Docker image for quick test, chatgpt generating docker command , is it right?

[yangjun1222]

Creating a Docker setup for this project on Ubuntu 22.04 involves writing a Dockerfile and using docker build and docker run commands to containerize the environment. Here's a step-by-step guide:

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1. Write a Dockerfile

The Dockerfile sets up the environment for the project, including Python, OpenCV, Node.js, and the required libraries.

# Use Ubuntu 22.04 as the base image
FROM ubuntu:22.04

# Set environment variables to prevent interactive prompts during apt installs
ENV DEBIAN_FRONTEND=noninteractive

# Update the package list and install system dependencies
RUN apt-get update && apt-get install -y \
    python3 python3-pip python3-venv \
    git \
    build-essential cmake \
    libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev \
    nodejs npm \
    && apt-get clean && rm -rf /var/lib/apt/lists/*

# Install Yarn globally
RUN npm install --global yarn

# Clone the repositories
WORKDIR /opt
RUN git clone https://github.com/opencv/opencv.git
RUN git clone https://github.com/opencv/opencv_contrib.git
RUN git clone https://github.com/bensondaled/pseyepy.git
RUN git clone https://github.com/jyjblrd/Low-Cost-Mocap.git

# Build and install OpenCV with contrib modules
WORKDIR /opt/opencv_build
RUN cmake -D CMAKE_BUILD_TYPE=Release \
          -D OPENCV_EXTRA_MODULES_PATH=/opt/opencv_contrib/modules \
          -D BUILD_opencv_sfm=ON \
          ../opencv \
    && make -j$(nproc) \
    && make install \
    && ldconfig

# Install Python dependencies
WORKDIR /opt/pseyepy
RUN pip3 install .

# Set up the Low-Cost-Mocap project
WORKDIR /opt/Low-Cost-Mocap/computer_code
RUN yarn install

# Expose ports for the web server
EXPOSE 3000

# Default command to start the services
CMD ["sh", "-c", "yarn run dev & python3 /opt/Low-Cost-Mocap/api/index.py"]

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2. Build the Docker Image

Save the Dockerfile in the root of your project directory and build the Docker image:

docker build -t low-cost-mocap .

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3. Run the Docker Container

Run the container, mapping the necessary ports:

docker run -p 3000:3000 -it low-cost-mocap

• -p 3000:3000: Maps the container’s port 3000 (web server) to the host system.
• -it: Runs the container interactively.

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4. Access the Application

• Frontend: Open your browser and navigate to http://localhost:3000.
• Backend: The backend runs automatically alongside the frontend, processing camera streams and computations.

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5. Verify and Debug

If something doesn't work as expected:

• Check container logs:

  docker logs <container_id>

• Access the container shell for debugging:

  docker exec -it <container_id> /bin/bash

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Let me know if you need additional help with any step!