Merge pull request #292 from jlaura/testing (b1648444) · Commits · aflab / astrogeology / Autocnet

.travis.yml

+30 −13

Original line number	Diff line number	Diff line
		language: generic # Since we use conda, just go generic
		sudo: false
		language: generic
		sudo: true

		branches:
		only:
		- dev
		- testing

		os:
		- linux
		- osx
		matrix:
		include:
		- os: linux
		env: PYTHON_VERSION=3.6
		- os: linux
		env: PYTHON_VERSION=3.7

		env:
		- PYTHON_VERSION=3.5
		- PYTHON_VERSION=3.6
		- PYTHON_VERSION=3.7

		# Setup a postgresql instance w/postgis
		services:
		- postgresql
		addons:
		postgresql: 9.6
		apt:
		packages:
		- postgresql-9.6-postgis-2.4

		before_install:
		# Create the template database that is used to instantiate the test DB
		- psql -c 'create database template_postgis;' -U postgres
		- psql template_postgis -U postgres -c "create extension postgis"
		- psql template_postgis -c "create extension postgis_topology"
		- psql -d template_postgis -c "GRANT ALL ON geometry_columns TO PUBLIC;"
		- psql -d template_postgis -c "GRANT ALL ON geography_columns TO PUBLIC;"
		- psql -d template_postgis -c "GRANT ALL ON spatial_ref_sys TO PUBLIC;"

		install:
		# We do this conditionally because it saves us some downloading if the
		# version is the same.
		- if [ "$TRAVIS_OS_NAME" == "linux" ]; then
		@@ -26,6 +44,7 @@ before_install:
		- export PATH="$HOME/miniconda/bin:$PATH"
		- hash -r
		- conda config --set always_yes yes --set changeps1 no
		- conda config --add channels conda-forge
		- conda update -q conda
		# Useful for debugging any issues with conda
		- conda info -a
		@@ -34,13 +53,11 @@ before_install:
		- source activate test

		# Install dependencies
		- conda config --add channels menpo
		- conda config --add channels usgs-astrogeology
		- conda config --add channels conda-forge
		- conda env update -n test -f environment.yml
		- export PROJ_LIB=$CONDA_PREFIX/share/proj

		script:
		- pytest autocnet tests
		- autocnet_config=config/test_config.yml pytest -v autocnet

		after_success:
		- coveralls

README.md

0 → 100644

+29 −0

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		# AutoCNet

		[![Gitter Chat](https://badges.gitter.im/USGS-Astrogeology/autocnet.svg)](https://gitter.im/USGS-Astrogeology/autocnet?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

		[![Travis-CI](https://travis-ci.org/USGS-Astrogeology/autocnet.svg?branch=dev)](https://travis-ci.org/USGS-Astrogeology/autocnet)

		[![Coveralls](https://coveralls.io/repos/USGS-Astrogeology/autocnet/badge.svg?branch=dev&service=github)](https://coveralls.io/github/USGS-Astrogeology/autocnet?branch=dev)

		[![Docs](https://img.shields.io/badge/Docs-latest-green.svg)](https://usgs-astrogeology.github.io/autocnet/)

		Automated sparse control network generation to support photogrammetric control of planetary image data.

		## Documentation
		Is available at: https://usgs-astrogeology.github.io/autocnet/

		## Installation Instructions
		We suggest using Anaconda Python to install Autocnet within a virtual environment. These steps will walk you through the process.

		1. [Download](https://www.continuum.io/downloads) and install the Python 3.x Miniconda installer. Respond ``Yes`` when prompted to add conda to your BASH profile.
		2. Install the autocnet environment using the supplied environment.yml file: `conda env create -n autocnet -f environment.yml`
		3. Activate your environment: `conda activate autocnet`
		4. If you are doing to develop autocnet or would like to use the bleeding edge version: `python setup.py develop`. Otherwise, `conda install -c usgs-astrogeology` autocnet.

		## How to run the test suite locally

		1. Install Docker
		2. Get the Postgresql with Postgis container and run it `docker run --name testdb -e POSTGRES_PASSOWRD='' -e POSTGRES_USER='postgres' -p 5432:5432 -d mdillon/postgis`
		3. create database template_postgis: `docker exec testdb psql -c 'create database template_postgis;' -U postgres`
		4. Run the test suite: `autocnet_config=config/test_config.yml pytest autocnet`

README.rst

deleted100644 → 0

+0 −52

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		===============================
		AutoCNet
		===============================

		.. image:: https://badges.gitter.im/USGS-Astrogeology/autocnet.svg
		:alt: Join the chat at https://gitter.im/USGS-Astrogeology/autocnet
		:target: https://gitter.im/USGS-Astrogeology/autocnet?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge

		.. image:: https://img.shields.io/pypi/v/autocnet.svg
		:target: https://pypi.python.org/pypi/autocnet

		.. image:: https://travis-ci.org/USGS-Astrogeology/autocnet.svg?branch=master
		:target: https://travis-ci.org/USGS-Astrogeology/autocnet

		.. image:: https://coveralls.io/repos/USGS-Astrogeology/autocnet/badge.svg?branch=master&service=github
		:target: https://coveralls.io/github/USGS-Astrogeology/autocnet?branch=master

		.. image:: https://img.shields.io/badge/Docs-latest-green.svg
		:target: hhttps://usgs-astrogeology.github.io/autocnet/
		:alt: Documentation Status

		.. image:: https://badge.waffle.io/USGS-Astrogeology/autocnet.png?label=ready&title=Ready
		:target: https://waffle.io/USGS-Astrogeology/autocnet
		:alt: 'Stories in Ready'

		Automated sparse control network generation to support photogrammetric control of planetary image data.

		* Documentation: https://usgs-astrogeology.github.io/autocnet/

		Installation Instructions
		-------------------------
		We suggest using Anaconda Python to install Autocnet within a virtual environment. These steps will walk you through the process.

		#. [Download](https://www.continuum.io/downloads) and install the Python 3.x Miniconda installer. Respond ``Yes`` when
		prompted to add conda to your BASH profile.
		#. (Optional) We like to sequester applications in their own environments to avoid any dependency conflicts. To do this:

		* ``conda create -n <your_environment_name> python=3 && source activate <your_environment_name>``

		Note, that you might want to specify either ``python=3.5`` or ``python=3.6``, depending on your requirements. Both are currently supported by autocnet.
		#. Make the newly created environment the active one:

		* ``conda activate <your_environment_name>`` (or ``source activate`` on an older conda system)

		#. Bring up a command line and add three channels to your conda environment-specific config file:

		* ``conda config --env --add channels conda-forge``
		* ``conda config --env --add channels menpo``
		* ``conda config --env --add channels usgs-astrogeology``
		#. Finally, install autocnet: ``conda install autocnet``

autocnet/camera/camera.py

+2 −2

Original line number	Diff line number	Diff line
		import numpy as np
		from autocnet.camera.utils import crossform
		import cv2
		from cv2 import triangulatePoints



		@@ -102,7 +102,7 @@ def triangulate(pt, pt1, p, p1):
		if pt1.shape[0] != 3:
		pt1 = pt1.T

		X = cv2.triangulatePoints(p, p1, pt[:2], pt1[:2])
		X = triangulatePoints(p, p1, pt[:2], pt1[:2])
		X /= X[3] # Homogenize
		return X

autocnet/io/db/model.py

+8 −18

Original line number	Diff line number	Diff line
		@@ -16,10 +16,12 @@ from sqlalchemy.types import TypeDecorator
		from geoalchemy2 import Geometry
		from geoalchemy2.shape import to_shape

		from autocnet import engine, Session
		from autocnet import engine, Session, config

		Base = declarative_base()

		srid = config['spatial']['srid']

		class JsonEncoder(json.JSONEncoder):
		def default(self, obj):
		if isinstance(obj, np.ndarray):
		@@ -116,7 +118,7 @@ class Keypoints(Base):
		id = Column(Integer, primary_key=True, autoincrement=True)
		image_id = Column(Integer, ForeignKey("images.id", ondelete="CASCADE"))
		convex_hull_image = Column(Geometry('POLYGON'))
		convex_hull_latlon = Column(Geometry('POLYGON', srid=949900))
		convex_hull_latlon = Column(Geometry('POLYGON', srid=srid))
		path = Column(String)
		nkeypoints = Column(Integer)

		@@ -159,7 +161,7 @@ class Matches(Base):
		destination_idx = Column(Integer, nullable=False)
		lat = Column(Float)
		lon = Column(Float)
		geom = Column(Geometry('POINT', dimension=2, srid=949900, spatial_index=True))
		geom = Column(Geometry('POINT', dimension=2, srid=srid, spatial_index=True))
		source_x = Column(Float)
		source_y = Column(Float)
		destination_x = Column(Float)
		@@ -184,7 +186,7 @@ class Images(Base):
		path = Column(String)
		serial = Column(String, unique=True)
		active = Column(Boolean)
		footprint_latlon = Column(Geometry('MultiPolygon', srid=949900, dimension=2, spatial_index=True))
		footprint_latlon = Column(Geometry('MultiPolygon', srid=srid, dimension=2, spatial_index=True))
		footprint_bodyfixed = Column(Geometry('MULTIPOLYGON', dimension=2))
		#footprint_bodyfixed = Column(Geometry('POLYGON',dimension=3))

		@@ -204,24 +206,12 @@ class Images(Base):
		'footprint_latlon':footprint,
		'footprint_bodyfixed':self.footprint_bodyfixed})

		"""class Network(Base):
		__tablename__ = 'network'
		id = Column(Integer, primary_key=True, autoincrement=True)
		#TODO: Document that images on delete will CASCADE into all other tables
		image_id = Column(Integer, ForeignKey("images.id", ondelete="CASCADE")) # Links back to the source image
		match_id = Column(Integer)
		point_id = Column(String) # User defined point identifier
		keypoint_id = Column(Integer) # id to link to a keypoint in the correct file
		x = Column(Float)
		y = Column(Float)
		geom = Column(Geometry('POINTZ', dimension=3, srid=949900, spatial_index=True))"""

		class Overlay(Base):
		__tablename__ = 'overlay'
		id = Column(Integer, primary_key=True, autoincrement=True)
		intersections = Column(ARRAY(Integer))
		#geom = Column(Geometry(geometry_type='POLYGON', management=True)) # sqlite
		geom = Column(Geometry('POLYGON', srid=949900, dimension=2, spatial_index=True)) # postgresql
		geom = Column(Geometry('POLYGON', srid=srid, dimension=2, spatial_index=True)) # postgresql


		class PointType(enum.IntEnum):
		@@ -237,7 +227,7 @@ class Points(Base):
		id = Column(Integer, primary_key=True, autoincrement=True)
		pointtype = Column(IntEnum(PointType), nullable=False) # 2, 3, 4 - Could be an enum in the future, map str to int in a decorator
		identifier = Column(String, unique=True)
		geom = Column(Geometry('POINT', srid=949900, dimension=2, spatial_index=True))
		geom = Column(Geometry('POINT', srid=srid, dimension=2, spatial_index=True))
		active = Column(Boolean, default=True)
		apriorix = Column(Float)
		aprioriy = Column(Float)