tensorflow keras jupyter notebooks docker install for mac pc

Tensorflow Keras Jupyter Notebooks Docker Pc Code Helps Us

We tested our installation through a real-time object detector.

Reda Data Scientist 7 min read Docker is the best platform to easily install Tensorflow with a GPU.

This tutorial aims demonstrate this and test it on a real-time object recognition application.

Docker Image for Tensorflow with GPU Docker is a tool which allows us to pull predefined images.

The image we will pull contains TensorFlow and nvidia tools as well as OpenCV.

The idea is to package all the necessary tools for image processing.

With that, we want to be able to run any image processing algorithm within minutes.

Hopefully, you will get the following output (GPU only): sudo nvidia-docker run --rm nvidiacuda nvidia-smi Result of nvidia-smi Fetch Image and Launch Jupyter You probably are familiar with Jupyter Notebook.

Jupyter Notebook documents are both human-readable documents containing the analysis description and the results (figures, tables, etc.) as well as executable documents which can be run to perform data analysis.

Jupyter Notebook can also run distributed algorithms with GPU.

Then you can navigate to your localhost and use the port 8888, for me, the link looks like this: You will need to paste your token to identify and access your jupyter notebooks: 3299304f3cdd149fe0d68ce0a9cb204bfb80c7d4edc42687 And eventually, you will get the following result.

You can therefore test your installation by running the jupyter notebooks.

The first link is a hello TensorFlow notebook to get more familiar with this tool.

The third link gives an example of using TensorFlow to build a simple fully connected neural network.

You can find here a TensorFlow implementation of a convolutionnal neural network.

Tensorflow Keras Jupyter Notebooks Docker Pc Code Helps Us

The following code helps us track objects over frames with our webcam.

It is a sample of code taken from the internet, you can find the github repository at the end of the article.

First of all, we need to open the access to the xserver to our docker image.

Other methods are described in the links at the end of the article.

It is know as one of the most used libraries for image processing and available for C as well as Python.

You should see the following output, OpenCV will open your webcam and render a video.

OpenCV will also find any object in the frame and print the label of the predicted object.

Conclusion I showed how one can use Docker to get your computer ready for image processing.

This image contains OpenCV and TensorFlow with either GPU or CPU.

Tensorflow Keras Jupyter Notebooks Docker Install For Mac Pc