I’ve occasionally wanted to add a lot of videos at once to a youtube playlist.
Usually, this is super annoying since it takes a bunch of mouse presses to just added one video, and you can’t even used keyboard shortcuts (like hitting TAB and then enter).
https://www.youtube.com/view_all_playlists
Add videos -> URL -> enter URL -> Add video.
Repeat for each video, and every single one of those requires you to move your mouse around. You have to wait a bit each time too as the page reloads with your new video on it.
I found a shortcut so that it’s annoying, but slightly less annoying. In this method, you open the modal to add a video, then instead of opening and closing the modal, you can just copy-paste-click to add all your videos. Specifically, this adds them to your “watch later” list. Then you can go to your watch later playlist, click “add all to playlist”, and add them to your desired playlist.
A bit convoluted to explain, but really easy in practice, and so much faster than the old process.
Open up the playlist editor as usual, then entire a URL. Click the “clock” icon.
The “clock” should change into a “check mark”. Then you can paste in the next URL (without having to exit the modal) and proceed to add all videos.
Note: If your “watch later” list already has a bunch of videos that you want to keep,
you can create a temporary playlist “temp playlist”.
Then on your “watch later” list, click the three dots, and add all of the existing videos to the new “temp playlist”.
Then, go to edit the “temp playlist” and click the three dots, then click `add all to` and un-check the `watch later` playlist. this will remove the videos from your `Watch Later` playlist
After you are done bulk-adding videos to your other playlist (say `cool playlist`), you can uncheck playlist `Watch later` from “add all to” list. This’ll remove the new videos of your list from the `Watch Later` list and leave it empty. Finally, go back to your `temp playlist` and click “add all to” `Watch later`.
Wow, that was a mouthful, but hopefully it should make sense.
I recently started working with April tags, since they seem cool & you see them all over the place (used as fiducials for robots trying to walk around a somewhat unstructured environment).
the internet fell short (feel free to skip this section)
It was surprisingly hard to find instructions to get started, my search-fu was failing me. My search results turned up the original “official” website from the April Robotics Laboratory at University of Michigan, https://april.eecs.umich.edu/software/apriltag.html
This had no “getting started” instructions on it. Same for the C++ wrapper by a researcher at CSAIL (now a professor who I met at CMU!) https://people.csail.mit.edu/kaess/apriltags
And same for the ROS wrapper around the Apriltags, which also confusingly seems to have several version that may or may not now be the same. http://wiki.ros.org/apriltags_ros and https://github.com/xenobot-dev/apriltags_ros
(oh wait neat, there are instructions at https://cmumrsdproject.wikispaces.com/AprilTags_ROS). However, I’m still not terribly familiar with ROS, so I wasn’t too enthused about using this wrapper.
Fortunately Patrick over at Kuindersma’s lab above me was able to get me started.
sudo apt-get install subversion cmake libopencv-dev libeigen3-dev libv4l-dev
sudo port install pkgconfig opencv eigen3
svn co https://svn.csail.mit.edu/apriltags
cd apriltags
make
./build/bin/apriltags_demo
Yay, now a window pops open (see “troubleshooting” if it doesn’t, as was the case for me) with a video stream. But we need tags for it to recognize!
Getting tags
I actually found this pretty annoying, the zipped files on those sites give you a thousand options and it’s not clear which ones will work. So for me, I actually had my friend give me four tags that definitely work.
ID = #0 #1 #6 and #7 tags.
Print out tag
Run
./build/bin/apriltags_demo
Now stick the tag in front of your camera. In the videostream you should now see a circle. In the terminal you should now see data streaming out.
The data display shows distance (from the camera to the tag), the xyz location of the center of the tag, as well as the roll, pitch, and yaw. These coordinates will depend on which side you put pointing up when you pasted the tag on, so beware. In fact, none of the data should be taken as absolute until you calibrate your camera.
Fortunately, eventually I found my way to a python library that made the whole process super simple. I ignored the above link (to official openCV docs) entirely. Instead, I used the following python package. All I had to do was print out the checkerboard pattern included in the repository, wave it in front of the camera and record a short video, run the python file, and bam! I had the configuration.yaml file I needed.
To get it working, I did have to make sure I had pyyaml installed
(venv) nrw@earlgrey:$ sudo -H pip install pyyaml --upgrade
This project is super awesome and included an example you can run right away and inspect. The following line, run in the root takes in the video included in the repo (chessboard.avi) and outputs the resulting configuration file to “calibration.yaml”.
(venv) nrw@earlgrey:~/projects/video2calibration$ ./calibrate.py example_input/chessboard.avi calibration.yaml --debug-dir out
At this point I printed out the checkboard pattern included in the repository, put it on a stiff surface, and then opened cheese (you don’t have to use cheese, we just need to record a video).
Then I waved my board around in front of the camera and recorded a short video.
wheeeeee
Anyhow, I record ten or fifteen seconds of video. Then I ran
nrw@earlgrey:~/projects/apriltags/example$ vi apriltags_demo.cpp
Specifically, we want to change the following section. Note that we are using the definition of the rotation matrix to pull out (from the calibration.yaml output) the focal point and principal point parameters.
public:
// default constructor
Demo() :
// default settiwgs, most can be modified through command line options (see below)
[...excerpted section...]
m_width(640),
m_height(480),
m_tagSize(0.00944), // in meters
m_fx(667), // in pixels
m_fy(666), //
m_px(344), // principal point
m_py(227),
Ah! I forgot, we also needed to measure, using a ruler (or calipers), the size of the apriltag in real life. So just measure one of the sides of the tag (which should be square…) and put it inoto m_tagSize. (The width and height should be the size in pixels of the image from the video camera).
Compile and run (use “make clean” if the build fails, then run “make” again)
nrw@earlgrey:~/projects/apriltags/example$ cd ..
nrw@earlgrey:~/projects/apriltags/$ nrw@earlgrey:~/projects/apriltags/example$ make
One easy way to double-check whether the camera is roughly calibrated is to physically measure the distance between the camera and the tag, and then compare to the “distance” output in your terminal. Hopefully they match…
Units
The roll, pitch, and yaw are reported in radians. To convert into degrees, multiply by 57.3 (approximately).
Framerate
A framerate of 17fps or so is totally reasonable, since the apriltags demo is decently compute intensive. I had a problem with lag, where the video ran smoothly but with a significant lag — this may have been a result of me running the entire thing in a virtual machine. Let me know if you don’t have lag!
Troubleshooting
I had a somewhat frustrating beginning where I couldn’t get the example program to run.
-- Found OpenCV: /opt/ros/lunar (found version "3.3.1")
framerate (17fps raesonable, but lag???)
output is in radians
9.23346 fps
0 tags detected:
0 tags detected:
0 tags detected:
0 tags detected:
0 tags detected:
0 tags detected:
0 tags detected:
0 tags detected:
1 tags detected:
OpenCV Error: Assertion failed (mtype == type0 || (((((mtype) & ((512 - 1) << 3)) >> 3) + 1) == 1 && ((1 << type0) & fixedDepthMask) != 0)) in create, file /tmp/binarydeb/ros-lunar-opencv3-3.3.1/modules/core/src/matrix.cpp, line 2542
terminate called after throwing an instance of 'cv::Exception'
what(): /tmp/binarydeb/ros-lunar-opencv3-3.3.1/modules/core/src/matrix.cpp:2542: error: (-215) mtype == type0 || (((((mtype) & ((512 - 1) << 3)) >> 3) + 1) == 1 && ((1 << type0) & fixedDepthMask) != 0) in function create
Id: 15 (Hamming: 1)Aborted (core dumped)
It turned out that because I had ROS installed, or perhaps also because I installed the “apriltags” ROS wrapper, I was having openCV version conflicts.
To solve, I simply had to edit one line in the CMakeLists.txt to force it to use the right version of openCV. I added an “exact required” tag, along with my openCV version (2.4.9.1), to the appropriate line.
nrw@earlgrey:~/projects/apriltags$ vi CMakeLists.txt
(line 14)
find_package(OpenCV 2.4.9.1 EXACT REQUIRED)
edit: Note that physically, the set-up is that I have an extra desktop which is always on and connect to the internet which is running Ubuntu (16.04). I have an external webcam. This also requires a dropbox account.
I’ve often wanted to monitor something remotely, but have had issues in the past trying to set up a video stream. For monitoring experiments remotely (or for instance a 3d printer), I really don’t need 30 frames per second.
I suppose nowadays, in theory I could set up a youtube live stream, especially since I could just disable audio. But for more control over the end result, my solution is a one-liner bash command, combined with a dropbox account.
I was having a terrible time with all my search results describing ways to create a timelapse animation, instead of detailing how to take the pictures for the timelapse in the first place.
use streamer
streamer -c /dev/video1 -t 10 -r 1 -o 0000.jpeg &
The settings for the above command are as follows:
Using the “second” camera (ince my desktop has a built-in webcam mapped to /dev/video0, whereas I wanted to take pictures with a USB webcam)
10 frames total
1 frame a second (rate)
Name starts at 0000.jpeg (it will automatically count up)
i used the first command to test whether the command is working.
For the actual timelapse, I wanted to take a picture every 5 minutes, or in other words every (1/360 = 0.0033) seconds. (I don’t think there’s an option to define the rate in anything other than seconds).
I wanted about 24 hours of timelapse. At every 5 minutes, I take 12 an hour or 12*24 a day, so around 300 frames
Streamer was defaulting to 320×240 pixel images, so I asked streamer to instead take 640×480 pictures, which are what my webcam supports.
Note: I did not really play around with this, but I think you can also create video with streamer, e.g.
Now, I can access my setup online at dropbox.com. I can also use the “share folder using link” option on dropbox to share with multiple people.
Make a QR code
This was purely for fun, but I turned the dropbox link into a QR code which I printed out and stuck next to the experiment
Protips
I find it really handy to include labeling information not just in the filenames but also physically in the image. Below you can see I labeled the image with the date of the timelapse.
Making a timelapse (animation / video of the resulting images) using ffmpeg
Takes all jpg files and turns it into an mp4 with 20 frames per second.
I was having a lot of issues following the instructions online, but somehow using the image2pipe solved everything. (I was getting errors like “would you like to overwrite this .jpeg file y/n”).
One thing that surprised me on this page, is that a common command such as “all images in this folder” is a little trickier than I’d expect. (I was working with another set of images that used timestamps as filenames, instead of an orderly 0001.jpeg like other examples onlin).
1) You must use “glob option”
2) You must surround your search pattern in quotes
note to self: to rotate all images in a directory 90 degrees clockwise:
for file in ./*.jpg do
convert "$file" -rotate 90 "${file%.JPG}"_rotated.JPG
done
There you have it!
Thanks to the one-liner “streamer” command, and by using dropbox as a syncing service. you can accomplish a real-time viewable timelapse with just 4 or 5 lines of code, and then use just one more line to create a video of the resulting images.
The “clock” should change into a “check mark”. Then you can paste in the next URL (without having to exit the modal) and proceed to add all videos.
Finally, go to your “watch later” playlist
After you are done bulk-adding videos to your other playlist (say `cool playlist`), you can uncheck playlist `Watch later` from “add all to” list. This’ll remove the new videos of your list from the `Watch Later` list and leave it empty. Finally, go back to your `temp playlist` and click “add all to” `Watch later`.
