Update dockerfile and README.

README.md

@@ -50,6 +50,8 @@ COCO models:
 
 See [INSTALL.md](INSTALL.md).
 
+Optionally, you can use the official [Dockerfile](docker) to set up full enivronment with one command.
+
 ## Getting Started
 
 Follow the [installation instructions](INSTALL.md) to set up required environment for running YolactEdge.

docker/Dockerfile

@@ -1,93 +1,43 @@
 FROM nvcr.io/nvidia/cuda:11.0.3-cudnn8-devel-ubuntu18.04
 
-#installation settings
-ARG APT_INSTALL="apt-get install -y --no-install-recommends"
-ARG PIP_INSTALL="python3 -m pip --no-cache-dir install --upgrade --user"
-ARG GIT_CLONE="git clone --depth 10"
-
-#user settings
-ARG USER=docker
-ARG UID=1000
-ARG GID=1000
-ARG PW=user
-
-# Add user and his password
-RUN useradd -m ${USER} --uid=${UID} \
-    && echo "${USER}:${PW}" | chpasswd \
-    && usermod -s /bin/bash ${USER}
-
+ARG DEBIAN_FRONTEND=noninteractive
+RUN apt-get update && apt-get install -y  \
+    git wget sudo build-essential \
+    python3 python3-setuptools python3-pip python3-dev python3-tk \
+    ffmpeg libsm6 libxext6
+RUN ln -svf /usr/bin/python3 /usr/bin/python
+RUN python -m pip install --upgrade --force pip
+
+# TensorRT
+ARG version="8.0.5.39-1+cuda11.0"
+RUN apt-get update && apt-get install -y libcudnn8=${version} libcudnn8-dev=${version} && apt-mark hold libcudnn8 libcudnn8-dev
+ARG version="7.2.3-1+cuda11.0"
+RUN apt-get update && \
+    apt-get install -y libnvinfer7=${version} libnvonnxparsers7=${version} libnvparsers7=${version} libnvinfer-plugin7=${version} libnvinfer-dev=${version} libnvonnxparsers-dev=${version} libnvparsers-dev=${version} libnvinfer-plugin-dev=${version} python3-libnvinfer=${version} && \
+    apt-mark hold libnvinfer7 libnvonnxparsers7 libnvparsers7 libnvinfer-plugin7 libnvinfer-dev libnvonnxparsers-dev libnvparsers-dev libnvinfer-plugin-dev python3-libnvinfer
+
+# create a non-root user
+ARG USER_ID=1000
+ARG USER=appuser
+RUN useradd -m --no-log-init --system --uid ${USER_ID} ${USER} -g sudo
+RUN echo '%sudo ALL=(ALL) NOPASSWD:ALL' >> /etc/sudoers
+USER ${USER}
 WORKDIR /home/${USER}
+ENV PATH="/home/${USER}/.local/bin:${PATH}"
 
-#tools
-RUN apt-get update && $APT_INSTALL \
-    nano \
-    git \
-    python3 \
-    python3-setuptools \
-    python3-pip \
-    python3-dev \
-    build-essential \
-    ffmpeg \
-    libsm6 \
-    libxext6 && \
-    pip3 install --upgrade pip 
-
-RUN $PIP_INSTALL \
-    cython \
-    opencv-python \
-    pillow \
-    matplotlib \
-    GitPython \
-    termcolor \
-    tensorboard
-
-RUN $PIP_INSTALL git+https://github.com/haotian-liu/cocoapi.git#"egg=pycocotools&subdirectory=PythonAPI"
-
-#pytorch  
-RUN $PIP_INSTALL torch==1.7.1+cu110 \
-                 torchvision==0.8.2+cu110 \
-                 -f https://download.pytorch.org/whl/torch_stable.html
-
-#install TensorRT packages
-ENV version="8.0.5.39-1+cuda11.0"
-RUN apt-get update && $APT_INSTALL \
-                    libcudnn8=${version} \
-                    libcudnn8-dev=${version} && \
-                    apt-mark hold libcudnn8 libcudnn8-dev
-
-ENV version="7.2.3-1+cuda11.0"
-RUN apt-get update && $APT_INSTALL \
-                libnvinfer7=${version} \ 
-                libnvonnxparsers7=${version} \
-                libnvparsers7=${version} \
-                libnvinfer-plugin7=${version} \
-                libnvinfer-dev=${version} \
-                libnvonnxparsers-dev=${version} \
-                libnvparsers-dev=${version} \
-                libnvinfer-plugin-dev=${version} \
-                python-libnvinfer=${version} \
-                python3-libnvinfer=${version} && \
-                apt-mark hold libnvinfer7 \
-                libnvonnxparsers7 \
-                libnvparsers7 \
-                libnvinfer-plugin7 \
-                libnvinfer-dev \ 
-                libnvonnxparsers-dev \
-                libnvparsers-dev \
-                libnvinfer-plugin-dev \
-                python-libnvinfer \
-                python3-libnvinfer
-
-#clone and compile torch2trt
-RUN $GIT_CLONE https://github.com/NVIDIA-AI-IOT/torch2trt
+# # Install dependencies
+RUN pip install --user cython opencv-python pillow matplotlib GitPython termcolor tensorboard
+RUN pip install --user git+https://github.com/haotian-liu/cocoapi.git#"egg=pycocotools&subdirectory=PythonAPI"
+RUN pip install --user torch==1.7.1+cu110 torchvision==0.8.2+cu110 -f https://download.pytorch.org/whl/torch_stable.html
 
+# torch2trt
+RUN git clone https://github.com/NVIDIA-AI-IOT/torch2trt
 WORKDIR /home/${USER}/torch2trt
-RUN python3 setup.py install --plugins
-
-#cleaning
-RUN apt-get clean && \
-    apt-get autoremove && \
-    rm -rf /var/lib/apt/lists/* /tmp/*
+RUN python setup.py install --plugins --user
 
-#start path
+WORKDIR /home/${USER}
+RUN ln -s /yolact_edge
+RUN ln -s /datasets
 WORKDIR /home/${USER}/yolact_edge
+
+ENV LANG C.UTF-8

docker/README.md

@@ -1,14 +1,11 @@
-Each step starts from the `yolact_edge` folder:
-- Build:
+## Use the container
 
-`cd docker`
+```Shell
+cd docker/
 
-`./build.sh`
-- Start work:
-``./docker/start.sh `pwd` <path to dataset on your computer>`` (dataset will be available inside the container in a /datasets folder)
+# Build:
+docker build --build-arg USER_ID=$UID -t yolact_edge_image .
 
-
-Connect to runnig container (if you need more than one terminal to the container):
-`./docker/into.sh`
-
-Container uses `yolact_edge` folder as docker volume, so all your modifications will be save after closing session.
+# Launch (with GPUs):
+./start.sh /path/to/yolact_edge /path/to/datasets
+```

docker/start.sh

@@ -1,13 +1,10 @@
 #!/bin/bash
 
-SOURCE=$1
+SOURCE_CODE=$1
 DATASETS=$2
-#for example from yolact_edge folder ./docker/start.sh `pwd` <path_to_datasets>
 
-docker run --rm \
-	   -ti \
-           --name yolact_edge \
-           --gpus all \
-           -v $SOURCE:/home/docker/yolact_edge/:rw \
-           -v $DATASETS:/datasets/:ro \
-           yolact_edge_image
+docker run --gpus all -it --name=yolact_edge \
+  --shm-size=8gb --env="DISPLAY" --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
+  -v $SOURCE_CODE:/yolact_edge/:rw \
+  -v $DATASETS:/datasets/:ro \
+  yolact_edge_image