Updates to hirise change detection (#411)

import numpy as np

from matplotlib.path import Path

from shapely.geometry import Point, MultiPoint

from autocnet.matcher.cpu_extractor import extract_features

def image_diff(arr1, arr2):

     arr1 = arr1.astype("float32")

     arr2 = arr2.astype("float32")

     arr1[arr1 == 0] = np.nan

     arr2[arr2 == 0] = np.nan

     diff = arr1-arr2

     diff[np.isnan(diff)] = 0

    bdiff = bytescale(diff)

    return bdiff

     return bytescale(diff)

def okubogar_detector(image1, image2, nbins=50, extractor_method="orb", extractor_kwargs={"nfeatures": 2000, "scaleFactor": 1.1, "nlevels": 1}, image_func=image_diff):

def okubogar_detector(image1, image2, nbins=50, extractor_method="orb", extractor_kwargs={"nfeatures": 2000, "scaleFactor": 1.1, "nlevels": 1}, cluster_params={"min_samples": 10, "max_eps": 10, "eps": .5, "xi":.5},  image_func=image_diff):

     arr1 = image1.read_array()

     arr2 = image2.read_array()

    arr1[arr1 == arr1.min()] = np.nan

    arr2[arr2 == arr2.min()] = np.nan

     arr1[arr1 == arr1.min()] = 0

     arr2[arr2 == arr2.min()] = 0

     arr1 = bytescale(arr1)

     arr2 = bytescale(arr2)

     bdiff = image_func(arr1, arr2)

     points = [Point(xval, yval) for xval,yval in zip(x,y)]

    optics = OPTICS(min_samples=10, max_eps=20,  eps=.3, p=2, xi=.5).fit(list(zip(x,y)))

     optics = OPTICS(**cluster_params).fit(list(zip(x,y)))

     classes = gpd.GeoDataFrame(columns=["label", "point"], geometry="point")

     classes["label"] = optics.labels_

         polys.append(poly)

         weights.append(weight)

    return polys, weights

     return polys, weights, bdiff