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Merge pull request #7 from Ar-Ray-code/humble-devel
Humble devel
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Dockerfile

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FROM nvidia/cuda:11.4.2-cudnn8-devel-ubuntu20.04
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FROM nvidia/cuda:11.7.0-devel-ubuntu22.04
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ENV TZ=Asia/Tokyo
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RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
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echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] http://packages.ros.org/ros2/ubuntu $(lsb_release -cs) main" | tee /etc/apt/sources.list.d/ros2.list > /dev/null && \
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apt update && \
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apt install -y -o Dpkg::Options::="--force-confdef" -o Dpkg::Options::="--force-confold" keyboard-configuration && \
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apt install -y ros-foxy-desktop && \
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apt install -y ros-humble-desktop && \
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apt install -y python3-colcon-common-extensions && \
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apt install -y ros-foxy-v4l2-camera && \
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apt install -y ros-humble-v4l2-camera && \
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apt install -y git && \
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apt install -y xterm && \
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apt install -y wget && \

README.md

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# darknet-ros-fp16
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darknet_ros + ROS2 Galactic + OpenCV4 + CUDA 11.2 + __CUDNN (FP16)__ :fire::fire::fire:
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darknet_ros + ROS2 Humble + OpenCV4 + CUDA 11.2 + __CUDNN (FP16)__ :fire::fire::fire:
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- [English (GitHub Wiki)](https://github.com/Ar-Ray-code/darknet_ros_fp16/wiki/Darknet_ros_FP16-Report-(1.3x-faster)-%F0%9F%94%A5)
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- [Japanese (zenn)](https://zenn.dev/array/articles/4c82fc8382e62d)
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- Ubuntu Desktop + NVIDIA Graphics Driver
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- v4l2-camera (Connect to `/dev/video*`)
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- NVIDIA Graphics Card (Volta , Turing , Ampere)
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- Docker + [NVIDIA-Docker](https://github.com/NVIDIA/nvidia-docker)
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- NVIDIA Graphics Card (Volta , Turing , Ampere)
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- Docker + [NVIDIA-Docker](https://github.com/NVIDIA/nvidia-docker)
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- This docker image is using `cuda:11.4.2` .
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- xhost (To install xhost , run `$ sudo apt install xorg` .)
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xhost +
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# Pull docker image from dockerhub
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docker pull ray255ar/darknet-ros-fp16
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# Run
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# Run
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docker run --rm -it \
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--device /dev/video0:/dev/video0:mwr \
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-e DISPLAY=$DISPLAY --runtime nvidia \
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## Installation :turtle:
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### Requirements
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- ROS2 Foxy
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- ROS2 Humble
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- OpenCV 4.2
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- CUDA 10 or 11 (tested with CUDA 11.5.119)
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- cuDNN 8.3 ([Installation tutorial](https://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html))
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- CUDA 10 or 11 (tested with CUDA 11.7)
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- cuDNN 8 ([Installation tutorial](https://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html))
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### Installation
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```bash
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$ sudo apt install ros-foxy-desktop ros-foxy-v4l2-camera
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$ source /opt/ros/foxy/setup.bash
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$ sudo apt install ros-humble-desktop ros-humble-v4l2-camera
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$ source /opt/ros/humble/setup.bash
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$ mkdir -p ~/ros2_ws/src
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$ cd ~/ros2_ws/src
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$ git clone --recursive https://github.com/Ar-Ray-code/darknet_ros_yolov4.git
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#### cuDNN (FP16)
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Darknet can be made even faster by enabling CUDNN_HALF(FP16), but you need to specify the appropriate architecture.
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Darknet can be made even faster by enabling CUDNN_HALF(FP16), but you need to specify the appropriate architecture.
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FP16 is automatically enabled for GPUs of the Turing or Ampere architecture if the appropriate cuDNN is installed. To disable it, change line 12 to `set(FP16_ENABLE OFF)`.
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Connect your webcam to your PC.
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```bash
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$ source /opt/ros/foxy/setup.bash
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$ source /opt/ros/humble/setup.bash
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$ source ~/ros2_ws/install/local_setup.bash
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$ ros2 launch darknet_ros demo-v4-tiny.launch.py
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```

yolov4-tiny-docker.bash

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#!/bin/bash
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source /opt/ros/foxy/setup.bash
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source /opt/ros/humble/setup.bash
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source /usr/share/colcon_argcomplete/hook/colcon-argcomplete.bash
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colcon build --symlink-install
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source install/setup.bash

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