Here's some code to display one image from an image_url: library (jpeg) library (RCurl) img <- RCurl::getBinaryURL (image_url) jj <- jpeg::readJPEG (img,native=TRUE) plot (0:1,0:1,type="n",ann=FALSE,axes=FALSE) rasterImage (jj,0,0,1,1) Edit: Another way to think of this is, is there functionality like ipython's display? How to unzip files into memory in Python (you may encounter issues with this approach if the images are too large to fit in Jupyter's allocated memory) If you go the directory route, a friendly reminder that you'll need to update the code in each example to match your directory structure. E.g. if you want to save images to and read images from I suppose another workaround in the lab notebook environment might include creating an output Markdown cell, which would presumably require users to wrap existing libraries which generate links (e.g., to reports) with display calls. Image(url= "http://my_site.com/my_picture.jpg", width=100, height=100) You can also display images stored locally, either via relative or absolute path. PATH = "/Users/reblochonMasque/Documents/Drawings/" Image(filename = PATH + "My_picture.jpg", width=100, height=100) if the image it wider than the display settings: thanks If you are on Windows/ using Anaconda3, go to Win Start ->Search for Jupyter Notebook (env). Click on it and the Jupyter opens up. On Jupyter webpage, on right hand side go to New -> Terminal and the terminal window opens up. In this terminal windows change the directory to the working directory, using cd command. The docker run command is mandatory to open a port for the container to allow the connection from a host browser, assigning the port to the docker container with -p, select your jupyter image from your docker images. docker run -it -p 8888:8888 image:version. Inside the container launch the notebook assigning the port you opened: The video encoded data (if in a format the browser can decode, eg. h264-encoded in ISO mp4 container) can be displayed using an HTML