Commit 269ab105 authored by Jay's avatar Jay Committed by jay
Browse files

Yanked path stuff that was not working, reworked single node visualization.

parent 1ee60f43

.coveragerc

+1 −0
Original line number Diff line number Diff line
@@ -4,6 +4,7 @@ source = autocnet 
omit =

    fileio/ControlNetFileV0002_pb2.py

    utils/visualization.py

    vis/*

exclude_lines =

    pragma: no cover

    def __repr__

autocnet/examples/Apollo15/two_image_adjacency.json

+2 −4
Original line number Diff line number Diff line 
{"autocnet/examples/Apollo15/AS15-M-0297_SML.png"

 : ["autocnet/examples/Apollo15/AS15-M-0298_SML.png"], 

 "autocnet/examples/Apollo15/AS15-M-0298_SML.png"

 : ["autocnet/examples/Apollo15/AS15-M-0297_SML.png"]}
 
{"AS15-M-0297_SML.png" : ["AS15-M-0298_SML.png"], 

 "AS15-M-0298_SML.png" : ["AS15-M-0297_SML.png"]}

autocnet/graph/network.py

+7 −8
Original line number Diff line number Diff line
@@ -14,7 +14,7 @@ from autocnet.matcher import feature_extractor as fe # extract features from ima 
from autocnet.matcher import outlier_detector as od

from autocnet.matcher import subpixel as sp

from autocnet.cg.cg import convex_hull_ratio, overlapping_polygon_area



from autocnet.vis.graph_view import plot_node



class Edge(object):

    """
@@ -325,6 +325,7 @@ class Node(object): 
        mask = od.adaptive_non_max_suppression(self.keypoints,nfeatures,robust)

        self.masks = ('anms', mask)





    def convex_hull_ratio(self, clean_keys=[]):

        """

        Compute the ratio $area_{convexhull} / area_{total}$
@@ -347,6 +348,9 @@ class Node(object): 
        ratio = convex_hull_ratio(keypoints, ideal_area)

        return ratio



    def plot(self, clean_keys=[], **kwargs):

        return plot_node(self, clean_keys=clean_keys, **kwargs)



    def update(self, *args):

        # Empty pass method to get NetworkX to accept a non-dict

        pass
@@ -377,13 +381,8 @@ class CandidateGraph(nx.Graph): 


        # the node_name is the relative path for the image

        for node_name, node in self.nodes_iter(data=True):



            if os.path.isabs(node_name):

            image_name = os.path.basename(node_name)

            image_path = node_name

            else:

                image_name = os.path.basename(os.path.abspath(node_name))

                image_path = os.path.abspath(node_name)



            # Replace the default node dict with an object

            self.node[node_name] = Node(image_name, image_path)

autocnet/vis/__init__.py

0 → 100644
+0 −0

Empty file added.

autocnet/utils/visualization.py→autocnet/vis/graph_view.py

+38 −27
Original line number Diff line number Diff line
@@ -8,12 +8,9 @@ from autocnet.fileio.io_gdal import GeoDataset # set handle, get image as array 
from matplotlib import pyplot as plt # plotting 





def plotFeatures(imageName, keypoints, pointColorAndHatch='b.', featurePointSize=7):

def plot_node(node, ax=None, clean_keys=[], **kwargs):

    """

    Plot an image and its found features using the image file name and 

    a keypoint list found using autocnet.feature_extractor. The user may

    also specify the color and style of the points to be plotted and the

    size of the points.

    Plot the array and keypoints for a given node.



    Parameters

    ----------
@@ -21,35 +18,49 @@ def plotFeatures(imageName, keypoints, pointColorAndHatch='b.', featurePointSize 
                The base name of the image file (without path). 

                This will be the title of the plot.



    keypoints : list

                The keypoints of this image found by the feature extractor.

    ax : object

         A MatPlotLIb axes object



    pointColorAndHatch : str

                         The color and hatch (symbol) to be used to mark

                         the found features. Defaults to 'b.', blue and 

                         square dot. See matplotlib documentation for

                         more choices.



    featurePointSize : int

                       The size of the point marker. Defaults to 7.

    clean_keys : list

                 of strings of masking array names to apply



    kwargs : dict

             of MatPlotLib plotting options

    """



    imgArray = GeoDataset(get_path(imageName)).read_array()

    height, width = imgArray.shape[:2]

    if ax is None:

        ax = plt.gca()



    displayBox = np.zeros((height, width), np.uint8)

    displayBox[:height, :width] = imgArray

    band = 1

    if 'band' in kwargs.keys():

        band = kwargs['band']

        kwargs.pop('band', None)



    plt.title(imageName)

    plt.margins(tight=True)

    plt.axis('off')

    plt.imshow(displayBox, cmap='Greys')

    array = node.get_array(band)



    for kp in keypoints: 

        x,y = kp.pt

        plt.plot(x,y,pointColorAndHatch, markersize=featurePointSize)

    ax.set_title(node.image_name)

    ax.margins(tight=True)

    ax.axis('off')



    if 'cmap' in kwargs:

        cmap = kwargs['cmap']

    else:

        cmap = 'Greys'



    ax.imshow(array, cmap=cmap)



    keypoints = node.keypoints

    if clean_keys:

        mask = np.prod([node._mask_arrays[i] for i in clean_keys], axis=0, dtype=np.bool)

        keypoints = node.keypoints[mask]



    marker = '.'

    if 'marker' in kwargs.keys():

        marker = kwargs['marker']

        kwargs.pop('marker', None)

    ax.scatter(keypoints['x'], keypoints['y'], marker=marker, **kwargs)



    return ax





def plotAdjacencyGraphFeatures(graph, pointColorAndHatch='b.', featurePointSize=7):