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Merge pull request #22 from Ar-Ray-code/feature/yolox_py_update
Feature/yolox py update (v0.3.1)
2 parents 1ca9482 + 5989847 commit 3f50e35

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-313
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‎README.md‎

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@@ -10,9 +10,9 @@
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| Base | ROS2 C++ | ROS2 Python |
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| --------------- | -------- | ----------- |
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| CPU | | ✅ |
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| CUDA | | ✅ |
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| CUDA (FP16) | | ✅ |
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| PyTorch | | ✅ |
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| PyTorch(CUDA) | | ✅ |
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| PyTorch(CUDA-FP16) | | ✅ |
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| TensorRT (CUDA) | ✅ | |
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| OpenVINO | ✅ | ✅ |
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| ONNX Runtime | | ✅ |
@@ -124,7 +124,7 @@ Check [this URL](https://github.com/Ar-Ray-code/YOLOX-ROS/tree/main/yolox_ros_cp
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<!-- - yolox/image_raw : Resized image (`sensor_msgs/Image`) -->
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- yololx/bounding_boxes : Output BoundingBoxes like darknet_ros_msgs (`bboxes_ex_msgs/BoundingBoxes`)
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- bounding_boxes: Output BoundingBoxes like darknet_ros_msgs (`bboxes_ex_msgs/BoundingBoxes`)
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※ If you want to use `darknet_ros_msgs` , replace `bboxes_ex_msgs` with `darknet_ros_msgs`.
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yolox_ros_py/launch/yolox_tflite.launch.py renamed to yolox_ros_py/launch/yolox_lite_tflite_camera.launch.py

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@@ -37,8 +37,8 @@ def generate_launch_description():
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yolox_tflite = launch_ros.actions.Node(
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package="yolox_ros_py", executable="yolox_tflite",output="screen",
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parameters=[
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{"model" : yolox_ros_share_dir+"/model.tflite"},
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{"score_th" : 0.4},
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{"model_path" : yolox_ros_share_dir+"/model.tflite"},
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{"conf" : 0.4},
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{"nms_th" : 0.5},
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{"input_shape/height" : 192},
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{"input_shape/width" : 192}

yolox_ros_py/launch/yolox_nano_onnx.launch.py renamed to yolox_ros_py/launch/yolox_nano_onnx_camera.launch.py

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@@ -28,9 +28,6 @@ def generate_launch_description():
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yolox_onnx = launch_ros.actions.Node(
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package="yolox_ros_py", executable="yolox_onnx",output="screen",
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parameters=[
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{"image_size/width": 640},
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{"image_size/height": 480},
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{"input_shape/width": 416},
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{"input_shape/height": 416},
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‎yolox_ros_py/launch/yolox_nano_onnx_gazebo.launch.py‎

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yolox_onnx = launch_ros.actions.Node(
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package="yolox_ros_py", executable="yolox_onnx",output="screen",
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parameters=[
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{"image_size/width": 640},
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{"image_size/height": 480},
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{"input_shape/width": 416},
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{"input_shape/height": 416},
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‎yolox_ros_py/launch/yolox_nano_onnx_picture.launch.py‎

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from matplotlib import image
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import launch
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import launch_ros.actions
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from launch.actions import DeclareLaunchArgument
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from ament_index_python.packages import get_package_share_directory
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from launch.launch_description_sources import PythonLaunchDescriptionSource
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from launch.substitutions import LaunchConfiguration
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from urllib.request import urlretrieve
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import os
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def generate_launch_description():
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yolox_ros_share_dir = get_package_share_directory('yolox_ros_py')
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dog_path = os.path.join(yolox_ros_share_dir, "./", "dog.jpg")
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url = "https://raw.githubusercontent.com/pjreddie/darknet/master/data/dog.jpg"
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if not os.path.exists(dog_path):
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os.system("wget {} -O {}".format(url, dog_path))
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image_path = LaunchConfiguration('image_path', default=dog_path)
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image_path_arg = DeclareLaunchArgument(
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'image_path',
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default_value=dog_path,
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description='Image path'
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)
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image_pub = launch_ros.actions.Node(
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package='image_publisher',
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executable='image_publisher_node',
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name='image_publisher',
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arguments=[image_path],
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)
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yolox_onnx = launch_ros.actions.Node(
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package="yolox_ros_py", executable="yolox_onnx",output="screen",
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parameters=[
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{"input_shape/width": 416},
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{"input_shape/height": 416},
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{"with_p6" : False},
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{"model_path" : yolox_ros_share_dir+"/yolox_nano.onnx"},
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{"conf" : 0.3},
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],
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)
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rqt_graph = launch_ros.actions.Node(
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package="rqt_graph", executable="rqt_graph",
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)
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return launch.LaunchDescription([
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image_path_arg,
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image_pub,
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yolox_onnx,
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# rqt_graph
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])

‎yolox_ros_py/launch/yolox_nano_onnx_youtube.launch.py‎

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from launch.launch_description_sources import PythonLaunchDescriptionSource
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import launch_ros
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def generate_launch_description():
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yolox_ros_share_dir = get_package_share_directory('yolox_ros_py')
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youtube_publisher_share_dir = get_package_share_directory('youtube_publisher')
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yolox_onnx = launch_ros.actions.Node(
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package="yolox_ros_py", executable="yolox_onnx",output="screen",
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parameters=[
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{"image_size/width": 640},
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{"image_size/height": 360},
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{"input_shape/width": 416},
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{"input_shape/height": 416},
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‎yolox_ros_py/launch/yolox_nano_openvino.launch.py‎

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yolox_openvino = launch_ros.actions.Node(
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package="yolox_ros_py", executable="yolox_openvino",output="screen",
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parameters=[
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{"image_size/width": 640},
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{"image_size/height": 480},
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{"device" : 'CPU'},
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{"model_path" : yolox_ros_share_dir+"/yolox_nano.onnx"},
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{"conf" : 0.3},

yolox_ros_py/launch/yolox_nano_cpu.launch.py renamed to yolox_ros_py/launch/yolox_nano_torch_cpu_camera.launch.py

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yolox_ros = launch_ros.actions.Node(
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package="yolox_ros_py", executable="yolox_ros",
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parameters=[
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{"image_size/width": 640},
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{"image_size/height": 480},
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{"yolox_exp_py" : yolox_ros_share_dir+'/yolox_nano.py'},
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{"device" : 'cpu'},
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{"fp16" : True},

yolox_ros_py/launch/yolox_nano.launch.py renamed to yolox_ros_py/launch/yolox_nano_torch_gpu_camera.launch.py

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from launch.launch_description_sources import PythonLaunchDescriptionSource
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from launch.substitutions import LaunchConfiguration
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from urllib.request import urlretrieve
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import os
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def generate_launch_description():
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yolox_ros_share_dir = get_package_share_directory('yolox_ros_py')
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yolox_ros = launch_ros.actions.Node(
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package="yolox_ros_py", executable="yolox_ros",
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parameters=[
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{"image_size/width": 640},
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{"image_size/height": 480},
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{"yolox_exp_py" : yolox_ros_share_dir+'/yolox_nano.py'},
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{"device" : 'gpu'},
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{"fp16" : True},

‎yolox_ros_py/package.xml‎

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<?xml-model href="http://download.ros.org/schema/package_format3.xsd" schematypens="http://www.w3.org/2001/XMLSchema"?>
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<package format="3">
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<name>yolox_ros_py</name>
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<version>0.3.0</version>
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<version>0.3.1</version>
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<description>The yolox_ros_py package</description>
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<maintainer email="[email protected]">Ar-Ray-code</maintainer>
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<license>Apache License, Version 2.0</license>

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