I’m missing a way to do post processing on the video before uploading. I want to be able to delete the first and last minutes of my video. I turn on the camera before I put on my helmet. I also want to delete some images when I’m stuck at an intersection for a minute or stopped to eat something or … .
I’m trying to use the mapillary_tools to turn the video from GoPro into pictures to delete the unnecessary images. But I’m stuck on creating the right command.
This command gives me images from the video with the wrong time and very bad quality. but with gps coordinates and this doesn’t produce 360° images. but 180°+
mapillary_tools video_process “VIDEO_PATH” “IMAGE_PATH” --geotag_source “gopro_videos” --interpolate_directions --video_sample_interval 0.1 --geotag_source_path “VIDEO_PATH” --overwrite_EXIF_gps_tag
I’m using a gopro max with the bicycle settings as specified in the recommendations.
Hi @Koen_VdE - I would recommend using the GoPro Player to trim your video file. It should be pretty easy to do there and you don’t need to convert anything to images. You can trim the videos and then drag them into the desktop uploader to upload. Cheers!
And how would you delete the short lunch break (or other stops) in the middle of a video?
You would use the “Trim” tool to break it into 2 videos, one before the lunch break, and one after the lunch break.
Also, we now automatically sample the video to one image every 3 meters, so you shouldn’t see a lot of images from your lunch break once to upload to Mapillary because your camera was probably stationary during that time. So another option is just to upload the whole thing and then delete selected images using the Mapillary web interface (Mapillary)
I would still like to use the mapillary tools to extract images first and have a little more control on what I upload. I know I’m being a bit difficult but I’m working in a goverment context and I need to be able to explain every step in this process. We will prefer a complete check before uploading not after uploading.
mapillary_tools’s local video sampling does not handle GoPro Max’s special video projection. If you have to, I’d recommend try out the pre-processing in @trekview blog post Using ffmpeg to Process Raw GoPro MAX .360’s into Equirectangular Projections | Trek View
Thanks for sharing! IMHO CAMM is mainly a spec for storing the telemetry data as a MP4 track, it does not mean programs have to load them into memory as its specified.
Also out of curiosity, why the memory misalignment would happen on a 8-byte double time_gps_epoch followed by a 4-byte int gps_fix_type? They look aligned.
Another reason to still stick with photo capturing: correction of missing or wrong GPS coordinates (happens every now and then with the GoPro Max). Currently I have a working workflow to do this with photos, adapting this to videos would take some coding effort.
Also I have the impression that the image quality is worse with videos.
Thank you.
I will take those into advisement.
For now I’m playing around with things. This is video active. I’ll have to look more. Maybe I got a splash on the lens but I think the blurring feature may be hiding some of the waves ( blurring, that is ). 
It was a rainy day but the clouds had broken up. THe go pro 11 video ( active ) doesn’t quite get that sunlight. Or it doesn’t come through as well. Again though this isn’t set in a mode that Mapillary recomends, just playing to see how it well it works.
Was the image processing toolchain also upgraded? I don’t remember if this happened before, but now adding GoPro photos to the Uploader shows them facing the direction of travel straight away - is this some auto interpolation, or is extra EXIF data processed?
I have a good example of this.
But it has only been uploaded 7 days ago.
And I’m guessing you didn’t interpolate the sequence on upload manually?
Oh well, GoPros don’t all have a compass, so maybe this makes sense for most people
Somehow didn’t have GPS on for Monday’s hike. Hope to have some to share here comparing some different settings.
Superb news!
I do hope however, that next to accepting current dominating formats, Mapillary will innovate in this area, as it seems to me that fixed frame rate video has quite some overhead. It seems to me that the approach of Mapillary’s Android app is a strong approach still, capturing based on distance covered or curve travelled. Then instead of having separate jpg’s, I think HEIF would be the way to go for storage and upload.
I am curious what others think about this.
We’ve been working on improving the video support feature. @Magnet do you happen to still have the GX019036.MP4 file which was giving you this trouble? Any chance you could share a link so we can see if the new method fixes the issue you’re describing?