Anaconda Jupyter Notebook with YOLOv8 in Docker 🐳📓

Welcome to our guide on setting up an Anaconda Jupyter Notebook environment for running YOLOv8, fully equipped with NVIDIA GeForce RTX 3090 Ti GPU support! 🚀

Prerequisites 📋

Before you begin, make sure you have the following:

• NVIDIA GPU drivers installed on your system (we're using an NVIDIA GeForce RTX 3090 Ti).
• Docker and NVIDIA-Docker installed.
• Basic knowledge of Docker and Jupyter Notebooks.

Installation 🛠️

Step 1: Clone the Repository

Clone this repository to your local machine using:

git clone [URL-to-this-repository]
cd [Repository-Name]

Step 2: Build the Docker Image

To build the Docker image with Anaconda and Jupyter Notebook, run:

docker build -t yolo-notebook .

This will create an image named yolo-notebook containing Anaconda, Jupyter Notebook, and all the necessary dependencies for YOLOv8.

Step 3: Run the Docker Container

Start the container with GPU support:

docker run --gpus all -p 8888:8888 -v $(pwd)/notebooks:/workspace/notebooks yolo-notebook

This command will start a Jupyter Notebook server, mapping the container's port 8888 to your local port 8888, and mount a local notebooks directory to the container.

Using Jupyter Notebook 📔

After starting the container, you'll see a URL in your terminal. Copy and paste this URL into your web browser to access the Jupyter Notebook interface.

In the Jupyter interface, navigate to the notebooks directory where you can create new notebooks or open existing ones.

Running YOLOv8 🔍

To run YOLOv8 in a Jupyter Notebook:

1. Open a new notebook in the Jupyter interface.
2. Import necessary libraries and load your YOLOv8 model.
3. Run your object detection tasks as required.

---

Troubleshooting 🛠

• GPU not recognized: Ensure NVIDIA drivers and NVIDIA-Docker are properly installed.
• Docker build issues: Check the Dockerfile for any errors or missing dependencies.
• Jupyter Notebook access issues: Ensure the Docker container is running and the port mapping is correct.

Contribution and Support 🤝

Contributions to this project are welcome! Please submit pull requests or open issues for any improvements or suggestions.

For support, please open an issue in this repository.

License 📜

This project is licensed under [LICENSE-NAME]. See the LICENSE file for details.