic_segmentation/lib/ +COPY --from=PADDLE_INFERENCE_BUILD /paddle/paddle_inference_cuda120_build.tar install/semantic_segmentation/lib/paddle_inference_cuda120_build.tar +RUN tar -xvf install/semantic_segmentation/lib/paddle_inference_cuda120_build.tar -C install/semantic_segmentation/lib +RUN rm install/semantic_segmentation/lib/paddle_inference_cuda120_build.tar + +# Add runtime libraries to path +ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/ +ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib +ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/paddle_inference_cuda120_build/paddle_inference_install_dir/paddle/lib/ + +ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/paddle_inference_cuda120_build/paddle_inference_install_dir/third_party/install/cryptopp/lib/ +ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/paddle_inference_cuda120_build/paddle_inference_install_dir/third_party/install/mkldnn/lib/ +ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${AMENT_WS}/install/semantic_segmentation/lib/paddle_inference_cuda120_build/paddle_inference_install_dir/third_party/install/mklml/lib/ + +COPY docker/wato_ros_entrypoint.sh ${AMENT_WS}/wato_ros_entrypoint.sh +ENTRYPOINT ["./wato_ros_entrypoint.sh"] # Source Cleanup and Security Setup RUN chown -R $USER:$USER ${AMENT_WS} RUN rm -rf src/* -USER ${USER} +USER ${USER} \ No newline at end of file diff --git a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp index a484fb13..40ec1faf 100644 --- a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp +++ b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp @@ -16,7 +16,8 @@ using namespace std::chrono_literals; -std::string resource_path = "/home/bolty/ament_ws/src/semantic_segmentation/resource"; +std::string resource_path = + "/home/bolty/ament_ws/install/semantic_segmentation/share/semantic_segmentation/resource"; std::string model_path = "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"; // 19 classes std::unordered_map cityscapes_labels = { diff --git a/watod-config.sh b/watod-config.sh index 3255dd40..c3dbbbb4 100755 --- a/watod-config.sh +++ b/watod-config.sh @@ -15,7 +15,7 @@ ## - simulation : starts simulation ## - samples : starts sample ROS2 pubsub nodes -# ACTIVE_MODULES="" +ACTIVE_MODULES="perception" ################################# MODE OF OPERATION ################################# ## Possible modes of operation when running watod. From 3fa0a4b9632fabeee68cb922952678cae585f877 Mon Sep 17 00:00:00 2001 From: Steven Gong Date: Sun, 10 Mar 2024 03:25:57 +0000 Subject: [PATCH 08/12] Clean up code --- .../semantic_segmentation.Dockerfile | 13 +- modules/docker-compose.perception.yaml | 6 +- .../semantic_segmentation/CMakeLists.txt | 2 +- .../semantic_segmentation/config/config.yaml | 3 - .../config/eve_config.yaml | 7 + ...ation.launch.py => eve_semantic.launch.py} | 4 +- .../semantic_segmentation/package.xml | 5 +- .../resource/cityscapes_demo.png | Bin 2676718 -> 0 bytes .../src/semantic_segmentation_node.cpp | 276 +++++++++--------- watod-config.sh | 2 +- 10 files changed, 155 insertions(+), 163 deletions(-) delete mode 100644 src/perception/semantic_segmentation/config/config.yaml create mode 100644 src/perception/semantic_segmentation/config/eve_config.yaml rename src/perception/semantic_segmentation/launch/{semantic_segmentation.launch.py => eve_semantic.launch.py} (87%) delete mode 100644 src/perception/semantic_segmentation/resource/cityscapes_demo.png diff --git a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile index e1d9bce5..7985d7c0 100644 --- a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile +++ b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile @@ -1,7 +1,6 @@ ARG BASE_BUILD_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04-devel ARG BASE_PROD_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04 ARG PADDLE_INFERENCE_BUILD_URL=ghcr.io/watonomous/perception_paddlepaddle_inference_build_cuda-12.0 -ARG RUNTIME_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04 ################################ Build library ################################ FROM ${PADDLE_INFERENCE_BUILD_URL} as PADDLE_INFERENCE_BUILD @@ -12,13 +11,12 @@ WORKDIR ${AMENT_WS}/src # Copy in the paddle inference library RUN mkdir -p semantic_segmentation/src -COPY --from=PADDLE_INFERENCE_BUILD /paddle/paddle_inference_cuda120_build.tar semantic_segmentation/src/paddle_inference_cuda120_build.tar -RUN tar -xvf semantic_segmentation/src/paddle_inference_cuda120_build.tar -C semantic_segmentation/src -RUN rm semantic_segmentation/src/paddle_inference_cuda120_build.tar +COPY --from=PADDLE_INFERENCE_BUILD /paddle/paddle_inference_cuda120_build.tar /paddle/paddle_inference_cuda120_build.tar +RUN tar -xvf /paddle/paddle_inference_cuda120_build.tar -C /paddle/ +RUN rm /paddle/paddle_inference_cuda120_build.tar # Copy in source code COPY src/perception/semantic_segmentation semantic_segmentation -COPY src/wato_msgs/sample_msgs sample_msgs # Scan for rosdeps RUN apt-get -qq update && rosdep update && \ @@ -39,6 +37,7 @@ RUN apt-fast install -qq -y --no-install-recommends $(cat /tmp/colcon_install_li # Copy in source code from source stage WORKDIR ${AMENT_WS} COPY --from=source ${AMENT_WS}/src src +COPY --from=source /paddle /paddle # Dependency Cleanup WORKDIR / @@ -64,7 +63,7 @@ ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib ENTRYPOINT ["./wato_ros_entrypoint.sh"] # ################################ Prod ################################ -FROM ${RUNTIME_IMAGE} as deploy +FROM ${BASE_PROD_IMAGE} as deploy # Install runtime libs @@ -99,4 +98,4 @@ ENTRYPOINT ["./wato_ros_entrypoint.sh"] RUN chown -R $USER:$USER ${AMENT_WS} RUN rm -rf src/* -USER ${USER} \ No newline at end of file +USER ${USER} diff --git a/modules/docker-compose.perception.yaml b/modules/docker-compose.perception.yaml index 892856fa..8ec36edd 100644 --- a/modules/docker-compose.perception.yaml +++ b/modules/docker-compose.perception.yaml @@ -55,9 +55,7 @@ services: - "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:build_main" target: deploy image: "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:${TAG}" - command: /bin/bash -c "ros2 launch semantic_segmentation semantic_segmentation.launch.py" - volumes: - - /mnt/wato-drive2/perception-weights/semantic_segmentation:/perception_models/semantic_segmentation + command: /bin/bash -c "ros2 launch semantic_segmentation eve_semantic.launch.py" deploy: resources: reservations: @@ -65,6 +63,8 @@ services: - driver: nvidia count: 1 capabilities: [ gpu ] + volumes: + - /mnt/wato-drive2/perception-weights/semantic_segmentation:/perception_models/semantic_segmentation lane_detection: build: diff --git a/src/perception/semantic_segmentation/CMakeLists.txt b/src/perception/semantic_segmentation/CMakeLists.txt index 8934368b..ecc86037 100644 --- a/src/perception/semantic_segmentation/CMakeLists.txt +++ b/src/perception/semantic_segmentation/CMakeLists.txt @@ -1,7 +1,7 @@ cmake_minimum_required(VERSION 3.8) project(semantic_segmentation LANGUAGES CXX CUDA) -set(PADDLE_LIB "/home/bolty/ament_ws/src/semantic_segmentation/src/paddle_inference_cuda120_build/paddle_inference_install_dir") # Set this path as per your setup +set(PADDLE_LIB "/paddle/paddle_inference_cuda120_build/paddle_inference_install_dir") # Set this path as per your setup option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON) option(WITH_GPU "Compile demo with GPU/CPU, default use CPU." ON) diff --git a/src/perception/semantic_segmentation/config/config.yaml b/src/perception/semantic_segmentation/config/config.yaml deleted file mode 100644 index 22ff0977..00000000 --- a/src/perception/semantic_segmentation/config/config.yaml +++ /dev/null @@ -1,3 +0,0 @@ -semantic_segmentation_node: - ros__parameters: - input_topic: "/camera/center/image_color" \ No newline at end of file diff --git a/src/perception/semantic_segmentation/config/eve_config.yaml b/src/perception/semantic_segmentation/config/eve_config.yaml new file mode 100644 index 00000000..dbabbdca --- /dev/null +++ b/src/perception/semantic_segmentation/config/eve_config.yaml @@ -0,0 +1,7 @@ +semantic_segmentation_node: + ros__parameters: + input_topic: /camera/left/image_color + publish_topic: /camera/left/segmentations + model_path: /perception_models/semantic_segmentation/pp_liteseg_infer_model/ + save_dir: /tmp + save_images: false diff --git a/src/perception/semantic_segmentation/launch/semantic_segmentation.launch.py b/src/perception/semantic_segmentation/launch/eve_semantic.launch.py similarity index 87% rename from src/perception/semantic_segmentation/launch/semantic_segmentation.launch.py rename to src/perception/semantic_segmentation/launch/eve_semantic.launch.py index 4fb1b34a..d4f742bd 100644 --- a/src/perception/semantic_segmentation/launch/semantic_segmentation.launch.py +++ b/src/perception/semantic_segmentation/launch/eve_semantic.launch.py @@ -8,14 +8,14 @@ def generate_launch_description(): config = os.path.join( get_package_share_directory('semantic_segmentation'), 'config', - 'config.yaml' + 'eve_config.yaml' ) return LaunchDescription([ Node( package='semantic_segmentation', executable='semantic_segmentation', - name='semantic_segmentation', + name='semantic_segmentation_node', parameters=[config] ) ]) diff --git a/src/perception/semantic_segmentation/package.xml b/src/perception/semantic_segmentation/package.xml index 660c0902..59e195ca 100644 --- a/src/perception/semantic_segmentation/package.xml +++ b/src/perception/semantic_segmentation/package.xml @@ -3,8 +3,9 @@ semantic_segmentation 0.0.0 - TODO: Package description - bolty + Package for semantic segmentation + Justin Leung + Steven Gong Apache-2.0 ament_cmake diff --git a/src/perception/semantic_segmentation/resource/cityscapes_demo.png b/src/perception/semantic_segmentation/resource/cityscapes_demo.png deleted file mode 100644 index ed701c2110bdf9acf7a892968669c2da8fdc857e..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 2676718 zcmYhi2QXak7eBme5JYE1bb>@#t0tmbH6lo&cdOUcI}wD{>*`&I5`@)z3%h&~E3vEy zRzwhl)xCc2|3B}%bLP%-&vWOw^UQPaocWy3`JDF#`kFLU>{I{%fJR$O-4FnvxV zP!Qh^=Z<2G|MQ$wo~r-=&8c@UZOLwZBAB73Dxh(iWBbe>Rs6NQsMRixt*@2I^gDiR@z&Wc{@Yttz`HSi{-ge&LON7>XT{ReDBBcq(6P9JHrB|y$MX1hdhalCteKwBO9%uq<}WMF z%xtR|#(BAV!*v}%CdQ#@+9+SB*Ln-AUt)?gLtT4LDX@C|4y8|y_MK~ 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zHy!r!5Q84{MM<_xrz^Uq8Ge1nD0w}zhotgoN#`Fu-{;9I(u|HjpQ zgL~{7ef^X>^+zm{Nff`u*Qxb?dHu;>KgUh~BTuzI$)$a>C+wedGVo`6;eS@IL6v{G z-9OLkm%#Ps`1*j>{;$1$*^~eI>kla$e)s;>@BM&K%d+49u>lnu%QYLbZ2h{%5qqN4 zK@yvktFfxZapTdu2;Cnu#Sh(sBNx_)L0#yrv8?fB5*X@f8?bvm3OT*HeMHe5$Jx0d z$sv+*uBV2s7@hfGO7hC=cf0?VZi(u7D$vwrP0^!VoL3GFKh#~5K||k#8&4=U^F|O1 zcrEVgJep~An7^=lAZe?8>&C8Wa43m?$-kzct#-{;_wAs$C9QW2X*UmFkKwpE1@idw zb)TLn1S8FZ>_tXExwu@CRtMczPBVrBW~gvDfGfgH1cqGv)p%3} zjn`~msj?6WL(+9VX$Ic>Vsn$|`>Zy_UgXw3R&`q1)MX)-f!}N2-}H9y^p!s>BWqisHBya$Tl`Gz(`eCw_`W)GR;V5EgQTzoMY%K=?T)| zRu)%f2B%td_mIwxxMGnNUp_mF29U5?ZkZX^i`<0mtwG|nU)NA8n)b;~Lmno5c)Hnm zV(_#48_S;mR2SVA>;M1&C3HntbYx+4WjbSWWnpw>05UK!H7zkREif`vF)}(eH##&j zD=;xSFfd{=D{BA%03~!qSaf7zbY(hiZ)9m^c>ppnF*PkQGA%GNR53C-H8(mmGAl4K WIxsL3Z cityscapes_labels = { {0, "road"}, {1, "sidewalk"}, {2, "building"}, {3, "wall"}, {4, "fence"}, @@ -68,9 +68,6 @@ YamlConfig load_yaml(const std::string& yaml_path) { return yaml_config; } -/* This example creates a subclass of Node and uses std::bind() to register a - * member function as a callback from the timer. */ - class SemanticSegmentationNode : public rclcpp::Node { public: bool FLAGS_use_mkldnn = true; @@ -78,9 +75,138 @@ class SemanticSegmentationNode : public rclcpp::Node { std::string FLAGS_trt_precision = "fp32"; bool FLAGS_use_trt_dynamic_shape = true; std::string FLAGS_dynamic_shape_path = resource_path + "/dynamic_shape.pbtxt"; - std::string FLAGS_img_path = resource_path + "/cityscapes_demo.png"; std::string FLAGS_devices = "GPU"; + // ROS Parameters + std::string image_topic; + std::string publish_topic; + std::string model_path; + std::string save_dir; + bool save_images; + + SemanticSegmentationNode() : Node("semantic_segmentation_node"), count_(0) { + this->declare_parameter("input_topic", "/camera/left/image_color"); + this->declare_parameter("publish_topic", "/camera/left/segmentations"); + this->declare_parameter( + "model_path", "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"); + this->declare_parameter( + "save_dir", "/tmp"); + this->declare_parameter("save_images", false); + + this->get_parameter("input_topic", image_topic); + this->get_parameter("publish_topic", publish_topic); + this->get_parameter("model_path", model_path); + this->get_parameter("save_dir", save_dir); + this->get_parameter("save_images", save_images); + + RCLCPP_INFO(this->get_logger(), "subscribing to image_topic: %s", image_topic.c_str()); + + yaml_config_ = load_yaml(resource_path + "/deploy.yaml"); + + // Print out the yaml config + RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config_.model_file.c_str()); + RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config_.params_file.c_str()); + RCLCPP_INFO(this->get_logger(), "is_normalize: %d", yaml_config_.is_normalize); + RCLCPP_INFO(this->get_logger(), "is_resize: %d", yaml_config_.is_resize); + + // Create the paddle predictor + predictor_ = create_predictor(yaml_config_); + + // Subscribe to the image topic + subscription_ = this->create_subscription( + image_topic, 10, + std::bind(&SemanticSegmentationNode::image_callback, this, std::placeholders::_1)); + + image_publisher_ = this->create_publisher(publish_topic, 10); + } + + void image_callback(const sensor_msgs::msg::Image::SharedPtr msg) { + RCLCPP_INFO(this->get_logger(), "Received image"); + cv::Mat img; + cv::Mat original_img; + + try { + img = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8)->image; + original_img = img.clone(); + } catch (cv_bridge::Exception& e) { + RCLCPP_ERROR(this->get_logger(), "Could not convert from '%s' to 'bgr8'.", + msg->encoding.c_str()); + return; + } + + // Process the image according to yaml config + RCLCPP_INFO(this->get_logger(), "Image shape before process: %d, %d, %d", img.rows, img.cols, + img.channels()); + process_image(img, yaml_config_); + + int rows = img.rows; + int cols = img.cols; + int chs = img.channels(); + RCLCPP_INFO(this->get_logger(), "Image shape after process: %d, %d, %d", rows, cols, chs); + std::vector input_data(1 * chs * rows * cols, 0.0f); + hwc_img_2_chw_data(img, input_data.data()); + + // Set input + auto input_names = predictor_->GetInputNames(); + auto input_t = predictor_->GetInputHandle(input_names[0]); + std::vector input_shape = {1, chs, rows, cols}; + input_t->Reshape(input_shape); + input_t->CopyFromCpu(input_data.data()); + + // Start timing + auto start = std::chrono::high_resolution_clock::now(); + + // Run + predictor_->Run(); + + // Stop timing + auto end = std::chrono::high_resolution_clock::now(); + + // Calculate elapsed time + std::chrono::duration elapsed = end - start; + + // Get output + auto output_names = predictor_->GetOutputNames(); + auto output_t = predictor_->GetOutputHandle(output_names[0]); + std::vector output_shape = output_t->shape(); + int out_num = + std::accumulate(output_shape.begin(), output_shape.end(), 1, std::multiplies()); + std::vector out_data(out_num); + output_t->CopyToCpu(out_data.data()); + + // Get pseudo image + std::vector out_data_u8(out_num); + cv::Mat out_gray_img(output_shape[1], output_shape[2], CV_8UC1, out_data_u8.data()); + cv::Mat colored_img; + // apply cityscapes_labels_colormap to img + cv::cvtColor(out_gray_img, colored_img, cv::COLOR_GRAY2BGR); + for (int i = 0; i < output_shape[1]; i++) { + for (int j = 0; j < output_shape[2]; j++) { + int label = out_data[i * output_shape[2] + j]; + if (cityscapes_labels.find(label) != cityscapes_labels.end()) { + auto [r, g, b] = cityscapes_label_colormap[label]; + colored_img.at(i, j) = cv::Vec3b(b, g, r); + } + } + } + + if (save_images) { + std::string filename = save_dir + "/segmentation_" + std::to_string(count_) + ".jpg"; + cv::imwrite(filename, colored_img); + filename = save_dir + "/orig_segmentation_" + std::to_string(count_) + ".jpg"; + cv::imwrite(filename, original_img); + RCLCPP_INFO(this->get_logger(), "Saved image to %s", filename.c_str()); + } + count_++; + + RCLCPP_INFO(this->get_logger(), "inference took %f ms", elapsed.count()); + + sensor_msgs::msg::Image::SharedPtr out_img_msg = + cv_bridge::CvImage(std_msgs::msg::Header(), "bgr8", colored_img).toImageMsg(); + + image_publisher_->publish(*out_img_msg); + } + std::shared_ptr create_predictor(const YamlConfig& yaml_config) { paddle_infer::Config infer_config; infer_config.SetModel(model_path + "/" + yaml_config.model_file, @@ -100,8 +226,6 @@ class SemanticSegmentationNode : public rclcpp::Node { // TRT config if (FLAGS_use_trt) { - // LOG(INFO) << "Use TRT"; - // LOG(INFO) << "trt_precision:" << FLAGS_trt_precision; RCLCPP_INFO(this->get_logger(), "trt_precision: %s", FLAGS_trt_precision.c_str()); // TRT precision @@ -236,8 +360,6 @@ class SemanticSegmentationNode : public rclcpp::Node { } void process_image(cv::Mat& img, const YamlConfig& yaml_config) { - // cv::Mat img = cv::imread(FLAGS_img_path, cv::IMREAD_COLOR); - // img = resizeWithPadding(img, 2048, 1024); img = resizeFromCenter(img, 2048, 1024); cv::cvtColor(img, img, cv::COLOR_BGR2RGB); if (yaml_config.is_resize) { @@ -249,141 +371,7 @@ class SemanticSegmentationNode : public rclcpp::Node { } } - cv::Mat read_process_image(const YamlConfig& yaml_config) { - cv::Mat img = cv::imread(FLAGS_img_path, cv::IMREAD_COLOR); - cv::cvtColor(img, img, cv::COLOR_BGR2RGB); - if (yaml_config.is_resize) { - cv::resize(img, img, cv::Size(yaml_config.resize_width, yaml_config.resize_height)); - } - if (yaml_config.is_normalize) { - img.convertTo(img, CV_32F, 1.0 / 255, 0); - img = (img - 0.5) / 0.5; - } - return img; - } - - SemanticSegmentationNode() : Node("semantic_segmentation_node"), count_(0) { - // Get the image topic parameter from the launch file) - std::string image_topic = this->declare_parameter("input_topic", "/camera/center/image_color"); - image_topic = this->get_parameter("input_topic").as_string(); - RCLCPP_INFO(this->get_logger(), "subscribing to image_topic: %s", image_topic.c_str()); - - publisher_ = this->create_publisher("topic", 10); - yaml_config_ = load_yaml(resource_path + "/deploy.yaml"); - - // Print out the yaml config - RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config_.model_file.c_str()); - RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config_.params_file.c_str()); - RCLCPP_INFO(this->get_logger(), "is_normalize: %d", yaml_config_.is_normalize); - RCLCPP_INFO(this->get_logger(), "is_resize: %d", yaml_config_.is_resize); - - // Create the paddle predictor - predictor_ = create_predictor(yaml_config_); - - // Subscribe to the image topic - subscription_ = this->create_subscription( - image_topic, 10, - std::bind(&SemanticSegmentationNode::image_callback, this, std::placeholders::_1)); - - image_publisher_ = - this->create_publisher("semantic_segmentation_image", 10); - } - private: - void image_callback(const sensor_msgs::msg::Image::SharedPtr msg) { - RCLCPP_INFO(this->get_logger(), "Received image"); - cv::Mat img; - cv::Mat original_img; - - // Convert msg to a cv mat - - try { - img = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8)->image; - original_img = img.clone(); - } catch (cv_bridge::Exception& e) { - RCLCPP_ERROR(this->get_logger(), "Could not convert from '%s' to 'bgr8'.", - msg->encoding.c_str()); - return; - } - - // Process the image according to yaml config - RCLCPP_INFO(this->get_logger(), "Image shape before process: %d, %d, %d", img.rows, img.cols, - img.channels()); - process_image(img, yaml_config_); - // img = read_process_image(yaml_config_); - - int rows = img.rows; - int cols = img.cols; - int chs = img.channels(); - RCLCPP_INFO(this->get_logger(), "Image shape after process: %d, %d, %d", rows, cols, chs); - std::vector input_data(1 * chs * rows * cols, 0.0f); - hwc_img_2_chw_data(img, input_data.data()); - - // Set input - auto input_names = predictor_->GetInputNames(); - auto input_t = predictor_->GetInputHandle(input_names[0]); - std::vector input_shape = {1, chs, rows, cols}; - input_t->Reshape(input_shape); - input_t->CopyFromCpu(input_data.data()); - - // Start timing - auto start = std::chrono::high_resolution_clock::now(); - - // Run - predictor_->Run(); - - // Stop timing - auto end = std::chrono::high_resolution_clock::now(); - - // Calculate elapsed time - std::chrono::duration elapsed = end - start; - - // Get output - auto output_names = predictor_->GetOutputNames(); - auto output_t = predictor_->GetOutputHandle(output_names[0]); - std::vector output_shape = output_t->shape(); - int out_num = - std::accumulate(output_shape.begin(), output_shape.end(), 1, std::multiplies()); - std::vector out_data(out_num); - output_t->CopyToCpu(out_data.data()); - - // Get pseudo image - std::vector out_data_u8(out_num); - cv::Mat out_gray_img(output_shape[1], output_shape[2], CV_8UC1, out_data_u8.data()); - cv::Mat colored_img; - // apply cityscapes_labels_colormap to img - cv::cvtColor(out_gray_img, colored_img, cv::COLOR_GRAY2BGR); - for (int i = 0; i < output_shape[1]; i++) { - for (int j = 0; j < output_shape[2]; j++) { - int label = out_data[i * output_shape[2] + j]; - if (cityscapes_labels.find(label) != cityscapes_labels.end()) { - auto [r, g, b] = cityscapes_label_colormap[label]; - colored_img.at(i, j) = cv::Vec3b(b, g, r); - } - } - } - - if (count_ < 1000) { - // write the source image - cv::imwrite("/home/bolty/ament_ws/src/semantic_segmentation/test/src_img" + - std::to_string(count_) + ".jpg", - original_img); - // write the segmentation image - cv::imwrite("/home/bolty/ament_ws/src/semantic_segmentation/test/out_img" + - std::to_string(count_) + ".jpg", - colored_img); - RCLCPP_INFO(this->get_logger(), "Image written to /tmp/out_img%d.jpg, inference took %f ms", - count_, elapsed.count()); - count_++; - } - - // Publish color image to topic - sensor_msgs::msg::Image::SharedPtr out_img_msg = - cv_bridge::CvImage(std_msgs::msg::Header(), "bgr8", colored_img).toImageMsg(); - - image_publisher_->publish(*out_img_msg); - } - rclcpp::Publisher::SharedPtr publisher_; rclcpp::Subscription::SharedPtr subscription_; rclcpp::Publisher::SharedPtr image_publisher_; int count_; @@ -396,4 +384,4 @@ int main(int argc, char* argv[]) { rclcpp::spin(std::make_shared()); rclcpp::shutdown(); return 0; -} \ No newline at end of file +} diff --git a/watod-config.sh b/watod-config.sh index c3dbbbb4..3255dd40 100755 --- a/watod-config.sh +++ b/watod-config.sh @@ -15,7 +15,7 @@ ## - simulation : starts simulation ## - samples : starts sample ROS2 pubsub nodes -ACTIVE_MODULES="perception" +# ACTIVE_MODULES="" ################################# MODE OF OPERATION ################################# ## Possible modes of operation when running watod. From c0c1df405752e169e519f18d6c103fff62a367d3 Mon Sep 17 00:00:00 2001 From: Steven Gong Date: Sun, 10 Mar 2024 05:38:29 +0000 Subject: [PATCH 09/12] Update image with correct header and create save image directories --- .../semantic_segmentation/config/eve_config.yaml | 2 +- .../src/semantic_segmentation_node.cpp | 16 ++++++++++------ 2 files changed, 11 insertions(+), 7 deletions(-) diff --git a/src/perception/semantic_segmentation/config/eve_config.yaml b/src/perception/semantic_segmentation/config/eve_config.yaml index dbabbdca..4bb70c50 100644 --- a/src/perception/semantic_segmentation/config/eve_config.yaml +++ b/src/perception/semantic_segmentation/config/eve_config.yaml @@ -3,5 +3,5 @@ semantic_segmentation_node: input_topic: /camera/left/image_color publish_topic: /camera/left/segmentations model_path: /perception_models/semantic_segmentation/pp_liteseg_infer_model/ - save_dir: /tmp + save_dir: /segmented save_images: false diff --git a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp index d0cacffc..1a5814d4 100644 --- a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp +++ b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp @@ -1,5 +1,6 @@ #include #include +#include #include #include #include @@ -89,8 +90,7 @@ class SemanticSegmentationNode : public rclcpp::Node { this->declare_parameter("publish_topic", "/camera/left/segmentations"); this->declare_parameter( "model_path", "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"); - this->declare_parameter( - "save_dir", "/tmp"); + this->declare_parameter("save_dir", "/tmp"); this->declare_parameter("save_images", false); this->get_parameter("input_topic", image_topic); @@ -99,6 +99,10 @@ class SemanticSegmentationNode : public rclcpp::Node { this->get_parameter("save_dir", save_dir); this->get_parameter("save_images", save_images); + if (!std::filesystem::exists(save_dir)) { + std::filesystem::create_directories(save_dir); + } + RCLCPP_INFO(this->get_logger(), "subscribing to image_topic: %s", image_topic.c_str()); yaml_config_ = load_yaml(resource_path + "/deploy.yaml"); @@ -191,18 +195,18 @@ class SemanticSegmentationNode : public rclcpp::Node { } if (save_images) { - std::string filename = save_dir + "/segmentation_" + std::to_string(count_) + ".jpg"; + std::string filename = save_dir + "/segmented_" + std::to_string(count_) + ".jpg"; cv::imwrite(filename, colored_img); - filename = save_dir + "/orig_segmentation_" + std::to_string(count_) + ".jpg"; + RCLCPP_INFO(this->get_logger(), "Saved segmented image to %s", filename.c_str()); + filename = save_dir + "/src_" + std::to_string(count_) + ".jpg"; cv::imwrite(filename, original_img); - RCLCPP_INFO(this->get_logger(), "Saved image to %s", filename.c_str()); } count_++; RCLCPP_INFO(this->get_logger(), "inference took %f ms", elapsed.count()); sensor_msgs::msg::Image::SharedPtr out_img_msg = - cv_bridge::CvImage(std_msgs::msg::Header(), "bgr8", colored_img).toImageMsg(); + cv_bridge::CvImage(msg->header, "bgr8", colored_img).toImageMsg(); image_publisher_->publish(*out_img_msg); } From e06f49a0447179eef1cd7d28a0eaace93e1b813c Mon Sep 17 00:00:00 2001 From: Steven Gong Date: Sun, 10 Mar 2024 06:31:29 +0000 Subject: [PATCH 10/12] Add visualization topics --- modules/docker-compose.perception.yaml | 2 +- .../semantic_segmentation/config/eve_config.yaml | 1 + .../launch/{eve_semantic.launch.py => eve.launch.py} | 0 .../src/semantic_segmentation_node.cpp | 11 ++++++++++- 4 files changed, 12 insertions(+), 2 deletions(-) rename src/perception/semantic_segmentation/launch/{eve_semantic.launch.py => eve.launch.py} (100%) diff --git a/modules/docker-compose.perception.yaml b/modules/docker-compose.perception.yaml index 8ec36edd..7efd036c 100644 --- a/modules/docker-compose.perception.yaml +++ b/modules/docker-compose.perception.yaml @@ -55,7 +55,7 @@ services: - "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:build_main" target: deploy image: "${PERCEPTION_SEMANTIC_SEGMENTATION_IMAGE}:${TAG}" - command: /bin/bash -c "ros2 launch semantic_segmentation eve_semantic.launch.py" + command: /bin/bash -c "ros2 launch semantic_segmentation eve.launch.py" deploy: resources: reservations: diff --git a/src/perception/semantic_segmentation/config/eve_config.yaml b/src/perception/semantic_segmentation/config/eve_config.yaml index 4bb70c50..8e9d755b 100644 --- a/src/perception/semantic_segmentation/config/eve_config.yaml +++ b/src/perception/semantic_segmentation/config/eve_config.yaml @@ -2,6 +2,7 @@ semantic_segmentation_node: ros__parameters: input_topic: /camera/left/image_color publish_topic: /camera/left/segmentations + publish_vis_topic: /camera/left/segmentations_viz model_path: /perception_models/semantic_segmentation/pp_liteseg_infer_model/ save_dir: /segmented save_images: false diff --git a/src/perception/semantic_segmentation/launch/eve_semantic.launch.py b/src/perception/semantic_segmentation/launch/eve.launch.py similarity index 100% rename from src/perception/semantic_segmentation/launch/eve_semantic.launch.py rename to src/perception/semantic_segmentation/launch/eve.launch.py diff --git a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp index 1a5814d4..cd55ac5a 100644 --- a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp +++ b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp @@ -81,6 +81,7 @@ class SemanticSegmentationNode : public rclcpp::Node { // ROS Parameters std::string image_topic; std::string publish_topic; + std::string publish_vis_topic; std::string model_path; std::string save_dir; bool save_images; @@ -88,6 +89,7 @@ class SemanticSegmentationNode : public rclcpp::Node { SemanticSegmentationNode() : Node("semantic_segmentation_node"), count_(0) { this->declare_parameter("input_topic", "/camera/left/image_color"); this->declare_parameter("publish_topic", "/camera/left/segmentations"); + this->declare_parameter("publish_vis_topic", "/camera/left/segmentations_viz"); this->declare_parameter( "model_path", "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"); this->declare_parameter("save_dir", "/tmp"); @@ -95,6 +97,7 @@ class SemanticSegmentationNode : public rclcpp::Node { this->get_parameter("input_topic", image_topic); this->get_parameter("publish_topic", publish_topic); + this->get_parameter("publish_vis_topic", publish_vis_topic); this->get_parameter("model_path", model_path); this->get_parameter("save_dir", save_dir); this->get_parameter("save_images", save_images); @@ -122,6 +125,7 @@ class SemanticSegmentationNode : public rclcpp::Node { std::bind(&SemanticSegmentationNode::image_callback, this, std::placeholders::_1)); image_publisher_ = this->create_publisher(publish_topic, 10); + image_viz_publisher_ = this->create_publisher(publish_vis_topic, 10); } void image_callback(const sensor_msgs::msg::Image::SharedPtr msg) { @@ -205,10 +209,14 @@ class SemanticSegmentationNode : public rclcpp::Node { RCLCPP_INFO(this->get_logger(), "inference took %f ms", elapsed.count()); + sensor_msgs::msg::Image::SharedPtr out_gray_img_msg = + cv_bridge::CvImage(msg->header, "mono8", out_gray_img).toImageMsg(); + sensor_msgs::msg::Image::SharedPtr out_img_msg = cv_bridge::CvImage(msg->header, "bgr8", colored_img).toImageMsg(); - image_publisher_->publish(*out_img_msg); + image_publisher_->publish(*out_gray_img_msg); + image_viz_publisher_->publish(*out_img_msg); } std::shared_ptr create_predictor(const YamlConfig& yaml_config) { @@ -378,6 +386,7 @@ class SemanticSegmentationNode : public rclcpp::Node { private: rclcpp::Subscription::SharedPtr subscription_; rclcpp::Publisher::SharedPtr image_publisher_; + rclcpp::Publisher::SharedPtr image_viz_publisher_; int count_; std::shared_ptr predictor_; YamlConfig yaml_config_; From 9723cc98d6d739afdad89413d0e4ec0826e1f71f Mon Sep 17 00:00:00 2001 From: Justin Leung Date: Mon, 18 Mar 2024 07:17:31 +0000 Subject: [PATCH 11/12] Address PR comments, add perception_utils --- .../semantic_segmentation.Dockerfile | 13 +- modules/docker-compose.perception.yaml | 2 +- .../perception_utils/CMakeLists.txt | 49 ++ .../include/perception_utils/camera_utils.hpp | 14 + src/perception/perception_utils/package.xml | 18 + .../perception_utils/src/camera_utils.cpp | 97 ++++ .../semantic_segmentation/CMakeLists.txt | 70 ++- .../config/eve_config.yaml | 2 +- .../include/semantic_segmentation_node.hpp | 58 +++ .../semantic_segmentation/package.xml | 7 +- .../src/semantic_segmentation_node.cpp | 483 +++++++----------- 11 files changed, 468 insertions(+), 345 deletions(-) create mode 100644 src/perception/perception_utils/CMakeLists.txt create mode 100644 src/perception/perception_utils/include/perception_utils/camera_utils.hpp create mode 100644 src/perception/perception_utils/package.xml create mode 100644 src/perception/perception_utils/src/camera_utils.cpp create mode 100644 src/perception/semantic_segmentation/include/semantic_segmentation_node.hpp diff --git a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile index 7985d7c0..d6db63be 100644 --- a/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile +++ b/docker/perception/semantic_segmentation/semantic_segmentation.Dockerfile @@ -1,11 +1,11 @@ -ARG BASE_BUILD_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04-devel -ARG BASE_PROD_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04 +ARG BASE_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04-devel +ARG RUNTIME_IMAGE=ghcr.io/watonomous/wato_monorepo/base:cuda12.0-humble-ubuntu22.04 ARG PADDLE_INFERENCE_BUILD_URL=ghcr.io/watonomous/perception_paddlepaddle_inference_build_cuda-12.0 ################################ Build library ################################ FROM ${PADDLE_INFERENCE_BUILD_URL} as PADDLE_INFERENCE_BUILD ################################ Source ################################ -FROM ${BASE_BUILD_IMAGE} as source +FROM ${BASE_IMAGE} as source WORKDIR ${AMENT_WS}/src @@ -17,6 +17,7 @@ RUN rm /paddle/paddle_inference_cuda120_build.tar # Copy in source code COPY src/perception/semantic_segmentation semantic_segmentation +COPY src/perception/perception_utils perception_utils # Scan for rosdeps RUN apt-get -qq update && rosdep update && \ @@ -26,7 +27,7 @@ RUN apt-get -qq update && rosdep update && \ | sort > /tmp/colcon_install_list ################################# Dependencies ################################ -FROM ${BASE_BUILD_IMAGE} as dependencies +FROM ${BASE_IMAGE} as dependencies RUN apt update && apt install -y tensorrt ros-humble-cv-bridge libopencv-dev @@ -36,8 +37,8 @@ RUN apt-fast install -qq -y --no-install-recommends $(cat /tmp/colcon_install_li # Copy in source code from source stage WORKDIR ${AMENT_WS} -COPY --from=source ${AMENT_WS}/src src COPY --from=source /paddle /paddle +COPY --from=source ${AMENT_WS}/src src # Dependency Cleanup WORKDIR / @@ -63,7 +64,7 @@ ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib ENTRYPOINT ["./wato_ros_entrypoint.sh"] # ################################ Prod ################################ -FROM ${BASE_PROD_IMAGE} as deploy +FROM ${RUNTIME_IMAGE} as deploy # Install runtime libs diff --git a/modules/docker-compose.perception.yaml b/modules/docker-compose.perception.yaml index 7efd036c..e8aa9f20 100644 --- a/modules/docker-compose.perception.yaml +++ b/modules/docker-compose.perception.yaml @@ -64,7 +64,7 @@ services: count: 1 capabilities: [ gpu ] volumes: - - /mnt/wato-drive2/perception-weights/semantic_segmentation:/perception_models/semantic_segmentation + - /mnt/wato-drive2/perception-weights/semantic_segmentation/pp_liteseg_infer_model:/perception_models/semantic_segmentation/pp_liteseg_infer_model lane_detection: build: diff --git a/src/perception/perception_utils/CMakeLists.txt b/src/perception/perception_utils/CMakeLists.txt new file mode 100644 index 00000000..da8db084 --- /dev/null +++ b/src/perception/perception_utils/CMakeLists.txt @@ -0,0 +1,49 @@ +cmake_minimum_required(VERSION 3.5) +project(perception_utils) + +# Default to C++14 +if(NOT CMAKE_CXX_STANDARD) + set(CMAKE_CXX_STANDARD 14) +endif() + +if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") + add_compile_options(-Wall -Wextra -Wpedantic) +endif() + +# Find dependencies +find_package(ament_cmake REQUIRED) +find_package(rclcpp REQUIRED) +find_package(OpenCV REQUIRED) + +# Include header files +include_directories(include + ${OpenCV_INCLUDE_DIRS} +) + +# Declare a C++ library +add_library(perception_utils SHARED + src/camera_utils.cpp +) + +# Specify libraries to link a library or executable target against +ament_target_dependencies(perception_utils + rclcpp + OpenCV) + +install(TARGETS perception_utils + EXPORT export_perception_utils + ARCHIVE DESTINATION lib + LIBRARY DESTINATION lib + RUNTIME DESTINATION bin +) + +ament_export_targets(export_perception_utils HAS_LIBRARY_TARGET) +ament_export_include_directories(include) +ament_export_dependencies(rclcpp) + +# Install header files +install(DIRECTORY include/ + DESTINATION include +) + +ament_package() \ No newline at end of file diff --git a/src/perception/perception_utils/include/perception_utils/camera_utils.hpp b/src/perception/perception_utils/include/perception_utils/camera_utils.hpp new file mode 100644 index 00000000..3b058e74 --- /dev/null +++ b/src/perception/perception_utils/include/perception_utils/camera_utils.hpp @@ -0,0 +1,14 @@ +#ifndef CAMERA_UTILS_HPP_ +#define CAMERA_UTILS_HPP_ + +#include + +namespace CameraUtils { +// Swaps the channels of an image from HWC to CHW format +void hwc_img_2_chw_data(const cv::Mat& hwc_img, float* data); +cv::Mat resize_image_aspect_ratio(const cv::Mat& original_image, int max_width, int max_height); +cv::Mat resize_with_padding(const cv::Mat& original_image, int target_width, int target_height); +cv::Mat resize_from_center(const cv::Mat& original_image, int target_width, int target_height); +}; // namespace CameraUtils + +#endif // CAMERA_UTILS_HPP_ \ No newline at end of file diff --git a/src/perception/perception_utils/package.xml b/src/perception/perception_utils/package.xml new file mode 100644 index 00000000..b269c8c2 --- /dev/null +++ b/src/perception/perception_utils/package.xml @@ -0,0 +1,18 @@ + + + perception_utils + 0.0.1 + A utility library for perception tasks in ROS 2. + + Justin Leung + Apache-2.0 + + ament_cmake + rclcpp + opencv + + + ament_cmake + + + \ No newline at end of file diff --git a/src/perception/perception_utils/src/camera_utils.cpp b/src/perception/perception_utils/src/camera_utils.cpp new file mode 100644 index 00000000..70b43081 --- /dev/null +++ b/src/perception/perception_utils/src/camera_utils.cpp @@ -0,0 +1,97 @@ +#include "perception_utils/camera_utils.hpp" +#include + +// Swaps the channels of an image from HWC to CHW format +void CameraUtils::hwc_img_2_chw_data(const cv::Mat& hwc_img, float* data) { + int rows = hwc_img.rows; + int cols = hwc_img.cols; + int chs = hwc_img.channels(); + for (int i = 0; i < chs; ++i) { + cv::extractChannel(hwc_img, cv::Mat(rows, cols, CV_32FC1, data + i * rows * cols), i); + } +} + +cv::Mat CameraUtils::resize_image_aspect_ratio(const cv::Mat& original_image, int max_width, + int max_height) { + int original_width = original_image.cols; + int original_height = original_image.rows; + double original_aspect_ratio = (double)original_width / original_height; + + int new_width, new_height; + double max_aspect_ratio = (double)max_width / max_height; + + if (original_aspect_ratio > max_aspect_ratio) { + // Width is the limiting factor + new_width = max_width; + new_height = static_cast(max_width / original_aspect_ratio); + } else { + // Height is the limiting factor + new_height = max_height; + new_width = static_cast(max_height * original_aspect_ratio); + } + + cv::Mat resized_image; + cv::resize(original_image, resized_image, cv::Size(new_width, new_height)); + + return resized_image; +} + +cv::Mat CameraUtils::resize_with_padding(const cv::Mat& original_image, int target_width, + int target_height) { + int original_width = original_image.cols; + int original_height = original_image.rows; + + double target_ratio = (double)target_width / target_height; + double original_ratio = (double)original_width / original_height; + + int new_width, new_height; + + if (original_ratio > target_ratio) { + // Original is wider. Fit to width and pad height. + new_width = target_width; + new_height = + static_cast(original_height * (static_cast(target_width) / original_width)); + } else { + // Original is taller. Fit to height and pad width. + new_height = target_height; + new_width = + static_cast(original_width * (static_cast(target_height) / original_height)); + } + + cv::Mat resized_image; + cv::resize(original_image, resized_image, cv::Size(new_width, new_height)); + + int top = (target_height - new_height) / 2; + int bottom = target_height - new_height - top; + int left = (target_width - new_width) / 2; + int right = target_width - new_width - left; + + cv::Mat padded_image; + cv::copyMakeBorder(resized_image, padded_image, top, bottom, left, right, cv::BORDER_CONSTANT, + cv::Scalar(0, 0, 0)); + + return padded_image; +} + +cv::Mat CameraUtils::resize_from_center(const cv::Mat& original_image, int target_width, + int target_height) { + int original_width = original_image.cols; + int original_height = original_image.rows; + + // Calculate the new height maintaining the aspect ratio + double target_ratio = (double)target_width / target_height; + int new_height = static_cast(original_width / target_ratio); + + // Calculate the cropping area + int startY = (original_height - new_height) / 2; + + // Crop the image from the center + cv::Rect roi(0, startY, original_width, new_height); + cv::Mat cropped_image = original_image(roi); + + // Resize the cropped image + cv::Mat resized_image; + cv::resize(cropped_image, resized_image, cv::Size(target_width, target_height)); + + return resized_image; +} \ No newline at end of file diff --git a/src/perception/semantic_segmentation/CMakeLists.txt b/src/perception/semantic_segmentation/CMakeLists.txt index ecc86037..b2dd1891 100644 --- a/src/perception/semantic_segmentation/CMakeLists.txt +++ b/src/perception/semantic_segmentation/CMakeLists.txt @@ -1,13 +1,12 @@ cmake_minimum_required(VERSION 3.8) +include(CMakePrintHelpers) project(semantic_segmentation LANGUAGES CXX CUDA) +message(STATUS "Perception Utils Include Dirs: ${perception_utils_INCLUDE_DIRS}") +message(STATUS "Perception Utils Include Dirs: ${perception_utils_INCLUDE_DIRS}") -set(PADDLE_LIB "/paddle/paddle_inference_cuda120_build/paddle_inference_install_dir") # Set this path as per your setup - -option(WITH_MKL "Compile demo with MKL/OpenBlas support, default use MKL." ON) -option(WITH_GPU "Compile demo with GPU/CPU, default use CPU." ON) -option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static." ON) -option(USE_TENSORRT "Compile demo with TensorRT." ON) -option(WITH_ROCM "Compile demo with rocm." OFF) +cmake_print_variables(PROJECT_SOURCE_DIR) +cmake_print_variables(perception_utils_INCLUDE_DIRS) +set(PADDLE_LIB "/paddle/paddle_inference_cuda120_build/paddle_inference_install_dir") # Compiler options if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") @@ -22,44 +21,63 @@ endif() # Platform-independent settings include_directories("${PADDLE_LIB}/") set(PADDLE_LIB_THIRD_PARTY_PATH "${PADDLE_LIB}/third_party/install/") -include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/include ${PADDLE_LIB_THIRD_PARTY_PATH}glog/include ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/include ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/include ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/include ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/include ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/include) +include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/include + ${PADDLE_LIB_THIRD_PARTY_PATH}glog/include + ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/include + ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/include + ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/include + ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/include + ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/include + ) -link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/lib ${PADDLE_LIB_THIRD_PARTY_PATH}glog/lib ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/lib ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/lib ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/lib ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/lib ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/lib ${PADDLE_LIB}/paddle/lib) +link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}protobuf/lib + ${PADDLE_LIB_THIRD_PARTY_PATH}glog/lib + ${PADDLE_LIB_THIRD_PARTY_PATH}gflags/lib + ${PADDLE_LIB_THIRD_PARTY_PATH}xxhash/lib + ${PADDLE_LIB_THIRD_PARTY_PATH}cryptopp/lib + ${PADDLE_LIB_THIRD_PARTY_PATH}onnxruntime/lib + ${PADDLE_LIB_THIRD_PARTY_PATH}paddle2onnx/lib + ${PADDLE_LIB}/paddle/lib) -# Find packages -find_package(rclcpp REQUIRED) -find_package(std_msgs REQUIRED) -find_package(sensor_msgs REQUIRED) -find_package(geometry_msgs REQUIRED) -find_package(image_transport REQUIRED) -find_package(OpenCV REQUIRED) -find_package(cv_bridge REQUIRED) -find_package(CUDA REQUIRED) -find_package(ament_cmake REQUIRED) -find_package(yaml-cpp REQUIRED) + message(STATUS "Perception Utils Include Dirs: ${perception_utils_INCLUDE_DIRS}") + +set(REQUIRED_PACKAGES + rclcpp + std_msgs + sensor_msgs + image_transport + OpenCV + cv_bridge + CUDA + ament_cmake + yaml-cpp + perception_utils +) + +foreach(PACKAGE ${REQUIRED_PACKAGES}) + find_package(${PACKAGE} REQUIRED) +endforeach() # Include directories include_directories(include ${rclcpp_INCLUDE_DIRS} ${std_msgs_INCLUDE_DIRS} ${sensor_msgs_INCLUDE_DIRS} - ${geometry_msgs_INCLUDE_DIRS} ${image_transport_INCLUDE_DIRS} ${CUDA_INCLUDE_DIRS} ${YAML_CPP_INCLUDE_DIRS} /usr/local/include ${PADDLE_LIB}/paddle/include ${PADDLE_LIB}/third_party/install/mkldnn/include - ) - + ${perception_utils_INCLUDE_DIRS} +) # Link directories link_directories(/usr/local/lib ${YAML_CPP_LIBRARIES}) - # Set additional dependencies set(EXTRA_LIBS "-lrt -ldl -lpthread") -set(DEPS ${rclcpp_LIBRARIES} ${std_msgs_LIBRARIES} ${sensor_msgs_LIBRARIES} ${geometry_msgs_LIBRARIES} ${image_transport_LIBRARIES} ${CUDA_LIBRARIES} ${YAML_CPP_LIBRARIES} ${EXTRA_LIBS} +set(DEPS ${rclcpp_LIBRARIES} ${std_msgs_LIBRARIES} ${sensor_msgs_LIBRARIES} ${image_transport_LIBRARIES} ${CUDA_LIBRARIES} ${YAML_CPP_LIBRARIES} ${EXTRA_LIBS} ${PADDLE_LIB}/paddle/lib/libpaddle_inference.so ${PADDLE_LIB}/paddle/lib/libphi.so ${PADDLE_LIB}/paddle/lib/libcommon.so @@ -89,8 +107,8 @@ ament_target_dependencies(semantic_segmentation std_msgs sensor_msgs cv_bridge - geometry_msgs image_transport OpenCV + perception_utils ) ament_package() diff --git a/src/perception/semantic_segmentation/config/eve_config.yaml b/src/perception/semantic_segmentation/config/eve_config.yaml index 8e9d755b..090c645e 100644 --- a/src/perception/semantic_segmentation/config/eve_config.yaml +++ b/src/perception/semantic_segmentation/config/eve_config.yaml @@ -5,4 +5,4 @@ semantic_segmentation_node: publish_vis_topic: /camera/left/segmentations_viz model_path: /perception_models/semantic_segmentation/pp_liteseg_infer_model/ save_dir: /segmented - save_images: false + save_images: false \ No newline at end of file diff --git a/src/perception/semantic_segmentation/include/semantic_segmentation_node.hpp b/src/perception/semantic_segmentation/include/semantic_segmentation_node.hpp new file mode 100644 index 00000000..1c035ce6 --- /dev/null +++ b/src/perception/semantic_segmentation/include/semantic_segmentation_node.hpp @@ -0,0 +1,58 @@ +#ifndef SEMANTIC_SEGMENTATION_NODE_HPP_ +#define SEMANTIC_SEGMENTATION_NODE_HPP_ + +#include +#include +#include +#include +#include +#include +#include +#include "paddle/include/paddle_inference_api.h" +#include "perception_utils/camera_utils.hpp" +#include "std_msgs/msg/string.hpp" +#include "yaml-cpp/yaml.h" + +struct YamlConfig { + std::string model_file; + std::string params_file; + bool is_normalize; + bool is_resize; + int resize_width; + int resize_height; +}; + +YamlConfig load_yaml(const std::string& yaml_path); + +class SemanticSegmentationNode : public rclcpp::Node { + public: + SemanticSegmentationNode(); + + private: + void image_callback(const sensor_msgs::msg::Image::SharedPtr msg); + std::shared_ptr create_predictor(const YamlConfig& yaml_config); + void process_image(cv::Mat& img, const YamlConfig& yaml_config); + + rclcpp::Subscription::SharedPtr subscription_; + rclcpp::Publisher::SharedPtr image_publisher_; + rclcpp::Publisher::SharedPtr image_viz_publisher_; + int count_; + std::shared_ptr predictor_; + YamlConfig yaml_config_; + + bool FLAGS_use_mkldnn; + bool FLAGS_use_trt; + std::string FLAGS_trt_precision; + bool FLAGS_use_trt_dynamic_shape; + std::string FLAGS_dynamic_shape_path; + std::string FLAGS_devices; + + std::string image_topic; + std::string publish_topic; + std::string publish_vis_topic; + std::string model_path; + std::string save_dir; + bool save_images; +}; + +#endif // SEMANTIC_SEGMENTATION_NODE_HPP_ \ No newline at end of file diff --git a/src/perception/semantic_segmentation/package.xml b/src/perception/semantic_segmentation/package.xml index 59e195ca..3d9a793d 100644 --- a/src/perception/semantic_segmentation/package.xml +++ b/src/perception/semantic_segmentation/package.xml @@ -10,19 +10,14 @@ ament_cmake - ament_lint_auto - ament_lint_common sensor_msgs - geometry_msgs std_msgs OpenCV cv_bridge image_transport + perception_utils rosidl_default_generators rosidl_default_runtime rosidl_interface_packages - - ament_cmake - diff --git a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp index cd55ac5a..96a40c4d 100644 --- a/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp +++ b/src/perception/semantic_segmentation/src/semantic_segmentation_node.cpp @@ -12,7 +12,9 @@ #include "yaml-cpp/yaml.h" #include +#include "perception_utils/camera_utils.hpp" #include "rclcpp/rclcpp.hpp" +#include "semantic_segmentation_node.hpp" #include "std_msgs/msg/string.hpp" using namespace std::chrono_literals; @@ -39,15 +41,6 @@ std::unordered_map> cityscapes_label_colormap = { {16, std::make_tuple(0, 80, 100)}, {17, std::make_tuple(0, 0, 230)}, {18, std::make_tuple(119, 11, 32)}}; -typedef struct YamlConfig { - std::string model_file; - std::string params_file; - bool is_normalize; - bool is_resize; - int resize_width; - int resize_height; -} YamlConfig; - YamlConfig load_yaml(const std::string& yaml_path) { YAML::Node node = YAML::LoadFile(yaml_path); std::string model_file = node["Deploy"]["model"].as(); @@ -69,328 +62,208 @@ YamlConfig load_yaml(const std::string& yaml_path) { return yaml_config; } -class SemanticSegmentationNode : public rclcpp::Node { - public: - bool FLAGS_use_mkldnn = true; - bool FLAGS_use_trt = true; - std::string FLAGS_trt_precision = "fp32"; - bool FLAGS_use_trt_dynamic_shape = true; - std::string FLAGS_dynamic_shape_path = resource_path + "/dynamic_shape.pbtxt"; - std::string FLAGS_devices = "GPU"; - - // ROS Parameters - std::string image_topic; - std::string publish_topic; - std::string publish_vis_topic; - std::string model_path; - std::string save_dir; - bool save_images; - - SemanticSegmentationNode() : Node("semantic_segmentation_node"), count_(0) { - this->declare_parameter("input_topic", "/camera/left/image_color"); - this->declare_parameter("publish_topic", "/camera/left/segmentations"); - this->declare_parameter("publish_vis_topic", "/camera/left/segmentations_viz"); - this->declare_parameter( - "model_path", "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"); - this->declare_parameter("save_dir", "/tmp"); - this->declare_parameter("save_images", false); - - this->get_parameter("input_topic", image_topic); - this->get_parameter("publish_topic", publish_topic); - this->get_parameter("publish_vis_topic", publish_vis_topic); - this->get_parameter("model_path", model_path); - this->get_parameter("save_dir", save_dir); - this->get_parameter("save_images", save_images); - - if (!std::filesystem::exists(save_dir)) { - std::filesystem::create_directories(save_dir); - } +SemanticSegmentationNode::SemanticSegmentationNode() + : Node("semantic_segmentation_node"), count_(0) { + this->declare_parameter("input_topic", "/camera/left/image_color"); + this->declare_parameter("publish_topic", "/camera/left/segmentations"); + this->declare_parameter("publish_vis_topic", "/camera/left/segmentations_viz"); + this->declare_parameter( + "model_path", "/perception_models/semantic_segmentation/pp_liteseg_infer_model/"); + this->declare_parameter("save_dir", "/tmp"); + this->declare_parameter("save_images", false); + + this->get_parameter("input_topic", image_topic); + this->get_parameter("publish_topic", publish_topic); + this->get_parameter("publish_vis_topic", publish_vis_topic); + this->get_parameter("model_path", model_path); + this->get_parameter("save_dir", save_dir); + this->get_parameter("save_images", save_images); + + if (!std::filesystem::exists(save_dir)) { + std::filesystem::create_directories(save_dir); + } - RCLCPP_INFO(this->get_logger(), "subscribing to image_topic: %s", image_topic.c_str()); + yaml_config_ = load_yaml(resource_path + "/deploy.yaml"); - yaml_config_ = load_yaml(resource_path + "/deploy.yaml"); + // Print out the yaml config + RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config_.model_file.c_str()); + RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config_.params_file.c_str()); + RCLCPP_INFO(this->get_logger(), "is_normalize: %d", yaml_config_.is_normalize); + RCLCPP_INFO(this->get_logger(), "is_resize: %d", yaml_config_.is_resize); - // Print out the yaml config - RCLCPP_INFO(this->get_logger(), "model_file: %s", yaml_config_.model_file.c_str()); - RCLCPP_INFO(this->get_logger(), "params_file: %s", yaml_config_.params_file.c_str()); - RCLCPP_INFO(this->get_logger(), "is_normalize: %d", yaml_config_.is_normalize); - RCLCPP_INFO(this->get_logger(), "is_resize: %d", yaml_config_.is_resize); + // Create the paddle predictor + predictor_ = create_predictor(yaml_config_); - // Create the paddle predictor - predictor_ = create_predictor(yaml_config_); + RCLCPP_INFO(this->get_logger(), "subscribing to image_topic: %s", image_topic.c_str()); + // Subscribe to the image topic + subscription_ = this->create_subscription( + image_topic, 10, + std::bind(&SemanticSegmentationNode::image_callback, this, std::placeholders::_1)); - // Subscribe to the image topic - subscription_ = this->create_subscription( - image_topic, 10, - std::bind(&SemanticSegmentationNode::image_callback, this, std::placeholders::_1)); + image_publisher_ = this->create_publisher(publish_topic, 10); + image_viz_publisher_ = this->create_publisher(publish_vis_topic, 10); +} - image_publisher_ = this->create_publisher(publish_topic, 10); - image_viz_publisher_ = this->create_publisher(publish_vis_topic, 10); +void SemanticSegmentationNode::image_callback(const sensor_msgs::msg::Image::SharedPtr msg) { + RCLCPP_INFO(this->get_logger(), "Received image"); + cv::Mat img; + cv::Mat original_img; + + try { + img = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8)->image; + original_img = img.clone(); + } catch (cv_bridge::Exception& e) { + RCLCPP_ERROR(this->get_logger(), "Could not convert from '%s' to 'bgr8'.", + msg->encoding.c_str()); + return; } - void image_callback(const sensor_msgs::msg::Image::SharedPtr msg) { - RCLCPP_INFO(this->get_logger(), "Received image"); - cv::Mat img; - cv::Mat original_img; - - try { - img = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8)->image; - original_img = img.clone(); - } catch (cv_bridge::Exception& e) { - RCLCPP_ERROR(this->get_logger(), "Could not convert from '%s' to 'bgr8'.", - msg->encoding.c_str()); - return; - } - - // Process the image according to yaml config - RCLCPP_INFO(this->get_logger(), "Image shape before process: %d, %d, %d", img.rows, img.cols, - img.channels()); - process_image(img, yaml_config_); - - int rows = img.rows; - int cols = img.cols; - int chs = img.channels(); - RCLCPP_INFO(this->get_logger(), "Image shape after process: %d, %d, %d", rows, cols, chs); - std::vector input_data(1 * chs * rows * cols, 0.0f); - hwc_img_2_chw_data(img, input_data.data()); - - // Set input - auto input_names = predictor_->GetInputNames(); - auto input_t = predictor_->GetInputHandle(input_names[0]); - std::vector input_shape = {1, chs, rows, cols}; - input_t->Reshape(input_shape); - input_t->CopyFromCpu(input_data.data()); - - // Start timing - auto start = std::chrono::high_resolution_clock::now(); - - // Run - predictor_->Run(); - - // Stop timing - auto end = std::chrono::high_resolution_clock::now(); - - // Calculate elapsed time - std::chrono::duration elapsed = end - start; - - // Get output - auto output_names = predictor_->GetOutputNames(); - auto output_t = predictor_->GetOutputHandle(output_names[0]); - std::vector output_shape = output_t->shape(); - int out_num = - std::accumulate(output_shape.begin(), output_shape.end(), 1, std::multiplies()); - std::vector out_data(out_num); - output_t->CopyToCpu(out_data.data()); - - // Get pseudo image - std::vector out_data_u8(out_num); - cv::Mat out_gray_img(output_shape[1], output_shape[2], CV_8UC1, out_data_u8.data()); - cv::Mat colored_img; - // apply cityscapes_labels_colormap to img - cv::cvtColor(out_gray_img, colored_img, cv::COLOR_GRAY2BGR); - for (int i = 0; i < output_shape[1]; i++) { - for (int j = 0; j < output_shape[2]; j++) { - int label = out_data[i * output_shape[2] + j]; - if (cityscapes_labels.find(label) != cityscapes_labels.end()) { - auto [r, g, b] = cityscapes_label_colormap[label]; - colored_img.at(i, j) = cv::Vec3b(b, g, r); - } + // Process the image according to yaml config + RCLCPP_INFO(this->get_logger(), "Image shape before process: %d, %d, %d", img.rows, img.cols, + img.channels()); + process_image(img, yaml_config_); + + int rows = img.rows; + int cols = img.cols; + int chs = img.channels(); + RCLCPP_INFO(this->get_logger(), "Image shape after process: %d, %d, %d", rows, cols, chs); + std::vector input_data(1 * chs * rows * cols, 0.0f); + CameraUtils::hwc_img_2_chw_data(img, input_data.data()); + + // Set input + auto input_names = predictor_->GetInputNames(); + auto input_t = predictor_->GetInputHandle(input_names[0]); + std::vector input_shape = {1, chs, rows, cols}; + input_t->Reshape(input_shape); + input_t->CopyFromCpu(input_data.data()); + + // Start timing + auto start = std::chrono::high_resolution_clock::now(); + + // Run + predictor_->Run(); + + // Stop timing + auto end = std::chrono::high_resolution_clock::now(); + + // Calculate elapsed time + std::chrono::duration elapsed = end - start; + + // Get output + auto output_names = predictor_->GetOutputNames(); + auto output_t = predictor_->GetOutputHandle(output_names[0]); + std::vector output_shape = output_t->shape(); + int out_num = + std::accumulate(output_shape.begin(), output_shape.end(), 1, std::multiplies()); + std::vector out_data(out_num); + output_t->CopyToCpu(out_data.data()); + + // Get pseudo image + std::vector out_data_u8(out_num); + cv::Mat out_gray_img(output_shape[1], output_shape[2], CV_8UC1, out_data_u8.data()); + cv::Mat colored_img; + // apply cityscapes_labels_colormap to img + cv::cvtColor(out_gray_img, colored_img, cv::COLOR_GRAY2BGR); + for (int i = 0; i < output_shape[1]; i++) { + for (int j = 0; j < output_shape[2]; j++) { + int label = out_data[i * output_shape[2] + j]; + if (cityscapes_labels.find(label) != cityscapes_labels.end()) { + auto [r, g, b] = cityscapes_label_colormap[label]; + colored_img.at(i, j) = cv::Vec3b(b, g, r); } } + } - if (save_images) { - std::string filename = save_dir + "/segmented_" + std::to_string(count_) + ".jpg"; - cv::imwrite(filename, colored_img); - RCLCPP_INFO(this->get_logger(), "Saved segmented image to %s", filename.c_str()); - filename = save_dir + "/src_" + std::to_string(count_) + ".jpg"; - cv::imwrite(filename, original_img); - } - count_++; + if (save_images) { + std::string filename = save_dir + "/segmented_" + std::to_string(count_) + ".jpg"; + cv::imwrite(filename, colored_img); + RCLCPP_INFO(this->get_logger(), "Saved segmented image to %s", filename.c_str()); + filename = save_dir + "/src_" + std::to_string(count_) + ".jpg"; + cv::imwrite(filename, original_img); + } + count_++; - RCLCPP_INFO(this->get_logger(), "inference took %f ms", elapsed.count()); + RCLCPP_INFO(this->get_logger(), "inference took %f ms", elapsed.count()); - sensor_msgs::msg::Image::SharedPtr out_gray_img_msg = - cv_bridge::CvImage(msg->header, "mono8", out_gray_img).toImageMsg(); + sensor_msgs::msg::Image::SharedPtr out_gray_img_msg = + cv_bridge::CvImage(msg->header, "mono8", out_gray_img).toImageMsg(); - sensor_msgs::msg::Image::SharedPtr out_img_msg = - cv_bridge::CvImage(msg->header, "bgr8", colored_img).toImageMsg(); + sensor_msgs::msg::Image::SharedPtr out_img_msg = + cv_bridge::CvImage(msg->header, "bgr8", colored_img).toImageMsg(); - image_publisher_->publish(*out_gray_img_msg); - image_viz_publisher_->publish(*out_img_msg); - } + image_publisher_->publish(*out_gray_img_msg); + image_viz_publisher_->publish(*out_img_msg); +} - std::shared_ptr create_predictor(const YamlConfig& yaml_config) { - paddle_infer::Config infer_config; - infer_config.SetModel(model_path + "/" + yaml_config.model_file, - model_path + "/" + yaml_config.params_file); - infer_config.EnableMemoryOptim(); - - if (FLAGS_devices == "CPU") { - RCLCPP_INFO(this->get_logger(), "Use CPU"); - if (FLAGS_use_mkldnn) { - RCLCPP_INFO(this->get_logger(), "Use MKLDNN"); - infer_config.EnableMKLDNN(); - infer_config.SetCpuMathLibraryNumThreads(5); +std::shared_ptr SemanticSegmentationNode::create_predictor( + const YamlConfig& yaml_config) { + paddle_infer::Config infer_config; + infer_config.SetModel(model_path + "/" + yaml_config.model_file, + model_path + "/" + yaml_config.params_file); + infer_config.EnableMemoryOptim(); + + if (FLAGS_devices == "CPU") { + RCLCPP_INFO(this->get_logger(), "Use CPU"); + if (FLAGS_use_mkldnn) { + RCLCPP_INFO(this->get_logger(), "Use MKLDNN"); + infer_config.EnableMKLDNN(); + infer_config.SetCpuMathLibraryNumThreads(5); + } + } else if (FLAGS_devices == "GPU") { + RCLCPP_INFO(this->get_logger(), "Use GPU"); + infer_config.EnableUseGpu(100, 0); + + // TRT config + if (FLAGS_use_trt) { + RCLCPP_INFO(this->get_logger(), "trt_precision: %s", FLAGS_trt_precision.c_str()); + + // TRT precision + if (FLAGS_trt_precision == "fp32") { + infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kFloat32, + false, false); + } else if (FLAGS_trt_precision == "fp16") { + infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kHalf, + false, false); + } else if (FLAGS_trt_precision == "int8") { + infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kInt8, + false, false); + } else { + RCLCPP_ERROR(this->get_logger(), "The trt_precision should be fp32, fp16 or int8."); } - } else if (FLAGS_devices == "GPU") { - RCLCPP_INFO(this->get_logger(), "Use GPU"); - infer_config.EnableUseGpu(100, 0); - - // TRT config - if (FLAGS_use_trt) { - RCLCPP_INFO(this->get_logger(), "trt_precision: %s", FLAGS_trt_precision.c_str()); - - // TRT precision - if (FLAGS_trt_precision == "fp32") { - infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kFloat32, - false, false); - } else if (FLAGS_trt_precision == "fp16") { - infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kHalf, - false, false); - } else if (FLAGS_trt_precision == "int8") { - infer_config.EnableTensorRtEngine(8ULL << 30, 1, 3, paddle_infer::PrecisionType::kInt8, - false, false); - } else { - RCLCPP_ERROR(this->get_logger(), "The trt_precision should be fp32, fp16 or int8."); - } - // TRT dynamic shape - if (FLAGS_use_trt_dynamic_shape) { - RCLCPP_INFO(this->get_logger(), "Enable TRT dynamic shape"); - RCLCPP_INFO(this->get_logger(), "dynamic_shape_path: %s", - FLAGS_dynamic_shape_path.c_str()); - if (FLAGS_dynamic_shape_path.empty()) { - std::map> min_input_shape = {{"image", {1, 3, 112, 112}}}; - std::map> max_input_shape = { - {"image", {1, 3, 1024, 2048}}}; - std::map> opt_input_shape = { - {"image", {1, 3, 512, 1024}}}; - infer_config.SetTRTDynamicShapeInfo(min_input_shape, max_input_shape, opt_input_shape); - } else { - infer_config.EnableTunedTensorRtDynamicShape(FLAGS_dynamic_shape_path, true); - } + // TRT dynamic shape + if (FLAGS_use_trt_dynamic_shape) { + RCLCPP_INFO(this->get_logger(), "Enable TRT dynamic shape"); + RCLCPP_INFO(this->get_logger(), "dynamic_shape_path: %s", FLAGS_dynamic_shape_path.c_str()); + if (FLAGS_dynamic_shape_path.empty()) { + std::map> min_input_shape = {{"image", {1, 3, 112, 112}}}; + std::map> max_input_shape = {{"image", {1, 3, 1024, 2048}}}; + std::map> opt_input_shape = {{"image", {1, 3, 512, 1024}}}; + infer_config.SetTRTDynamicShapeInfo(min_input_shape, max_input_shape, opt_input_shape); + } else { + infer_config.EnableTunedTensorRtDynamicShape(FLAGS_dynamic_shape_path, true); } } - } else { - RCLCPP_ERROR(this->get_logger(), "The devices should be GPU or CPU"); - } - - auto predictor = paddle_infer::CreatePredictor(infer_config); - return predictor; - } - - void hwc_img_2_chw_data(const cv::Mat& hwc_img, float* data) { - int rows = hwc_img.rows; - int cols = hwc_img.cols; - int chs = hwc_img.channels(); - for (int i = 0; i < chs; ++i) { - cv::extractChannel(hwc_img, cv::Mat(rows, cols, CV_32FC1, data + i * rows * cols), i); - } - } - - // Function to resize an image while maintaining aspect ratio - cv::Mat resizeImageAspectRatio(const cv::Mat& originalImage, int maxWidth, int maxHeight) { - int originalWidth = originalImage.cols; - int originalHeight = originalImage.rows; - double originalAspectRatio = (double)originalWidth / originalHeight; - - int newWidth, newHeight; - double maxAspectRatio = (double)maxWidth / maxHeight; - - if (originalAspectRatio > maxAspectRatio) { - // Width is the limiting factor - newWidth = maxWidth; - newHeight = static_cast(maxWidth / originalAspectRatio); - } else { - // Height is the limiting factor - newHeight = maxHeight; - newWidth = static_cast(maxHeight * originalAspectRatio); } - - cv::Mat resizedImage; - cv::resize(originalImage, resizedImage, cv::Size(newWidth, newHeight)); - - return resizedImage; - } - - cv::Mat resizeWithPadding(const cv::Mat& originalImage, int targetWidth, int targetHeight) { - int originalWidth = originalImage.cols; - int originalHeight = originalImage.rows; - - double targetRatio = (double)targetWidth / targetHeight; - double originalRatio = (double)originalWidth / originalHeight; - - int newWidth, newHeight; - - if (originalRatio > targetRatio) { - // Original is wider. Fit to width and pad height. - newWidth = targetWidth; - newHeight = - static_cast(originalHeight * (static_cast(targetWidth) / originalWidth)); - } else { - // Original is taller. Fit to height and pad width. - newHeight = targetHeight; - newWidth = - static_cast(originalWidth * (static_cast(targetHeight) / originalHeight)); - } - - cv::Mat resizedImage; - cv::resize(originalImage, resizedImage, cv::Size(newWidth, newHeight)); - - int top = (targetHeight - newHeight) / 2; - int bottom = targetHeight - newHeight - top; - int left = (targetWidth - newWidth) / 2; - int right = targetWidth - newWidth - left; - - cv::Mat paddedImage; - cv::copyMakeBorder(resizedImage, paddedImage, top, bottom, left, right, cv::BORDER_CONSTANT, - cv::Scalar(0, 0, 0)); - - return paddedImage; + } else { + RCLCPP_ERROR(this->get_logger(), "The devices should be GPU or CPU"); } - cv::Mat resizeFromCenter(const cv::Mat& originalImage, int targetWidth, int targetHeight) { - int originalWidth = originalImage.cols; - int originalHeight = originalImage.rows; - - // Calculate the new height maintaining the aspect ratio - double targetRatio = (double)targetWidth / targetHeight; - int newHeight = static_cast(originalWidth / targetRatio); - - // Calculate the cropping area - int startY = (originalHeight - newHeight) / 2; - - // Crop the image from the center - cv::Rect roi(0, startY, originalWidth, newHeight); - cv::Mat croppedImage = originalImage(roi); - - // Resize the cropped image - cv::Mat resizedImage; - cv::resize(croppedImage, resizedImage, cv::Size(targetWidth, targetHeight)); + auto predictor = paddle_infer::CreatePredictor(infer_config); + return predictor; +} - return resizedImage; +void SemanticSegmentationNode::process_image(cv::Mat& img, const YamlConfig& yaml_config) { + img = CameraUtils::resize_from_center(img, 2048, 1024); + cv::cvtColor(img, img, cv::COLOR_BGR2RGB); + if (yaml_config.is_resize) { + cv::resize(img, img, cv::Size(yaml_config.resize_width, yaml_config.resize_height)); } - - void process_image(cv::Mat& img, const YamlConfig& yaml_config) { - img = resizeFromCenter(img, 2048, 1024); - cv::cvtColor(img, img, cv::COLOR_BGR2RGB); - if (yaml_config.is_resize) { - cv::resize(img, img, cv::Size(yaml_config.resize_width, yaml_config.resize_height)); - } - if (yaml_config.is_normalize) { - img.convertTo(img, CV_32F, 1.0 / 255, 0); - img = (img - 0.5) / 0.5; - } + if (yaml_config.is_normalize) { + img.convertTo(img, CV_32F, 1.0 / 255, 0); + img = (img - 0.5) / 0.5; } - - private: - rclcpp::Subscription::SharedPtr subscription_; - rclcpp::Publisher::SharedPtr image_publisher_; - rclcpp::Publisher::SharedPtr image_viz_publisher_; - int count_; - std::shared_ptr predictor_; - YamlConfig yaml_config_; -}; +} int main(int argc, char* argv[]) { rclcpp::init(argc, argv); From a84fb8f8bc1522c945e67cdfbcfc580ba15e2b38 Mon Sep 17 00:00:00 2001 From: JohnTurco Date: Wed, 3 Apr 2024 00:28:56 +0000 Subject: [PATCH 12/12] Turned off inline-cache --- .github/templates/docker_context/docker_context.sh | 6 ------ .github/workflows/build_and_unitest.yml | 3 --- 2 files changed, 9 deletions(-) diff --git a/.github/templates/docker_context/docker_context.sh b/.github/templates/docker_context/docker_context.sh index e8dc0d1f..126b5cb2 100755 --- a/.github/templates/docker_context/docker_context.sh +++ b/.github/templates/docker_context/docker_context.sh @@ -36,12 +36,6 @@ while read -r module; do # Loop through each service while read -r service_out; do - # Temporarily skip perception services that have too large image size - if [[ "$service_out" == "lane_detection" ]] || \ - [[ "$service_out" == "camera_object_detection" ]] || \ - [[ "$service_out" == "semantic_segmentation" ]]; then - continue - fi # Construct JSON object for each service with module and service name json_object=$(jq -nc --arg module_out "$module_out" --arg service_out "$service_out" \ '{module: $module_out, service: $service_out}') diff --git a/.github/workflows/build_and_unitest.yml b/.github/workflows/build_and_unitest.yml index 214815b1..ca93daf6 100644 --- a/.github/workflows/build_and_unitest.yml +++ b/.github/workflows/build_and_unitest.yml @@ -96,7 +96,6 @@ jobs: cache-from: | ${{ steps.construct-registry-url.outputs.url }}:source_${{ env.SOURCE_BRANCH }} ${{ steps.construct-registry-url.outputs.url }}:source_${{ env.TARGET_BRANCH }} - cache-to: type=inline builder: ${{ steps.buildx.outputs.name }} target: dependencies @@ -112,7 +111,6 @@ jobs: ${{ steps.construct-registry-url.outputs.url }}:source_${{ env.SOURCE_BRANCH }} ${{ steps.construct-registry-url.outputs.url }}:build_${{ env.SOURCE_BRANCH }} ${{ steps.construct-registry-url.outputs.url }}:build_${{ env.TARGET_BRANCH }} - cache-to: type=inline builder: ${{ steps.buildx.outputs.name }} target: build @@ -135,7 +133,6 @@ jobs: env: DOCKER_BUILDKIT: 1 COMPOSE_DOCKER_CLI_BUILD: 1 - BUILDKIT_INLINE_CACHE: 1 with: image: ${{ steps.construct-registry-url.outputs.url }} tag: build_${{ env.SOURCE_BRANCH }}

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