YI 360 VR camera REVIEW

Omitted some sample_video commands - Note the video start time. This is essentially the first video frame. Just point the camera at the GPS device display, then delete those “bad images” after process but before upload.

usage: see -h for available tools and corresponding arguments, add --advanced to see additional advanced tools and/or arguments and --version to see version. sample_video
[-h] [–advanced] [–version] [–verbose] [–import_path IMPORT_PATH]
–video_import_path VIDEO_IMPORT_PATH
[–video_sample_interval VIDEO_SAMPLE_INTERVAL]
[–video_duration_ratio VIDEO_DURATION_RATIO]
[–video_start_time VIDEO_START_TIME] [–skip_subfolders]

optional arguments:
-h, --help show this help message and exit
–advanced Use the tools under an advanced level with additional
arguments and tools available.
–version Print mapillary tools version.
–verbose print debug info
–import_path IMPORT_PATH
path to your photos, or in case of video, path where
the photos from video sampling will be saved
–video_import_path VIDEO_IMPORT_PATH
Path to a video or directory with one or more video
files.
–video_sample_interval VIDEO_SAMPLE_INTERVAL
Time interval for sampled video frames in seconds
–video_duration_ratio VIDEO_DURATION_RATIO
Real time video duration ratio of the under or
oversampled video duration.
–video_start_time VIDEO_START_TIME
Video start time in epochs (milliseconds)
–skip_subfolders Skip all subfolders and import only the images in the
given directory path.

I think I have to create something myself… on testing with only images:

At the highest resolution, the camera can’t stitch inside the camera, I need the Windows software. The stitching software removes all the EXIF data… So I need to read the original file for the EXIF data, match it to the GPX track and add it to the stitched image… (can mapillary tools do that? with wildcards?)

Example: original file: YITL_0029360.JPG (which has needed EXIF data)
stitched file: YITL_Stitch
0029_360_190521123653_360.JPG (no EXIF data what so ever)
(the numbers at the end are a sort of serial number, no time in there…)

I’ll upload a sample image:

This image quality easily meets the LG360! (excuse the mess, the house and garden ar a bit of a project :stuck_out_tongue: ) Now I can see grass, not just a green blur.

What EXIF data do you want to keep? The tools only need the date/time tag as mentioned above. Then it can merge in the GPS/gpx data.

Exiv2 (Windows version uses cygwin) allows all the EXIF data to be read from one file and written to another. Also useful for new/modified tags. There are bound to be other Windows pgms that do this.,

The tools can parse through a folder of images and insert the (interpolated) GPS/gpx data based on the date/time EXIF tag

EXIV2:
I did a quick look at their doc page: https://www.exiv2.org/manpage.html

I get the feeling it has a problem with microseconds? And, wow, what a list of options… I think you understand what I want/need to do, but I think I’ve faster altered the perl software I shared earlier, than that I’ve figured this out I think?

QUALITY COMPARISON YI360 vs LG360
I took al look at more images I have taken with the LG360. I more or less accidentally took a good image to compare it to, but looking with a more critical eye, I see that the LG has a lot of difficulty with the lower sun and with less daylight. The first few tests do give me the impression that the image quality of the YI seems much more stable… Therefor, in movie-grab-mode the quality may be less, compared to a good LG-image, but overall the quality of the YI seems much more stable…

Next up is working on creating a good workflow to get as good as possible EXIF data in the images.
Next to that I realy hope the Mapillary team can get rid of the error I’m getting with the app. Then I can do tests with “image mode”. And really get to work :wink:

[update]
NEW MICRO SD CARD
Did some experimenting with my new Sandisk Extreme PRO 128GB memory card. With a timer going off every one second, it missed quite a lot of images. On 2 seconds it snapped all the 5.7K (16.6MP) images. Setting at 1.5 felt a bit unstable and it worked well at 1.75 seconds. All this done manually (beep, press button :wink: ), so an actual value will probably be around 1.5 to 1.7 seconds per image.
This means that when an “interval setting” becomes workable, this camera is fast enough for taking pictures when walking and when cycling not to fast (at 12 km/h it’ll be around 5 meters per image).

So for now I’m stuck with video mode… That gives me time to get to a good workflow processing an MP4.

But ultimately I offcourse want “the best”… and separate images have a higher quality then MP4-grabs (obviously), so I prefer an “image interval mode”.

I am very (very) surprised that you find LG’s resolution/detail better. Considering how much the Yi costs, and that they did a pro camera as well, I was expecting much better. Maybe it’s the same as with Gear MK1 - the older cameras had plain better sensors?
Could also be the issue of most modern 360 cameras focusing on video instead of photo

I did compare MP4 grabs with LG images! And I did say the separate images are much better! And the focusing, freshness and stitching is better. Just did a test under lower lighting, also better :wink:

But I am certain that it’ll be an “all win” when the interval images starts to work!

Today I did a “duration test”. As I red in other tests, it’s just under an hour at 1 fps.

[update] You really need to see this, really!

http://www.geoarchief.nl/mapillary.html?key=MQbZm9TD3kpAdoalJMPyBA&zoom=.1

Press play!!

I had quite a bit of work getting the EXIF data in correct. But I did :). I updated my “GEO tag assistant” to find the right start and stop time. For the test I set the YI to taking an image every 1 second. In my walking speed that became one image every almost 2 meters. I set it to one second expecting that the time between each image would become a tiny bit more or less than that so I could test the microsecond matching of the Perl script.
The timer of the camera matched the GPS sequence perfectly, I ended up mismatching the sequence deliberately by one second, to do the testing :wink:

And I must say, I’m quite happy with the result!

At first I feared that aprox. 1.8 meters between the images would be overkill, but when I press play it’s almost like you’re watching a video, not a sequence of images, NICE!.
I also think the overall image quality is very nice! (even though the sun was already quite low…)

When I see the ‘animation’. it underlines that the “mechanical x-axis stabilizer” I bought was a waste of money. But the horizon isn’t extremely stable and you can see me walking… Maybee the Feiyotech G5GS with a custom connectionblock (red) might be next on my wishlist :wink:

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I think my wife won’t let me test the YI for a while… I had an accident

OK, for more reasons than one I processed the last sequence I created with my “roof rack”.

It’s a two suction-cup system. I used the car antenna to secure the rig (if the cups would fail…). The whole thing stayed put, even with the accident I had, so I expect it’ll hold on the highway as well :wink:

I set the recording to max resolution and max frame rate (25 fps)

I did have a bit of work improving my Perl script to get the matching right with the GPX track. I discovered a few optimizations to the microsecond calculation, since I now have 25 images per second in stead of the previous test of 1 image per second.
Furthermore I improved the script to exclude images that are les then 1.5 meters away of the previous image. This resulted in an distance ranging 1.5 and 2.3 meters, which in my opinion is more then enough. It reduced the sequence from 4.235 to 1.269 images.

Also I discovered that using a faster moving vehicle doesn’t improve the quality of the GPX track. It is best to drive as slowly as legally allowed to get the best possible GPX track. And seriously slow down at turns to give the GPS a chance to discover and record the change. I had to manually adjust the sequence at one sharp turn. Beside that the interpolation went perfectly and It worked good enough to use a start time and increment 1/25 th of a second each image.

This 4 minute track resulted in a MP4 file of 13,5 Gb. The raw unstitched datafile is almost 4Gb and the separate JPG files are a bit over 14Gb (in the best ffmpeg quality I could export them). So it’s about 1 Gb per minute raw recording resulting in a MP4 for processing of 3.3 Gb per minute. So I could drive around for a bit over an hour to get a raw file that fits my 128 Gb micro SD card… Then I’dd have a 400 Gb MP4 for processing… Also to generate that 13.5 Gb file it needed two hours of stitching on my computer… So really large tracks likely aren’t that good of an idea :wink:

I had done several more tests, but I didn’t like the GPS quality and also I think I need to extend the distance between the camera and the car. I have published this one sequence to see how it comes out, but I think I need to buy a lightweight “extension stick” to see less car in the images.

When the track is online I’ll publish a link.
[update] here it is:

I’m sure I set the orientation correctly in my Perl program, what happend? One image is correct, the next looks the other way etc!?
[update]
Must need a bit of time, all looks well now

What I feared, to much car in view, how much higher would i need to go to get it decent?
[update]
Now that the sequence is correctly orientated, it’s easier to evaluate:
I think it looks as well as the “walking sequence” so faster motion doesn’t influence the image quality. How much higher would be ok though? Higher is better naturaly, but to high is a danger to stability and the risk of to much stress on the suction cups…I’ve ordered this:

stay safe out there - I’d be afraid to even ride a quadbike on a narrow path like that.
The car being in the photo is an issue for most contributors, since it’s a trade off between stability/discreetness/cost etc. Nadir stitching isn’t great so it you are not losing much data from the image, it just doesn’t look quite as “pro”

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I took my YI 360 with us on our holiday to France. I am not the “sitting down and reading a bok person”… so what did I do with weather hitting high scores in 74 years… I walked around with my 360 camera :sweat_smile:

First I did my utmost best recording a fantastic cave and manually sort of geo-reference it. I just uploaded that one and will share a link for you to see how this pans out…

This was where we were on holiday:


I started recording all of Bonnal… but ended up walking about 130 km (80 miles) recording over 24 Gb of image data…


When I turn on “360 only” the area is completely empty

With this it’ll be a prefect dataset to improve my program to optimize the workflow… will keep ya’ll posted :wink:

[update][edit, missed a few :wink: ]
First stage automated, 148 MP4 files are converted to 42,236 images. This took 94 minutes, that’s 7.5 images per second (AMD A8-7600 Radeon R7 running Ubuntu)

Walk through the caves of Moidons (Jura France) !

Lessons learned so far:

  1. don’t play around with the movie interval, there is no way to find that setting out later. Ended up using one image per second. When walking briskly (about 7 km/u, being 2 m/s) that is more then enough. One image every 2 seconds would be enough to, but now I have a spare (a sun flare, or something else…)
  2. start your GPS recording sooner. The location is crappy the first few minutes.I had bought a second hand ‘GNS2000 plus’ (external compact GPS / GLONASS receiver) but misplaced it in the luggage (but found it agian :wink: ) That one gets a good bearing much sooner (at a higher quality)
  3. The date and more importantly the time of the MP4-file is the time of the last frame. Knowing the frame rate I can now easily calculate the time of each frame. Accuracy, up to a second, so when walking about 2m.

[edit] Update: 12th of August:
Hmmmmmm, point 3 has proven not to be true all the time… Even though I have a good and fast micro flashcard… sometimes there appears to be a delay for some reason… I had it now with one track… I thought I found the perfect solution:

ffmpeg -i movie.MP4 -dump

It gives a creation time like “creation_time : 2019-07-24 10:53:19”.
But the weird thing is… the file date is proving much more accurate then the time given in the meta data of the file itself…

So for now I hope that one movie file is a f*ckup and my approach is good (enough).
[/edit]

AD 1) I have set up a minimal distance in my program between images, so that will prevent an overload of images by default.

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As to the time it takes to process…

  1. The conversion from MP4 to seperate JPG’s runs at about 7.5 images per second on my computer
  2. The GEO referencing (and adding other EXIF data) runs quite fast. I built a detection to only load the GPX files of the matching day. Speed… about 10 images per second (removing about 1/3 of the images for upload)
  3. And then Hugin, the program that stitches the raw images… well… that one takes it’s time… One image takes about 18 seconds to get stitched… so that’s about 3 images per minute

With 27.641 images that’ll be almost 6 days of calculation!
It is that I am extremely content with the stitching quality… so…OK… well… that’s gonna take a while…

I red on this forum the (or some?) GoPro Fusion have temperature problems.

I used the YI360 on my holiday actively, and during the hottest week for the better part of the last century! So if that isn’t a good (over) heating test, I don’t know what would be :wink:

It does get warm, hot even. Which isn’t that odd, since mine is black and it got towards 40 degrees Centigrade! The internal battery lasts for about just under an hour. I brought two powerbanks along that add about an hour each.

To be able to use the powerbank during my walks I performed a small hack; I cut out a small part of the plastic cover, so I could plug in the USB power cord:

.

Luckely the YI360 allows operation during charging. All this went fine. The YI360 got warm, very warm even, but never refused operation!

So far I have learned that times and dates recorded by the camera do need some filtering…

These are the variables I can “play” with:

  • file date (usable for the moment of the last frame)
  • number of frames & frame rate => total time recorded
  • via “ffmpeg” the moment of the first frame

I have done some testing by taking images and interval movies of a synced clock. Images are just fine, there does appear to be some delay, but it’s something like half a second at most. For MP4 however: to my surprise there appears to be some sort of error in the time found by ‘ffmpeg’ for the start time, it is exactly a whopping 10 seconds earlier than the time I see on the clock!
Then the rest just became much easier… with more then 75 images the file time is about a second later, another for about 150 images and one more with more then 300 images.

And more importantly: try to reduce the variables:

It may sound so obvious, but when using external GPS recording for later matching it’ll make you’re life so much easier when you know how to synchronize the time of your camera with the GPS time.
The internal clock of your camera most likely isn’t perfect… I just found out that after the last time I synced the time with my phone about three months have passed and the time of the camera was a whopping 6 seconds out of sync!

So remember: before you go: sync the time of your camera with GPS!

The time recorded of your GPS device most likely is in (exact) sync with the time broadcasted by the GPS satellites (it doesn’t get much better than that!)

For the YI360:

  • connect your app to the camera
  • tap the gear symbol (top right)
  • scroll to the bottom and tap ‘others’
  • tap: ‘correct camera time’

PS: I honestly don’t understand why this isn’t done by default upon connecting the camera to app

Well there are some edits and corrections still in the pipe line, but now you can see I did quite some walking in my holiday: :wink:
Before and after:

Take a look for yourself:


I started recording all of Bonnal… but ended up walking about 130 km (80 miles) recording over 24 Gb of image data…

PS: don’t comment just too much yet… I have 16 pending edits for this region…

PS2: I uploaded all the GPX tracks to OSM also… If you’dd like there are quite a few edits/corrections to be done…

I could not hold a stick in my hand for so long.

Good eye, that did prove to require some treatment after my holiday… am figuring something out with a back pack for later. But If I want the same stability it’ll require a gimbal… thinking about the “g360 feiyu tech gimbal”:

Years ago I found a ready made backpack (with a camera pole mounted) on the internet. It was rather expensive. I do not find it any more.

There is backpack on Aliexpress https://www.aliexpress.com/item/32833663974.html?spm=a2g0s.9042311.0.0.27424c4daB2ifg with camera mount
I made some modification - rotate bracket inside on 90 degrees and made straight aluminium tube 49 cm long

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