Metadata-Version: 2.1
Name: ellipsis-AI
Version: 0.0.1
Summary: Package to use Ellipsis Drive for AI
Home-page: https://github.com/ellipsis-drive-internal/python-package-AI
Author: Daniel van der Maas
Author-email: daniel@ellipsis-drive.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: ellipsis
Requires-Dist: numpy
Requires-Dist: math
Requires-Dist: datetime
Requires-Dist: tifffile
Requires-Dist: io
Requires-Dist: requests
Requires-Dist: os
Requires-Dist: rasterio

This package is meant to help you run models on Ellipsis Drive content.


applyModel(model, blockId, captureId, targetBlockId, targetCaptureId, visualizationId, inputWidth, token)

model must be a function mapping a (inputWidth,inputWidth,b) numpy array to an (inputWidth,inputWidth) numpy array.

model: a function mapping a inputWidth by inputWidth by bands numpy array to a 3 dimensional numpy array. The resulting numpy array should always have the same shape.
blockId: the id of the block to classify
captureId: the id of the capture to classify
targetBlockId: the id of the block to write the classifications to
targetCaptureId: the id of the capture to write the classifications to
inputWidth: the size of the input array. Must be a number divisible by 256
visualizationId: id of the visualization to use as input. If not specified the original raster is used.
token: your token




