Run label maker as a dask job
Project description
label-maker-dask
Library for running label-maker as a dask job
Basic Example
Instantiate a distributed dask cluster
from dask.distributed import Client
cluster = ...
client = Client(cluster)
Create a label maker job
from label_maker_dask import LabelMakerJob
lmj = LabelMakerJob(
zoom=13,
bounds=[-44.4836425781, -23.02665962797, -43.412719726, -22.5856399016],
classes=[
{ "name": "Roads", "filter": ["has", "highway"] },
{ "name": "Buildings", "filter": ["has", "building"] }
],
imagery="http://a.tiles.mapbox.com/v4/mapbox.satellite/{z}/{x}/{y}.jpg?access_token=ACCESS_TOKEN",
ml_type="segmentation",
label_source="https://qa-tiles-server-dev.ds.io/services/z17/tiles/{z}/{x}/{y}.pbf"
)
Build & execute the job
lmj.build_job()
lmj.execute_job()
View or otherwise use the results (by passing to a machine learning framework)
for result in lmj.results:
...
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
label-maker-dask-0.1.1.tar.gz
(8.7 kB
view hashes)
Built Distribution
Close
Hashes for label_maker_dask-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7b0d17d9ac9e57e7c8d18ec635b6db57c5ce71729d8e3e6538239a8e95c5941a |
|
MD5 | 14478f57397a69a875b277c550d7103b |
|
BLAKE2b-256 | 32a6ad06ad5e1739c1eded044e822a5488a57b3d1738105206367220d5c665c1 |