Exemplo n.º 1
0
def cluster(targetLocationPath, probabilityPath, iterationCountPerBurst, maximumGeoDiameter, minimumGeoDiameter):
    # Initialize
    probabilityInformation = probability_store.Information(probabilityPath)
    imagePath = probabilityInformation.getImagePath()
    imageInformation = image_store.Information(imagePath)
    multispectralImage = imageInformation.getMultispectralImage()
    multispectralGeoTransform = multispectralImage.getGeoTransform()
    spatialReference = multispectralImage.getSpatialReference()
    # Convert maximumGeoDiameter into maximumPixelDiameter
    maximumPixelDiameter = max(
        image_store.convertGeoDimensionsToPixelDimensions(
            maximumGeoDiameter, maximumGeoDiameter, multispectralGeoTransform
        )
    )
    # Convert minimumGeoDiameter into minimumPixelDiameter
    minimumPixelDiameter = max(
        image_store.convertGeoDimensionsToPixelDimensions(
            minimumGeoDiameter, minimumGeoDiameter, multispectralGeoTransform
        )
    )
    # Load pixelDimensions
    windowGeoLength = probabilityInformation.getWindowLengthInMeters()
    pixelWidth, pixelHeight = image_store.convertGeoDimensionsToPixelDimensions(
        windowGeoLength, windowGeoLength, multispectralGeoTransform
    )
    # Cluster
    probabilityPacks = probability_store.load(probabilityPath)
    vectors = [(x, y, probability) for x, y, label, probability in probabilityPacks if label == 1]
    windowLocations = grapeCluster(vectors, iterationCountPerBurst, maximumPixelDiameter, minimumPixelDiameter)
    windowCenters = [(xy[0] + pixelWidth / 2, xy[1] + pixelHeight / 2) for xy in windowLocations]
    geoCenters = image_store.convertPixelLocationsToGeoLocations(windowCenters, multispectralGeoTransform)
    # Save
    point_store.save(targetLocationPath, geoCenters, spatialReference)
def saveShapefile(targetPath, sourceProbabilityPath, multispectralImage, windowLengthInMeters):
    # Get pixelDimensions
    windowPixelWidth, windowPixelHeight = multispectralImage.convertGeoDimensionsToPixelDimensions(windowLengthInMeters, windowLengthInMeters)
    # Load positiveProbabilityPacks
    positiveProbabilityPacks = load(sourceProbabilityPath, withNegative=False)
    # Center
    positivePixelCenters = [(x[0] + windowPixelWidth / 2, x[1] + windowPixelHeight / 2) for x in positiveProbabilityPacks]
    # Convert
    positiveGeoCenters = multispectralImage.convertPixelLocationsToGeoLocations(positivePixelCenters)
    # Save
    point_store.save(targetPath, positiveGeoCenters, multispectralImage.getSpatialReference())
Exemplo n.º 3
0
def buildPatch(
    targetPatchPath, pixelCenters, actualPixelPointMachine, multispectralImage, panchromaticImage, windowLengthInMeters
):
    # Set paths
    targetPositivePath = targetPatchPath + "_positive"
    targetNegativePath = targetPatchPath + "_negative"
    # Label
    positivePatchPixelCenters, negativePatchPixelCenters = labelPixelCenters(pixelCenters, actualPixelPointMachine)
    # Convert
    positivePatchGeoCenters = multispectralImage.convertPixelLocationsToGeoLocations(positivePatchPixelCenters)
    negativePatchGeoCenters = multispectralImage.convertPixelLocationsToGeoLocations(negativePatchPixelCenters)
    # Save
    spatialReference = multispectralImage.getSpatialReference()
    point_store.save(targetPositivePath, positivePatchGeoCenters, spatialReference)
    point_store.save(targetNegativePath, negativePatchGeoCenters, spatialReference)
    # Extract
    window_process.extract(
        targetPositivePath, positivePatchGeoCenters, 1, windowLengthInMeters, multispectralImage, panchromaticImage
    )
    window_process.extract(
        targetNegativePath, negativePatchGeoCenters, 0, windowLengthInMeters, multispectralImage, panchromaticImage
    )
    # Combine
    return sample_process.combineDatasets(targetPatchPath, [targetPositivePath, targetNegativePath])
 def save(fileName, points):
     targetPath = os.path.join(targetFolderPath, fileName)
     point_store.save(targetPath, points, spatialReference)
        XY_Shoreline = geo_rect_func.rotate_translate(
            np.asarray(XY_shor_und[:, 0, 0], dtype='float64'),
            np.asarray(XY_shor_und[:, 0, 1], dtype='float64'),
            rotation=None,
            translation=tuple(translation))

        #saving real-world coordinates of shoreline
        xy_srl = zip(list(XY_Shoreline[0]), list(XY_Shoreline[1]))
        try:
            shrl_name = sys.argv[3]
        except:
            shrl_name = str(shl + '.shp')
            print 'File shoreline shp saved to', shrl_name
        #point_store.save(shrl_name,xy_srl,'+proj=utm +zone=33 +ellps=WGS84 +datum=WGS84 +units=m +no_defs ')
        point_store.save(
            shrl_name, xy_srl,
            '+proj=utm +zone=33 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs '
        )
        reader = shapefile.Reader(shrl_name)
        fields = reader.fields[1:]
        field_names = [field[0] for field in fields]
        buffer = []
        for sr in reader.shapeRecords():
            atr = dict(zip(field_names, sr.record))
            geom = sr.shape.__geo_interface__
            asa = geom.values()
            buffer.append(asa[-1])

        try:
            json_shrl_name = sys.argv[4]
        except:
            json_shrl_name = str(shrl_name + '.json')
Exemplo n.º 6
0
def saveshp(fn, points, proj4):
    point_store.save(fn, points, proj4)
    print "saved as ", fn