How it works

The following describes how the script works at each step.

Image source here

Video input

1. User defines video and script settings

Users sets desired settings and input held in config.ini

2 Validate mode vs video metadata

In order to process the video in the correct flow, the following logic is checked against mode input.

Validate GoPro EAC .360 (mode=video+eac)

See validations: https://docs.google.com/spreadsheets/d/1x9WnLwPHZIKRyfKkCW2ORVprpsAlA3c2hqVu4S9yIaY/edit#gid=428268485

If all validations pass, send to MAX2Sphere frame pipeline.

Validate dual GoPro Fisheye (mode=video+fisheye)

See validations: https://docs.google.com/spreadsheets/d/1x9WnLwPHZIKRyfKkCW2ORVprpsAlA3c2hqVu4S9yIaY/edit#gid=2125124048

If all validations pass, send to Fusion2Sphere frame pipeline.

Validate equirectangular mp4 (mode=video+equirectangular)

See validations: https://docs.google.com/spreadsheets/d/1x9WnLwPHZIKRyfKkCW2ORVprpsAlA3c2hqVu4S9yIaY/edit#gid=967778760

If all validations pass, send to equirectangular frame pipeline.

Validate HERO mp4 (mode=video+hero)

See validations: https://docs.google.com/spreadsheets/d/1x9WnLwPHZIKRyfKkCW2ORVprpsAlA3c2hqVu4S9yIaY/edit#gid=0

If all validations pass, send to HERO frame pipeline.

3. Extract metadata from video

Done using exiftool:

$ exiftool -ee -G3 -api LargeFileSupport=1 -X IN_VIDEO.mp4 > VIDEO_META.xml

Note, if dual fisheyes, uses the front image (GBFR) for extraction.

4. Calculate un-timed GPS points

GoPro reports telemetry at different time intervals, and not every GPS position recorded has a time.

~ 18 Hz (up to 18 measurements per second) GPS position (lat/lon/alt/spd)
1 Hz (1 measurements per second, but not exactly 1 second apart) GPS timestamps
1 Hz (always at same interval as GPS timestamps) GPS accuracy (cm) and fix (2d/3d)

You can see examples of these values in real GoPro telemetry here.

Therefore up to 18 points have no time between GPS timestamps being reported. The number of points reported between times also varies based on mode/GPS signal (when GPS signal low, this number might be a lot lower).

To do this we calculate how many points there are between each time interval. Based on the number of points, we then calculate time.

Before doing this we first remove any duplicate GPS points (lat+lon+alt).

e.g.

<Track4:GPSLatitude>51 deg 16&#39; 21.17&quot; N</Track4:GPSLatitude>
<Track4:GPSLongitude>0 deg 50&#39; 45.50&quot; W</Track4:GPSLongitude>
<Track4:GPSAltitude>81.907 m</Track4:GPSAltitude>
<Track4:GPSLatitude>51 deg 16&#39; 21.17&quot; N</Track4:GPSLatitude>
<Track4:GPSLongitude>0 deg 50&#39; 45.50&quot; W</Track4:GPSLongitude>
<Track4:GPSAltitude>81.907 m</Track4:GPSAltitude>
<Track4:GPSLatitude>51 deg 16&#39; 21.17&quot; N</Track4:GPSLatitude>
<Track4:GPSLongitude>0 deg 50&#39; 45.50&quot; W</Track4:GPSLongitude>
<Track4:GPSAltitude>81.907 m</Track4:GPSAltitude>
<Track4:GPSLatitude>51 deg 16&#39; 21.17&quot; N</Track4:GPSLatitude>
<Track4:GPSLongitude>0 deg 60&#39; 45.62&quot; W</Track4:GPSLongitude>
<Track4:GPSAltitude>81.907 m</Track4:GPSAltitude>

In this case, only these two points would be considered.

<Track4:GPSLatitude>51 deg 16&#39; 21.17&quot; N</Track4:GPSLatitude>
<Track4:GPSLongitude>0 deg 50&#39; 45.50&quot; W</Track4:GPSLongitude>
<Track4:GPSAltitude>81.907 m</Track4:GPSAltitude>
<Track4:GPSLatitude>51 deg 16&#39; 21.17&quot; N</Track4:GPSLatitude>
<Track4:GPSLongitude>0 deg 60&#39; 45.62&quot; W</Track4:GPSLongitude>
<Track4:GPSAltitude>81.907 m</Track4:GPSAltitude>

For example, if GPSDateTime 1 = 1:00:00.000 and GPSDateTime 2 = 1:00:01.000 and there are 9 (non-dupe) points reported between these two time, we know each point is about .100 second apart so times for points will be 1:00:00.000, 1:00:00.100. 1:00:00.200, ... 1:00:00.900.

A note on final points reported in GPMF

At the end of the GoPro telemetry there is not a final time. That is, some GPS points continue beyond final reported time (usually 3 or 4).

e.g here we have 3 points following the final time

 <Track3:GPSMeasureMode>3-Dimensional Measurement</Track3:GPSMeasureMode>
 <Track3:GPSDateTime>2021:09:04 07:23:17.199</Track3:GPSDateTime>
 <Track3:GPSHPositioningError>1.49</Track3:GPSHPositioningError>
 <Track3:GPSLatitude>51 deg 16&#39; 21.18&quot; N</Track3:GPSLatitude>
 <Track3:GPSLongitude>0 deg 50&#39; 45.54&quot; W</Track3:GPSLongitude>
 <Track3:GPSAltitude>80.771 m</Track3:GPSAltitude>
 <Track3:GPSSpeed>1.152</Track3:GPSSpeed>
 <Track3:GPSSpeed3D>1.18</Track3:GPSSpeed3D>
 <Track3:GPSLatitude>51 deg 16&#39; 21.18&quot; N</Track3:GPSLatitude>
 <Track3:GPSLongitude>0 deg 50&#39; 45.54&quot; W</Track3:GPSLongitude>
 <Track3:GPSAltitude>80.765 m</Track3:GPSAltitude>
 <Track3:GPSSpeed>1.131</Track3:GPSSpeed>
 <Track3:GPSSpeed3D>1.15</Track3:GPSSpeed3D>
 <Track3:GPSLatitude>51 deg 16&#39; 21.18&quot; N</Track3:GPSLatitude>
 <Track3:GPSLongitude>0 deg 50&#39; 45.54&quot; W</Track3:GPSLongitude>
 <Track3:GPSAltitude>80.744 m</Track3:GPSAltitude>
 <Track3:GPSSpeed>1.099</Track3:GPSSpeed>
 <Track3:GPSSpeed3D>1.13</Track3:GPSSpeed3D>
 <Track3:GPSLatitude>51 deg 16&#39; 21.17&quot; N</Track3:GPSLatitude>
 <Track3:GPSLongitude>0 deg 50&#39; 45.54&quot; W</Track3:GPSLongitude>
 <Track3:GPSAltitude>80.748 m</Track3:GPSAltitude>
 <Track3:GPSSpeed>1.11</Track3:GPSSpeed>
 <Track3:GPSSpeed3D>1.1</Track3:GPSSpeed3D>
 <Track3:TimeStamp>20.204954</Track3:TimeStamp>
 <Track3:TimeStamp>20.204954</Track3:TimeStamp>
 <Track3:TimeStamp>20.204954</Track3:TimeStamp>
 <Track3:TimeStamp>20.204954</Track3:TimeStamp>
 <Track3:TimeStamp>20.18495</Track3:TimeStamp>
 <Track3:TimeStamp>20.18495</Track3:TimeStamp>
 <Track3:TimeStamp>20.18495</Track3:TimeStamp>
 <Composite:ImageSize>5376x2688</Composite:ImageSize>
 <Composite:Megapixels>14.5</Composite:Megapixels>
 <Composite:AvgBitrate>117 Mbps</Composite:AvgBitrate>
 <Composite:Rotation>0</Composite:Rotation>
 <Composite:GPSPosition>51 deg 16&#39; 21.21&quot; N, 0 deg 50&#39; 45.54&quot; W</Composite:GPSPosition>
</rdf:Description>
</rdf:RDF>

Full output.

In this case, we can calculate the final time as follows (I will use examples from the linked file):

Subtract the last reported GPSDateTime (end time) from the first reported GPSDateTime (start time)
- 2021:09:04 07:23:17.199 - 2021:09:04 07:22:56.299 = 20.9s
Subtract the video duration metadata value from this:
- 21.2 - 20.9 = 0.3s
This will give you remaining seconds of video. Add this value to the final reported GPSDateTime to create the final time.
- 2021:09:04 07:23:17.199 + 0.3 = 07:23:17.499
It is then possible to calculate points in-between in exactly the same way as before.

5. Create video GPX

A GPX file can then be created using all time, elevation (altitude), latitude, and longitude calculated earlier

<trkseg>
    <trkpt lat="51.27254444444444" lon="-0.8459694444444444">
        <ele>82.008</ele>
        <time>2021-09-04T07:24:07.744000Z</time>
    </trkpt>
    <trkpt...
      ...
</trkseg>

6. Extract frames at set rate for video type

User can set the ffmpeg -r value. Depending on the mode of the video (set by user), we extract like so:

GoPro EAC .360

$ ffmpeg -i INPUT.360 -map 0:0 -r XXX -q:v QQQ trackN/img%d.jpg -map 0:5 -r XXX -q:v QQQ trackN/img%d.jpg

Where XXX = framerate user passes in CLI. And QQQ = quality.

Note: if timelapse mode is used, the track numbers are different:

Regular video = -map 0:0 and -map 0:5
Timewarp video = -map 0:0 and -map 0:4

Dual GoPro Fisheye

$ ffmpeg -i INPUT_FR.mp4 -r XXX -q:v QQQ FR/img%d.jpg 
$ ffmpeg -i INPUT_BK.mp4 -r XXX -q:v QQQ BK/img%d.jpg

Where XXX = framerate user passes in CLI. And QQQ = quality.

Equirectangular / HERO mp4

$ ffmpeg -i INPUT.mp4 -r XXX -q:v QQQ img%d.jpg

7. Process to equirectangular for EAC / Fisheyes

Skip step 7 if Equirectangular / HERO mp4 input

7A. MAX2Sphere flow (2 GoPro EAX Frames)

Merge 2 tracks of frames into one

$ @SYSTEM_PATH/MAX2spherebatch -w XXXX -n 1 -m YYYY track%d/frame%4d.jpg

Note, -w flag variable (XXXX), if in XML ImageWidth is:

4096, then -w = 4096
2272, then -w = 2272

For -m flag variable YYYY is equal to number of frames extracted.

7B. Fusion2Sphere flow (2 GoPro Fisheye Frames)

@SYSTEM_PATH/fusion2sphere -b 5 -f FR/img%d.jpg BK/img%d.jpg -o FINAL/img%d.jpg parameter-examples/PPPP.txt

Note, PPPP variable is determined by frame ImageWidth:

3104, then PPPP = photo-mode.txt
1568, then PPPP = video-3k-mode.txt
2704, then PPPP = video-5_2k-mode.txt

8. Add logo

Skip if option not selected by user.

User should be able to pass flag -n at upload with path to a logo file.

Logo file must be:

.png filetype
square dimensions
= 500 px height

8A. Add nadir (equirectangular)

User can set nadir overlay size and logo.

To create the nadir, these steps can be followed:

https://www.trekview.org/blog/2021/adding-a-custom-nadir-to-360-video-photo/

Example of nadir image height (equirectangular)

Note, nadir convert to equirectangular/resize step only needs to be converted to equirectangular and resized once (as all frames have same dimensions so output can be overlaid over each).

8B. Add watermark (HERO)

User can set watermark overlay size and logo.

To create the watermark, these steps can be followed:

https://www.trekview.org/blog/2022/adding-a-custom-watermark-to-hero-photo-video/

Example of watermark image height (non-equirectangular)

9. Insert equirectangular metadata to frames (equirectangular only)

Skip step 7 if HERO mp4 input

Value type	Image metadata field injected	Example injected
Fixed	XMP-GPano:StitchingSoftware	Spherical Metadata Tool
Fixed	XMP-GPano:SourcePhotosCount	2
Fixed	XMP-GPano:UsePanoramaViewer	TRUE
Fixed	XMP-GPano:ProjectionType	equirectangular
Is same as ImageHeight value	XMP-GPano:CroppedAreaImageHeightPixels	2688
Is same as ImageWidth value	XMP-GPano:CroppedAreaImageWidthPixels	5376
Is same as ImageHeight value	XMP-GPano:FullPanoHeightPixels	2688
Is same as ImageWidth value	XMP-GPano:FullPanoWidthPixels	5376
Fixed	XMP-GPano:CroppedAreaLeftPixels	0
Fixed	XMP-GPano:CroppedAreaTopPixels	0

Note, some spatial fields are always fixed (e.g. XMP-GPano:SourcePhotosCount b/c GoPro 360 cameras only have 2 lenses), so values are static.

10. Add photo times and add GPS data

10A Add photo times

First frame (all modes)

To assign first photo time, we use the first GPSDateTime value reported in telemetry and assign it to photo time fields as follows:

Video metadata field extracted	Example extracted	Image metadata field injected	Example injected
TrackN:GPSDateTime	2020:04:13 15:37:22.444	DateTimeOriginal	2020:04:13 15:37:22Z
TrackN:GPSDateTime	2020:04:13 15:37:22.444	SubSecTimeOriginal	444
TrackN:GPSDateTime	2020:04:13 15:37:22.444	SubSecDateTimeOriginal	2020:04:13 15:37:22.444Z

Example exiftool command to write these values:

$ exiftool DateTimeOriginal:"2020:04:13 15:37:22Z" SubSecTimeOriginal:"444" SubSecDateTimeOriginal: "2020:04:13 15:37:22.444Z"

Other frames (normal mode)

Now we need to assign time to other photos. To do this we simply order the photos in ascending numerical order (as we number them sequentially when extracting frames).

We always extract videos at a fixed frame rate based on transport type. Therefore, we really only need to know the video start time, to determine time of first photo. From there we can incrementally add time based on extraction rate (e.g. photo 2 is 0.2 seconds later than photo one where framerate is set at extraction as 5 FPS).

Extraction Frame rate	Photo spacing (sec)
1	1
2	0.5
5	0.2

Other frames (timewarp mode)

Timewarp is a GoPro mode that speeds up the video (e.g. when set a 5x every second of video is 5 seconds of footage).

We therefore explicitly ask use if video was shot in timewarp mode and the settings used (there is no easy way to determine this automatically).

Timewarp mode	Each photo true time (sec) @1 FPS	Each photo true time (sec) @2 FPS	Each photo true time (sec) @5 FPS
2x	2	1	0.4
5x	5	2.5	1
10x	10	5	2
15x	15	7.5	3
30x	30	15	6

To give an example, lets say first photo gets assigned first GPS time = 00:00:01.000 and we extract photos at 5FPS for timewarp mode 30x. in this case second photo has time 00:00:01.000 +6 secs.

10B Add GPS points

Now we can use the photo time and GPS positions / times to geotag the photos:

All frames (all modes)

We can use Exiftool's geotag function to add GPS data (latitude, longitude, altitude).

exiftool -Geotag file.xml "-Geotime<SubSecDateTimeOriginal" dir

This will write the following fields into the photos

Image metadata field injected	Example injected
GPS:GPSDateStamp	2020:04:13
GPS:GPSTimeStamp	15:37:22.444
GPS:GPSLatitude	51 deg 14' 54.51"
GPS:GPSLatitudeRef	North
GPS:GPSLongitude	16 deg 33' 55.60"
GPS:GPSLongitudeRef	West
GPS:GPSAltitudeRef	Above Sea Level
GPS:GPSAltitude	157.641 m

11. Insert final metadata to frames

Video metadata field extracted	Example extracted	Image metadata field injected	Example injected
Trackn:DeviceName	GoPro Max	IFD0:Model	GoPro Max

12. Create photo GPX

Same as step 5, but now only using GPS points added to photos (not all video points added to photos as more video gps than photos).

13. Create sequence json

The sequence JSON holds information about each photo, and its relationship to other photos.

To create this, the following entries are calculated and added in the gpx file:

Name	Field in telemtry	Value	Image metadata (or fixed value)
GPS Epoch	`gps_epoch`	seconds	time converted to epoch
GPS Fix Type	`gps_fix_typ`e		Either 2 or 3 (reported in GoPro GPSMeasureMode field as NDimensional Measurement)
Vertical Accuracy	`gps_vertical_accuracy`	meters	reported in GoPro GPSHPositioningError
Horizontal Accuracy	`gps_horizontal_accuracy`	meters	reported in GoPro GPSHPositioningError
Velocity East	`gps_velocity_east_next`	meters/second	Calculated using GPS lat,lon position/time between this an next photo. For last position, is always 0.
Velocity North	`gps_velocity_north_next`	meters/second	Calculated using GPS lat,lon position/time between this an next photo. For last position, is always 0.
Velocity Up	`gps_velocity_up_next`	meters/second	Calculated using GPS alt position/time between this and next photo. For last position, is always 0.
Speed Accuracy	`gps_speed_accuracy`	meters/second	Always '0.1' (fixed)
Speed	`gps_speed_next`	meters/second	Calculated using GPS lat,lon position/time between this an next photo. For last position, is always 0.
Azimuth (heading)	`gps_azimuth_next`	degrees	Calculated using GPS lat,lon position between this an next photo. For last position, is always 0.
Pitch	`gps_pitch_next`	degrees	Calculated using GPS alt position between this an next photo. For last position, is always 0.
Distance Meters	`gps_distance_next`	meters	Calculated using GPS lat,lon position between this an next photo. For last position, is always 0.
Distance Time	`gps_time_next`	seconds	Calculated using GPS lat,lon position between this an next photo. For last position, is always 0.
Elevation change	`gps_elevation_change_next`	meters	Calculated using GPS elevation position between this an next photo. For last position, is always 0.

gps_time_seconds_next

Is time to next photo.

Uses GPSDateTime values (to subsecond resolution) from each photo. Calculation is:

Photo Next GPSDateTime - Photo Current GPSDateTime

Output in seconds

gps_distance_meters_next

Is distance to next photo lat/lon.

To calculate distance, you can use the Haversine formula to find the distance between two points on a sphere (Earth) given their longitudes and latitudes.

Output is meters

gps_elevation_change_meters_next

Is elevation change to next photo.

Uses elevation values from each photo. Calculation is:

Photo Next Elevation - Photo Elevation

Output in meters.

gps_pitch_degrees_next

Is pitch (or angle) to next photo.

pitch(θ) = tan(θ) = opposite / adjacent

We have the adjacent measurement (gps_distance_meters_next), and the opposite value (gps_elevation_change_meters_next).

Occasionally GPS lat/lon in points is identical, but elevation might change. In this case we default to write pitch as 0. This only happens if distance = 0.

Output is in degrees between -90 and 90

gps_speed_meters_second_next

Is speed to next photo.

Speed = distance / time

We have both these values from above (gps_distance_meters_next and gps_time_seconds_next)

Output is meters per second.

gps_velocity_east_meters_second_next

Is velocity (east vector) to next photo.

Velocity = Displacement / Time in a direction

So Velocity East = Distance (along latitude) / Time (between source and destination)

Or using the diagram above Velocity East = Distance (from A to C) / Time (from A to B)

Note, this calculation can result in a negative output. North and East are positive directions. If you travel West/South, in terms of an East/North vector, you will be traveling in both a negative East/North velocity.

If I drive from home to work (defining my positive direction), then my velocity is positive if I go to work, but negative when I go home from work. It is all about direction seen from how I defined my positive axis.

Output is meters per second (can be negative)

gps_velocity_north_meters_second_next

Is velocity (north vector) to next photo.

Same as above, but...

Velocity North = Distance from C to B) / Time (from A to B)

Output is meters per second (can be negative)

gps_velocity_up_meters_second_next

Is velocity (up/vertical) to next photo.

Same as above, but...

Velocity Up = Elevation change (from A to B) / Time (from A to B)

Output is meters per second (can be negative)

gps_heading_degrees_next

Is heading (from North) to next photo.

Output is degrees between 0-360.

Other sequence json data

Other values included in the json include

sequence.uuid: UUID of the sequence
sequence.distance_km: total distance using all positive distance_mtrs connection values
sequence.earliest_time: earliest time GPSDateTime (if connection method gps / filename) or originalDateTime (if connection originalDateTime) value for photo in sequence
sequence.latest_time: atest time GPSDateTime (if connection method gps / filename) or originalDateTime (if connection originalDateTime) value for photo in sequence
sequence.duration_sec: sequence.latest_time - sequence.earliest_time
sequence.average_speed_kmh: sequence_distance_km / sequence_duration_sec
sequence.camera_make:
sequence.camera_model:

The sequence JSON has the following structure:

{
    "sequence" : {
        "uuid": "",
        "distance_km": "",
        "earliest_time": "",
        "latest_time": "",
        "duration_sec": "",
        "average_speed_kmh": "",
        "camera_make": "",
        "camera_model": ""
    },
    "photo" : [
        {
            "uuid": "",
            "gps_latitude": "",
            "gps_longitude": "",
            "gps_epoch": "",
            "gps_fix_type": "",
            "gps_vertical_accuracy": "",
            "gps_horizontal_accuracy": "",
            "gps_velocity_east_next": "", 
            "gps_velocity_north_next": "",
            "gps_velocity_up_next": "",
            "gps_speed_accuracy": "",
            "gps_speed_next": "",
            "gps_pitch_next": "",
            "gps_distance_next": "",
            "gps_time_next": "",
            "gps_elevation_change_next": "",
        },
        {
            "uuid":
            ....
        }

Step 14: Done

You now have:

a set of geotagged .jpg photos in a directory (SEQUENCENAME_DATETIME/)
a video gpx in the same directory (SEQUENCENAME_video.gpx)
a photo gpx (step 6) in the same directory (SEQUENCENAME_frames.gpx)
a sequence json (SEQUENCENAME_sequence.json)

Image input

1. User defines image and script settings

Users sets desired settings and input.

2 Validate mode vs photo metadata

In order to process the photo in the correct flow, the following logic is checked against mode input.

Validate equirectangular jpg (mode=photo+equirectangular)

See validations: https://docs.google.com/spreadsheets/d/1x9WnLwPHZIKRyfKkCW2ORVprpsAlA3c2hqVu4S9yIaY/edit#gid=459687648

If all validations pass, send to equirectangular frame pipeline.

Validate HERO jpg (mode=photo+hero)

See validations: https://docs.google.com/spreadsheets/d/1x9WnLwPHZIKRyfKkCW2ORVprpsAlA3c2hqVu4S9yIaY/edit#gid=445373652

If all validations pass, send to HERO frame pipeline.

3. Extract metadata from photo

Done using exiftool:

$ exiftool -ee -G3 -X IN_PHOTO.jpg > PHOTO_META.xml

4. Create photo GPX

A GPX file can then be created using all time, elevation (altitude), latitude.

<trkseg>
    <trkpt lat="51.27254444444444" lon="-0.8459694444444444">
        <ele>82.008</ele>
        <time>2021-09-04T07:24:07.744000Z</time>
    </trkpt>
    <trkpt...
      ...
</trkseg>

5 Create sequence JSON

The sequence JSON holds information about each photo, and its relationship to other photos.

(see video flow for how sequence.json is structured)

6. Add logo

Skip if option not selected by user.

(see video flow for how logos are added to photos)

Step 7: Done

You now have:

a set of geotagged .jpg photos in a directory (SEQUENCENAME_DATETIME/)
a photo gpx in the same directory (SEQUENCENAME_frames.gpx)
a sequence json (SEQUENCENAME_sequence.json)

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LOGIC.md

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LOGIC.md

File metadata and controls

How it works

Video input

1. User defines video and script settings

2 Validate mode vs video metadata

3. Extract metadata from video

4. Calculate un-timed GPS points

5. Create video GPX

6. Extract frames at set rate for video type

7. Process to equirectangular for EAC / Fisheyes

7A. MAX2Sphere flow (2 GoPro EAX Frames)

7B. Fusion2Sphere flow (2 GoPro Fisheye Frames)

8. Add logo

8A. Add nadir (equirectangular)

8B. Add watermark (HERO)

9. Insert equirectangular metadata to frames (equirectangular only)

10. Add photo times and add GPS data

10A Add photo times

First frame (all modes)

Other frames (normal mode)

Other frames (timewarp mode)

10B Add GPS points

All frames (all modes)

11. Insert final metadata to frames

12. Create photo GPX

13. Create sequence json

gps_time_seconds_next

gps_distance_meters_next

gps_elevation_change_meters_next

gps_pitch_degrees_next

gps_speed_meters_second_next

gps_velocity_east_meters_second_next

gps_velocity_north_meters_second_next

gps_velocity_up_meters_second_next

gps_heading_degrees_next

Other sequence json data

Step 14: Done

Image input

1. User defines image and script settings

2 Validate mode vs photo metadata

3. Extract metadata from photo

4. Create photo GPX

5 Create sequence JSON

6. Add logo

Step 7: Done