Commit 52360416 authored by jlaura's avatar jlaura Committed by Kelvin Rodriguez
Browse files

Updates for testing control and ring_matching (#265) 

* updates to get control tests updated

* Updates tests for ring matcher

* Refactors OpenCV SIFT extractor out of unit/functional tests

* Removes unused control code

* Should fix failing conda build

* pyproj datdir issues

* Working on deprecation fixes for scipy imread

* Swapping imageio
parent 97c0ad20

.travis.yml

+1 −1
Original line number Diff line number Diff line
@@ -38,7 +38,7 @@ before_install: 
  - 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/__init__.py

+13 −2
Original line number Diff line number Diff line
@@ -12,12 +12,23 @@ import autocnet.matcher 
import autocnet.transformation

import autocnet.utils



from pkg_resources import get_distribution, DistributionNotFound

try:

    _dist = get_distribution('autocnet')

    # Normalize case for Windows systems

    dist_loc = os.path.normcase(_dist.location)

    here = os.path.normcase(__file__)

    if not here.startswith(os.path.join(dist_loc, 'autocnet')):

        # not installed, but there is another version that *is*

        raise DistributionNotFound

except DistributionNotFound:

    __version__ = 'Please install this project with setup.py'

else:

    __version__ = _dist.version



# Patch the candidate graph into the root namespace

from autocnet.graph.network import CandidateGraph



__version__ = "0.1.0"



def get_data(filename):

    packagdir = autocnet.__path__[0]

    dirname = os.path.join(os.path.dirname(packagdir), 'data')

autocnet/camera/camera.py

+3 −23
Original line number Diff line number Diff line 
import numpy as np

from autocnet.camera.utils import crossform

try:

import cv2

except:

    cv2 = None







def compute_epipoles(f):
@@ -103,29 +101,11 @@ def triangulate(pt, pt1, p, p1): 
        pt = pt.T

    if pt1.shape[0] != 3:

        pt1 = pt1.T

    #if cv2:



    X = cv2.triangulatePoints(p, p1, pt[:2], pt1[:2])

    X /= X[3] # Homogenize

    return X

    """

    # Stubbed in for a ticket addressing making OpenCV an optional dependency

    else:

        npts = len(pt)

        a = np.zeros((4, 4))

        coords = np.empty((npts, 4))

        coords[:] = 1

        for i in range(npts):

            # Compute AX = 0

            a[0] = pt[i][0] * p[2] - p[0]

            a[1] = pt[i][1] * p[2] - p[1]

            a[2] = pt1[i][0] * p1[2] - p1[0]

            a[3] = pt1[i][1] * p1[2] - p1[1]

            # v.T is a least squares solution that minimizes the error residual

            u, s, vh = np.linalg.svd(a)

            v = vh.T

            coords[i] = v[:,3] / (v[:,3][-1])

        return coords.T

    """



def projection_error(p1, p, pt, pt1):

    """

    Based on Hartley and Zisserman p.285 this function triangulates

autocnet/control/control.py

+1 −36
Original line number Diff line number Diff line
@@ -10,37 +10,6 @@ from autocnet.matcher import subpixel as sp 
from plio.io.io_controlnetwork import to_isis, write_filelist





def subpixel_match(cg, cn, threshold=0.9, template_size=19, search_size=53, max_x_shift=1.0, max_y_shift=1.0, **kwargs):



    def subpixel_group(group, threshold=0.9, template_size=19, search_size=53, max_x_shift=1.0, max_y_shift=1.0, **kwargs):

        offs = []

        for i, (idx, r) in enumerate(group.iterrows()):

            if i == 0:

                x = r.x

                y = r.y

                offs.append([0, 0, np.inf])

                continue



            e = r.edge

            s_img = cg.edge[e[0]][e[1]].source.geodata

            s_template = sp.clip_roi(s_img, (x, y), template_size)

            # s_template = cv2.Canny(bytescale(s_template), 50,100) # Canny - bad idea

            d_img = cg.edge[e[0]][e[1]].destination.geodata

            d_search = sp.clip_roi(d_img, (r.x, r.y), search_size)

            #d_search = cv2.Canny(bytescale(d_search), 50,100)



            xoff, yoff, corr = sp.subpixel_offset(

                s_template, d_search, **kwargs)

            offs.append([xoff, yoff, corr])

        df = pd.DataFrame(

            offs, columns=['x_off', 'y_off', 'corr'], index=group.index)

        return df

    gps = cn.data.groupby('point_id').apply(subpixel_group, threshold=0.9, max_x_shift=5,

                                            max_y_shift=5, template_size=template_size, search_size=search_size, **kwargs)

    cn.data[['x_off', 'y_off', 'corr']] = gps.reset_index()[

        ['x_off', 'y_off', 'corr']]





def identify_potential_overlaps(cg, cn, overlap=True):

    """

    Identify those points that could have additional measures
@@ -67,7 +36,7 @@ def identify_potential_overlaps(cg, cn, overlap=True): 
    candidate_cliques = []

    geoms = []

    idx = []

    for i, p in cn.data.groupby('point_id'):

    for i, p in cn.groupby('point_id'):

        # Which images are covered already.  This finds any connected cycles that

        #  a node is in (this can be more than one - an hourglass network for example)

        # Extract the fully connected subgraph for each covered image in order to
@@ -123,7 +92,3 @@ def identify_potential_overlaps(cg, cn, overlap=True): 
        return candidate_cliques.query('overlap == True')['candidates']

    else:

        return candidate_cliques.candidates
 




def deepen_correspondences(cg, cn):

    pass

autocnet/control/tests/test_control.py

+28 −26
Original line number Diff line number Diff line 
"""from unittest.mock import MagicMock

from unittest.mock import MagicMock

import geopandas as gpd

import pandas as pd

from shapely.geometry import Polygon



import pytest

from autocnet.control import control



import os

import sys

sys.path.insert(0, '..')

from .. import control

def test_identify_potential_overlaps(controlnetwork, candidategraph):

    res = control.identify_potential_overlaps(candidategraph,

                                              controlnetwork,

                                              overlap=False)



    assert res.equals(pd.Series([(2,), (2,),

                                 (1,), (1,),

                                 (0,), (0,)],

                                 index=[6,7,8,9,10,11]))



def test_potential_overlap(controlnetwork, candidategraph):

    # Patch in an intersection check so that all points intersect all geoms

    candidategraph.create_node_subgraph = MagicMock(return_value=candidategraph)

    coords = [(-1., -1.), (-1., 1.), (1., 1.), (1., -1.), (-1., -1.)]

    poly = gpd.GeoSeries(Polygon(coords))

    candidategraph.compute_intersection = MagicMock(return_value=(poly, 0))

    res = control.identify_potential_overlaps(candidategraph,

                                              controlnetwork,

                                              overlap=True)



    assert res.equals(pd.Series([(2,), (2,),

                                 (1,), (1,),

                                 (0,), (0,)],

                                 index=[6,7,8,9,10,11]))



"""

def test_fromcandidategraph(candidategraph, controlnetwork_data):#, controlnetwork):

    matches = candidategraph.get_matches()

    cn = control.ControlNetwork.from_candidategraph(matches)
@@ -42,28 +65,7 @@ def test_bad_validate_points(bad_controlnetwork): 
    assert bad_controlnetwork.validate_points().iloc[0] == True

    assert not bad_controlnetwork.validate_points().iloc[1:].all()



def test_identify_potential_overlaps(controlnetwork, candidategraph):

    res = control.identify_potential_overlaps(candidategraph,

                                              controlnetwork,

                                              overlap=False)



    assert res.equals(pd.Series([(2,), (2,),

                                 (1,), (1,),

                                 (0,), (0,)],

                                 index=[6,7,8,9,10,11]))



def test_potential_overlap(controlnetwork, candidategraph):

    # Patch in an intersection check so that all points intersect all geoms

    candidategraph.create_node_subgraph = MagicMock(return_value=candidategraph)

    coords = [(-1., -1.), (-1., 1.), (1., 1.), (1., -1.), (-1., -1.)]

    poly = gpd.GeoSeries(Polygon(coords))

    candidategraph.compute_intersection = MagicMock(return_value=(poly, 0))

    res = control.identify_potential_overlaps(candidategraph,

                                              controlnetwork,

                                              overlap=True)



    assert res.equals(pd.Series([(2,), (2,),

                                 (1,), (1,),

                                 (0,), (0,)],

                                 index=[6,7,8,9,10,11]))

"""
 
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