Hi everyone,
For the next month we’ll be experimenting with a new Mapillary challenge which will leverage Mapillary computer vision technology to improve OpenStreetMap. We’re working with the community in select locations to take features we’ve detected automatically and convert them to map data in OpenStreetMap.
The process is pretty simple:
Mapillary provides GeoJSON that shows the location of benches, mailboxes, and rubbish bins that we have detected. Each GeoJSON represents an area of 25 square kilometers. This should be enough map data for a meaningful challenge, whilst giving each group the opportunity to add every detected feature and achieve 100% completion.
There is also the opportunity for each group to collect more imagery during the challenge and request new downloads of the data. This can be done three times during the challenge by each group which will allow the groups to capture new streets or improve the quality of imagery if a particular feature has not been picked up in that area.
Each changeset will have #mapillary2osm in the comments to help inform us when an edit is linked to the competition. Edits will be tracked on this leaderboard and ranked according to the number of relevant nodes added by each username.
This is very much an experiment, but we’re hoping it will help to inform us on how our detected map features can be converted to OpenStreetMap data. This will inform our improvements to OpenStreetMap’s Mapillary integrations.
If you would like your location to be considered for future challenges, comment below with the latitude and longitude of the area.
This is an important step in understanding how we can convert automatically derived data to useful map data in the OpenStreetMap.
We’re looking forward to seeing the results.
Best,
Ed & Team
The plan:
Make sure you read through the following to know how to participate and have your edits included on the leaderboard.
Challenge structure
- Take a look at your zone: 25 square kilometre zones have been created around each of the lat/lons that were put forward by each community group. This should be enough to get a decent number of point features, but also an area that can be completed to 100% for the derived features.
- Download map features: Find the map feature data for your area and download it. The map features are provided as a GeoJSON file and can be viewed in iD Editor by going to ‘Map Data’ on the sidebar and then loading the GeoJSON file where it says ‘Custom Map Data’. You will see the detections as pink circles on the map. Use the Mapillary street-level imagery layer to see which images the map features have been detected in.
The map features contained in the GeoJSON are provided under the ODbL license and may not be used for any purpose other than OpenStreetMap editing.
- Edit the map:
- Take a look at the detected feature and the image it was detected in. If it’s not on the map, add it!
- Edits should be creating one of the following objects:
- Add the hashtag #mapillary2osm to the changeset so that we can link these edits to the #mapillary2osm challenge.
- If you are a relatively new mapper, select ‘I would like someone to review my edits’ when saving the changeset.
- If it looks like each location will complete all map edits well before the end of the challenge, we may release other map feature data. These will appear in the same folders.
- Capture more imagery: Contributors can capture more imagery in the target area and request new map feature data 3 times during the competition. This is 3 requests per location, not per individual, so coordinate as a team to make sure you capture imagery and request map data at the right times. Requests to be sent to me as a private message.
The leaderboard will update hours after you make the edits with the total reflecting the sum of nodes created that have one of the three tags.
Timeline
16th of April: Map feature data made available and challenge begins
16th of May: Challenge closes.
20th of May: Results announced.
Target locations
Here are the 6 locations selected for this initial experiment. We encourage people to contribute to the location only if they reside in the same country.
- Antwerp, Belgium (coming soon)
- Austin, United States
- Ballerup, Denmark
- Kyiv, Ukraine
- Melbourne, Australia
- São Paulo, Brazil
Comment below if you are interested in participating in future map editing. Provide the latitude and longitude of the area you would like to start editing.
Map features in focus:
- amenity=bicycle_parking | Bike rack in Mapillary
- amenity=post_box | Mailbox in Mapillary
- amenity=bench | Bench in Mapillary
Prizes
The top 5 participants in the most active area will receive an assortment of Mapillary swag. A minimum of 5 edits are required to be eligible for the prize.
Disclaimers
Please keep in mind that these edits are going to OpenStreetMap and affecting real people who rely on these maps.
- Make sure all edits you make are reflecting the reality on the ground. This means you should not be:
- Making fake edits to increasing your score.
- Adding false detections to the map. Just because Mapillary says an object is there, doesn’t mean it really is.
- Adding the wrong tags to objects.
- The map data provided in each GeoJSON is to be used for OpenStreetMap contributions only. It is not to be used for any commercial purposes.
- The quality and quantity of detections will vary between each of the participating locations. This is inevitable. One objective with this challenge is to work out how the detection accuracy varies between locations. You can help to improve the detection accuracy by capturing high quality images in your area. This will increase the chance of an object being identified but also provide an opportunity for more training date in future.
