automate/improve infrastructure

[andrewljohnson]

This issue describes how deeposm works now. Then it describes changes needed to improve the infrastructure. Also see notes/scripts on these issues: #8, #23, #30, and #39 (these issues were closed to merge with this issue, not completed).

Test Data and Training

• one app does both the data prep, and neural net training
• it uses a GPU/Tensorflow on a Linux box in my office
• findings are then uploaded to S3

Display on deeposm.org

• when a deeposm.org page is loaded, it checks S3, grabs findings, and updates the database
• deeposm.org shows where DeepOSM detects mis-registered roads

Issues with this Setup

• The scripts to gather data, train, and upload findings should run on a cycle, not manually when I press a button
• The data prep and training modules should be separate - DeepOSM has one monster Dockerfile.gpu-devel that includes GDAL, Tensorflow, and more. This makes the build fragile and hard to deploy.
• Actual work includes:
  • move the analysis to AWS, run on a cycle
  • set up a cron job to have deeposm.org check for new findings
  • parallelize the analysis, so we can do deeper nets and more area
  • import NAIPs into Postgres, instead of hacking them up and caching files
  • use Overpass or other approach to getting OSM data, instead of hacking up PBF extracts with Osmium

[anandthakker]

use Overpass or other approach to getting OSM data, instead of hacking up PBF extracts with Osmium

@andrewljohnson have you considered OSM QA Tiles?

[andrewljohnson]

@anandthakker I'm probably wrong, but I decided it doesn't really help me to use "tiled" data, because my source imagery isn't projected to Mercator, or tiled into a TMS pyramid?

When I did my first run at this, I used Mapzen vector tiles, plus TMS imagery tiles (since they align). But when I switched to NAIPs, it seemed to make more sense (less code) to clip some line strings to the bounds of my NAIPs or arbitrary tiles.

So that's also why I think my end solution is a planet DB with an API, and maybe that API is Overpass, or something simple I just cook up for this use case?

[anandthakker]

Ah -- yeah, I see what you mean. I went the tiled route for skynet-data basically because between existing tiled satellite source (Mapbox Satellite, DG, etc.) and OSM QA tiles, I figured I could skip a lot of the work. Since you've already handled chopping up the NAIP images, I agree that using tiles provides less of a benefit... Although, I guess one upside to going the tiled route would be that maybe it would be easier, in the future, to swap in a different imagery source (without your having to host/maintain/process it as much). Might not be worth it if you don't see yourself going that route, though

[brandongalbraith]

Have you considered running the analysis at Digital Ocean and pushing the results into S3 from there? The compute at DO is significantly cheaper than at AWS.

[andrewljohnson]

@brandongalbraith The analysis runs at home on a Linux box I have.

also: I might try out some Google ML infrastructure, just got my invite yesterday.

[brandongalbraith]

@andrewljohnson

Sorry about that! I inferred from above:

Actual work includes:
move the analysis to AWS, run on a cycle

that the analysis was planned to run in AWS. Happy to help break everything apart to scale it out, my day gig is devops/infrastructure.

[andrewljohnson]

@brandongalbraith i realized that after I answered too fast :)

I guess the right answer is I hadn't much thought about it.