qyup/sm-3d-camera-control repository overview

⁠sm-3d-camera-control Docker Image

This Docker image provides a pre-configured environment for controlling 3D cameras and processing images, specifically designed for use with the Supermaker AI Qwen Image Multiple Angles project. It includes all necessary dependencies, libraries, and configurations to seamlessly integrate with the Supermaker AI platform and facilitate research, development, and deployment of 3D camera control applications. This image simplifies the setup process, eliminating compatibility issues and accelerating the development workflow for users working with 3D camera systems and AI-powered image analysis.

This image is built on a lightweight Ubuntu base and includes pre-installed Python 3.10, CUDA 11.8, PyTorch 1.13, OpenCV, and other essential libraries optimized for 3D camera control. It also contains example scripts and configuration files to enable immediate experimentation and integration with your own projects. The image is designed for performance and efficiency, ensuring optimal resource utilization when running complex image processing and 3D reconstruction algorithms.

⁠How to run

To run the sm-3d-camera-control Docker image, use the following command: bash docker run --gpus all -it --rm
-v /path/to/your/data:/data
-p 8888:8888
supermakerai/sm-3d-camera-control:latest

Explanation:

• docker run: Starts a new container.
• --gpus all: Enables access to all available GPUs within the container (required for CUDA acceleration). Remove if you do not have a GPU.
• -it: Runs the container in interactive mode with a pseudo-TTY allocated.
• --rm: Automatically removes the container when it exits.
• -v /path/to/your/data:/data: Mounts a local directory (/path/to/your/data) to the container's /data directory. This allows you to share data between your host machine and the container. Replace /path/to/your/data with the actual path to your data directory.
• -p 8888:8888: Maps port 8888 on the host machine to port 8888 on the container. This is useful for accessing services running inside the container, such as Jupyter Notebook.
• supermakerai/sm-3d-camera-control:latest: Specifies the Docker image to use.

Running with Jupyter Notebook:

If you want to run Jupyter Notebook within the container, you can use the following command: bash docker run --gpus all -it --rm
-v /path/to/your/data:/data
-p 8888:8888
supermakerai/sm-3d-camera-control:latest
jupyter notebook --ip 0.0.0.0 --port 8888 --allow-root

After running this command, you can access Jupyter Notebook in your browser by navigating to http://localhost:8888.

Important Considerations:

• Ensure you have Docker and the NVIDIA Container Toolkit installed on your system.
• Replace /path/to/your/data with the actual path to the directory containing your 3D camera data and project files.
• This container is optimized for integration with the Supermaker AI ecosystem, as described in the blog post available at https://supermaker.ai/blog/qwen-image-multiple-angles-3d-camera-alibabas-breakthrough-in-ai-camera-control/⁠.