To get started, move your mouse cursor over the
[ ] box to the left of the first code snippet, underneath the Downloading Model Data header. It will change to a "Play" icon. Click on this icon.
After typically 20 seconds or so, you'll see the notebook come to life. The previous output will vanish and you'll see it replaced with the result of running on your new runtime (see the section titled Aside below for more about what a runtime is).
When you see
Setup Successful!, you know you've finished this step. You can open another copy of the notebook and compare it to our previous run, just to make sure it looks correct.
Each time you open a Colab notebook, Google lets you temporarily use a computer in their datacenter to run your code. This computer is running a program called the runtime, which lets you play around with TensorFlow without having to worry about how fast your computer and without needing to buy an expensive graphics card.
When you close your Colab notebook, Google replaces your runtime with a brand new one, and releases your machine to someone else. This means that each time you come back, you'll need to set up the machine from scratch.
The first cell in the notebook does just this. It downloads the TensorFlow Model that will be used to recognize objects.
The code you just ran sets up a TensorFlow graph--a series of processing steps that translate the image from your camera into object labels and bounding boxes. You can visualize the graph using a tool called [TensorBoard]. This step isn't strictly necessary but it lets you peek inside the network to see the complexity behind the scenes.
To do this:
- Under Optional: Visualize the Graph with TensorBoard, click Play.
- Wait a few seconds after the block finishes executing. You should then see the TensorBoard UI appear below:
Be sure to click Allow.
Finally, scroll down and you should see video from your camera appear on screen. Above the video, you'll see the output from the Object Detector.