The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
H3: Static and dynamic content editing
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
This is a fig caption. This is how it will look like under a video frame as a description.
H4: How to customize formatting for each rich text
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
H5: Sample text is being used as a placeholder. Sample text helps you understand how real text may look. Sample text is being used as a placeholder for real text that is normally present.
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
H6: How to customize formatting for each rich text
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
Block Quote: Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
This is a heading 3.
Sample text is being used as a placeholder.
Sample text is being used as a placeholder.
Sample text is being used as a placeholder.
This is a heading 2.
Sample text is being used as a placeholder.
Sample text is being used as a placeholder.
Sample text is being used as a placeholder.
# clone openpilot into your home directory
cd ~
git clone --recurse-submodules https://github.com/commaai/openpilot.git
# setup ubuntu environment
openpilot/tools/ubuntu_setup.sh
# build openpilot
cd openpilot && scons -j$(nproc)
Maps are useful. Accurate maps are even more useful. Building accurate maps requires a lot of data. Mapping vehicles are expensive, EONs are not.
“How can cheap EONs ever make accurate maps?”, you might be thinking. Well, let me show you something:
Viewing frusta calculated with sensor fusion algorithm (INS + GNSS + Visual-Odometry). Without map-based corrections (left) and with map-based corrections (right).
On the right side of the image we see perfectly localized camera poses. This was done by using data collected with EONs and grey pandas. But how? Is it magic? It’s not…. it’s just math, and there’s more good news. We want to help you build accurate maps too, here’s some stuff to help you get started:
