Python gdal.GDT_Byte方法代码示例

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def create_mask_from_model(image_path, model_path, model_clear=0, num_chunks=10, buffer_size=0):
    """Returns a multiplicative mask (0 for cloud, shadow or haze, 1 for clear) built from the model at model_path."""
    from pyeo.classification import classify_image  # Deferred import to deal with circular reference
    with TemporaryDirectory() as td:
        log = logging.getLogger(__name__)
        log.info("Building cloud mask for {} with model {}".format(image_path, model_path))
        temp_mask_path = os.path.join(td, "cat_mask.tif")
        classify_image(image_path, model_path, temp_mask_path, num_chunks=num_chunks)
        temp_mask = gdal.Open(temp_mask_path, gdal.GA_Update)
        temp_mask_array = temp_mask.GetVirtualMemArray()
        mask_path = get_mask_path(image_path)
        mask = create_matching_dataset(temp_mask, mask_path, datatype=gdal.GDT_Byte)
        mask_array = mask.GetVirtualMemArray(eAccess=gdal.GF_Write)
        mask_array[:, :] = np.where(temp_mask_array != model_clear, 0, 1)
        temp_mask_array = None
        mask_array = None
        temp_mask = None
        mask = None
        if buffer_size:
            buffer_mask_in_place(mask_path, buffer_size)
        log.info("Cloud mask for {} saved in {}".format(image_path, mask_path))
        return mask_path 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def create_mask_from_class_map(class_map_path, out_path, classes_of_interest, buffer_size=0, out_resolution=None):
    """Creates a mask from a classification mask: 1 for each pixel containing one of classes_of_interest, otherwise 0"""
    # TODO: pull this out of the above function
    class_image = gdal.Open(class_map_path)
    class_array = class_image.GetVirtualMemArray()
    mask_array = np.isin(class_array, classes_of_interest)
    out_mask = create_matching_dataset(class_image, out_path, datatype=gdal.GDT_Byte)
    out_array = out_mask.GetVirtualMemArray(eAccess=gdal.GA_Update)
    np.copyto(out_array, mask_array)
    class_array = None
    class_image = None
    out_array = None
    out_mask = None
    if out_resolution:
        resample_image_in_place(out_path, out_resolution)
    if buffer_size:
        buffer_mask_in_place(out_path, buffer_size)
    return out_path 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def create_mask_from_fmask(in_l1_dir, out_path):
    log = logging.getLogger(__name__)
    log.info("Creating fmask for {}".format(in_l1_dir))
    with TemporaryDirectory() as td:
        temp_fmask_path = os.path.join(td, "fmask.tif")
        apply_fmask(in_l1_dir, temp_fmask_path)
        fmask_image = gdal.Open(temp_fmask_path)
        fmask_array = fmask_image.GetVirtualMemArray()
        out_image = create_matching_dataset(fmask_image, out_path, datatype=gdal.GDT_Byte)
        out_array = out_image.GetVirtualMemArray(eAccess=gdal.GA_Update)
        log.info("fmask created, converting to binary cloud/shadow mask")
        out_array[:,:] = np.isin(fmask_array, (2, 3, 4), invert=True)
        out_array = None
        out_image = None
        fmask_array = None
        fmask_image = None
        resample_image_in_place(out_path, 10) 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def create_temp_tiff(self, name, content=np.ones([3, 3, 3]), geotransform=(10, 10, 0, 10, 0, -10)):
        """Creates a temporary geotiff in self.path
        """
        if len(content.shape) != 3:
            raise IndexError
        path = os.path.join(self.path, name)
        driver = gdal.GetDriverByName('GTiff')
        new_image = driver.Create(
            path,
            xsize=content.shape[1],
            ysize=content.shape[2],
            bands=content.shape[0],
            eType=gdal.GDT_Byte
        )
        new_image.SetGeoTransform(geotransform)
        for band in range(content.shape[0]):
            raster_band = new_image.GetRasterBand(band+1)
            raster_band.WriteArray(content[band, ...].T)
        new_image.SetProjection(self.srs.ExportToWkt())
        new_image.FlushCache()
        self.images.append(new_image)
        self.image_paths.append(path) 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def driver_create(self):
        """
        Use gdal.Driver.Create to create out_image.tiff.
        """
        file_name = os.path.join(self.data_dir, "out_image.tiff")
        image_format = "GTiff"
        driver = gdal.GetDriverByName(str(image_format))
        data_source = driver.Create(file_name, 50, 50, 1, gdal.GDT_Byte)
        raster = np.ones((50, 50), dtype=np.uint8)
        raster[10:40, 10:40] = 0
        raster = raster * 255
        data_source.GetRasterBand(1).WriteArray(raster)
        # Avoid PermissionError on Windows when trying to delete
        # file_name. From:
        # http://stackoverflow.com/questions/22068148/extremely-frustrating-behavior-with-windowserror-error-32-to-remove-temporary
        data_source.FlushCache()
        driver = None
        data_source = None
        os.remove(file_name) 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def make_geotiff(data, length, width, latn_p, lonw_p, dlat, dlon, outfile, compress_option):

    if data.dtype == np.float32:
        dtype = gdal.GDT_Float32
        nodata = np.nan  ## or 0?
    elif data.dtype == np.uint8:
        dtype = gdal.GDT_Byte
        nodata = None

    driver = gdal.GetDriverByName('GTiff')
    outRaster = driver.Create(outfile, width, length, 1, dtype, options=compress_option)
    outRaster.SetGeoTransform((lonw_p, dlon, 0, latn_p, 0, dlat))
    outband = outRaster.GetRasterBand(1)
    outband.WriteArray(data)
    if nodata is not None: outband.SetNoDataValue(nodata)
    outRaster.SetMetadataItem('AREA_OR_POINT', 'Point')
    outRasterSRS = osr.SpatialReference()
    outRasterSRS.ImportFromEPSG(4326)
    outRaster.SetProjection(outRasterSRS.ExportToWkt())
    outband.FlushCache()

    return


#%% Main 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def getDTfromGDAL(gdal_dt):
    """
    Returns datatype (numpy/scipy) from gdal_dt.

    Parameters
    ----------
    gdal_dt : datatype
        data.GetRasterBand(1).DataType

    Return
    ----------
    dt : datatype
    """
    if gdal_dt == gdal.GDT_Byte:
        dt = 'uint8'
    elif gdal_dt == gdal.GDT_Int16:
        dt = 'int16'
    elif gdal_dt == gdal.GDT_UInt16:
        dt = 'uint16'
    elif gdal_dt == gdal.GDT_Int32:
        dt = 'int32'
    elif gdal_dt == gdal.GDT_UInt32:
        dt = 'uint32'
    elif gdal_dt == gdal.GDT_Float32:
        dt = 'float32'
    elif gdal_dt == gdal.GDT_Float64:
        dt = 'float64'
    elif gdal_dt == gdal.GDT_CInt16 or gdal_dt == gdal.GDT_CInt32 or gdal_dt == gdal.GDT_CFloat32 or gdal_dt == gdal.GDT_CFloat64:
        dt = 'complex64'
    else:
        print('Data type unkown')
        # exit()
    return dt 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def getGDALGDT(dt):
    """
    Need arr.dtype.name in entry.
    Returns gdal_dt from dt (numpy/scipy).

    Parameters
    ----------
    dt : datatype

    Return
    ----------
    gdal_dt : gdal datatype
    """
    if dt == 'bool' or dt == 'uint8':
        gdal_dt = gdal.GDT_Byte
    elif dt == 'int8' or dt == 'int16':
        gdal_dt = gdal.GDT_Int16
    elif dt == 'uint16':
        gdal_dt = gdal.GDT_UInt16
    elif dt == 'int32':
        gdal_dt = gdal.GDT_Int32
    elif dt == 'uint32':
        gdal_dt = gdal.GDT_UInt32
    elif dt == 'int64' or dt == 'uint64' or dt == 'float16' or dt == 'float32':
        gdal_dt = gdal.GDT_Float32
    elif dt == 'float64':
        gdal_dt = gdal.GDT_Float64
    elif dt == 'complex64':
        gdal_dt = gdal.GDT_CFloat64
    else:
        print('Data type non-suported')
        # exit()

    return gdal_dt 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def create_uniquevalue_tiff(
        outname, im, d, GeoTransform, Projection, wholeValue=1, gdal_dt=False):
    '''!@brief Write an empty image on the hard drive.

    Input:
        outname: the name of the file to be written
        im: the image cube
        GeoTransform: the geotransform information
        Projection: the projection information
    Output:
        Nothing --
    '''
    nl = im.shape[0]
    nc = im.shape[1]

    driver = gdal.GetDriverByName('GTiff')
    # Get the data type
    if not gdal_dt:
        gdal_dt = gdal.GDT_Byte

    dst_ds = driver.Create(outname, nc, nl, d, gdal_dt)
    dst_ds.SetGeoTransform(GeoTransform)
    dst_ds.SetProjection(Projection)

    if d == 1:
        im[:] = wholeValue
        out = dst_ds.GetRasterBand(1)
        out.WriteArray(im)
        out.FlushCache()
    else:
        for i in range(d):
            im[:, :, i] = wholeValue
            out = dst_ds.GetRasterBand(i + 1)
            out.WriteArray(im[:, :, i])
            out.FlushCache()
    dst_ds = None

    return outname 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def combine_masks(mask_paths, out_path, combination_func = 'and', geometry_func ="intersect"):
    """ORs or ANDs several masks. Gets metadata from top mask. Assumes that masks are a
    Python true or false. Also assumes that all masks are the same projection for now."""
    log = logging.getLogger(__name__)
    log.info("Combining masks {}:\n   combination function: '{}'\n   geometry function:'{}'".format(
        mask_paths, combination_func, geometry_func))
    masks = [gdal.Open(mask_path) for mask_path in mask_paths]
    combined_polygon = align_bounds_to_whole_number(get_combined_polygon(masks, geometry_func))
    gt = masks[0].GetGeoTransform()
    x_res = gt[1]
    y_res = gt[5]*-1  # Y res is -ve in geotransform
    bands = 1
    projection = masks[0].GetProjection()
    out_mask = create_new_image_from_polygon(combined_polygon, out_path, x_res, y_res,
                                             bands, projection, datatype=gdal.GDT_Byte, nodata=0)

    # This bit here is similar to stack_raster, but different enough to not be worth spinning into a combination_func
    # I might reconsider this later, but I think it'll overcomplicate things.
    out_mask_array = out_mask.GetVirtualMemArray(eAccess=gdal.GF_Write)
    out_mask_array = out_mask_array.squeeze() # This here to account for unaccountable extra dimension Windows patch adds
    out_mask_array[:, :] = 1
    for mask_index, in_mask in enumerate(masks):
        in_mask_array = in_mask.GetVirtualMemArray()
        in_mask_array = in_mask_array.squeeze()  # See previous comment
        if geometry_func == "intersect":
            out_x_min, out_x_max, out_y_min, out_y_max = pixel_bounds_from_polygon(out_mask, combined_polygon)
            in_x_min, in_x_max, in_y_min, in_y_max = pixel_bounds_from_polygon(in_mask, combined_polygon)
        elif geometry_func == "union":
            out_x_min, out_x_max, out_y_min, out_y_max = pixel_bounds_from_polygon(out_mask, get_raster_bounds(in_mask))
            in_x_min, in_x_max, in_y_min, in_y_max = pixel_bounds_from_polygon(in_mask, get_raster_bounds(in_mask))
        else:
            raise Exception("Invalid geometry_func; can be 'intersect' or 'union'")
        out_mask_view = out_mask_array[out_y_min: out_y_max, out_x_min: out_x_max]
        in_mask_view = in_mask_array[in_y_min: in_y_max, in_x_min: in_x_max]
        if mask_index is 0:
            out_mask_view[:,:] = in_mask_view
        else:
            if combination_func is 'or':
                out_mask_view[:, :] = np.bitwise_or(out_mask_view, in_mask_view, dtype=np.uint8)
            elif combination_func is 'and':
                out_mask_view[:, :] = np.bitwise_and(out_mask_view, in_mask_view, dtype=np.uint8)
            elif combination_func is 'nor':
                out_mask_view[:, :] = np.bitwise_not(np.bitwise_or(out_mask_view, in_mask_view, dtype=np.uint8), dtype=np.uint8)
            else:
                raise Exception("Invalid combination_func; valid values are 'or', 'and', and 'nor'")
        in_mask_view = None
        out_mask_view = None
        in_mask_array = None
        in_mask = None
    out_mask_array = None
    out_mask = None
    return out_path 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def open_data(filename):
    '''
    The function open and load the image given its name.
    The type of the data is checked from the file and the scipy array is initialized accordingly.
    Input:
        filename: the name of the file
    Output:
        im: the data cube
        GeoTransform: the geotransform information
        Projection: the projection information
    '''
    data = gdal.Open(filename, gdal.GA_ReadOnly)
    if data is None:
        print('Impossible to open ' + filename)
        # exit()
    nc = data.RasterXSize
    nl = data.RasterYSize
    d = data.RasterCount

    # Get the type of the data
    gdal_dt = data.GetRasterBand(1).DataType
    if gdal_dt == gdal.GDT_Byte:
        dt = 'uint8'
    elif gdal_dt == gdal.GDT_Int16:
        dt = 'int16'
    elif gdal_dt == gdal.GDT_UInt16:
        dt = 'uint16'
    elif gdal_dt == gdal.GDT_Int32:
        dt = 'int32'
    elif gdal_dt == gdal.GDT_UInt32:
        dt = 'uint32'

    elif gdal_dt == gdal.GDT_Float32:
        dt = 'float32'
    elif gdal_dt == gdal.GDT_Float64:
        dt = 'float64'
    elif gdal_dt == gdal.GDT_CInt16 or gdal_dt == gdal.GDT_CInt32 or gdal_dt == gdal.GDT_CFloat32 or gdal_dt == gdal.GDT_CFloat64:
        dt = 'complex64'
    else:
        print('Data type unkown')
        # exit()

    # Initialize the array
    if d == 1:
        im = np.empty((nl, nc), dtype=dt)
    else:
        im = np.empty((nl, nc, d), dtype=dt)

    if d == 1:
        im[:, :] = data.GetRasterBand(1).ReadAsArray()
    else:
        for i in range(d):
            im[:, :, i] = data.GetRasterBand(i + 1).ReadAsArray()

    GeoTransform = data.GetGeoTransform()
    Projection = data.GetProjection()
    data = None
    return im, GeoTransform, Projection 

# 需要导入模块: import gdal [as 别名]
# 或者: from gdal import GDT_Byte [as 别名]
def export_geomap2geotiff(path, geo_model, geo_map=None, geotiff_filepath=None):
    """

    Args:
        path (str): Filepath for the exported geotiff, must end in .tif
        geo_map (np.ndarray): 2-D array containing the geological map
        cmap (matplotlib colormap): The colormap to be used for the export
        geotiff_filepath (str): Filepath of the template geotiff

    Returns:
        Saves the geological map as a geotiff to the given path.
    """
    import gdal

    plot = PlotData2D(geo_model)
    cmap = plot._cmap
    norm = plot._norm

    if geo_map is None:
        geo_map = geo_model.solutions.geological_map[0].reshape(geo_model._grid.topography.resolution)

    if geotiff_filepath is None:
        # call the other function
        print('stupid')

    # **********************************************************************
    geo_map_rgb = SM(norm=norm, cmap=cmap).to_rgba(geo_map.T) # r,g,b,alpha
    # **********************************************************************
    # gdal.UseExceptions()
    ds = gdal.Open(geotiff_filepath)
    band = ds.GetRasterBand(1)
    arr = band.ReadAsArray()
    [cols, rows] = arr.shape

    outFileName = path
    driver = gdal.GetDriverByName("GTiff")
    options = ['PROFILE=GeoTiff', 'PHOTOMETRIC=RGB', 'COMPRESS=JPEG']
    outdata = driver.Create(outFileName, rows, cols, 3, gdal.GDT_Byte, options=options)

    outdata.SetGeoTransform(ds.GetGeoTransform())  # sets same geotransform as input
    outdata.SetProjection(ds.GetProjection())  # sets same projection as input
    outdata.GetRasterBand(1).WriteArray(geo_map_rgb[:, ::-1, 0].T * 256)
    outdata.GetRasterBand(2).WriteArray(geo_map_rgb[:, ::-1, 1].T * 256)
    outdata.GetRasterBand(3).WriteArray(geo_map_rgb[:, ::-1, 2].T * 256)
    outdata.GetRasterBand(1).SetColorInterpretation(gdal.GCI_RedBand)
    outdata.GetRasterBand(2).SetColorInterpretation(gdal.GCI_GreenBand)
    outdata.GetRasterBand(3).SetColorInterpretation(gdal.GCI_BlueBand)
    # outdata.GetRasterBand(4).SetColorInterpretation(gdal.GCI_AlphaBand)  # alpha band

    # outdata.GetRasterBand(1).SetNoDataValue(999)##if you want these values transparent
    outdata.FlushCache()  # saves to disk
    outdata = None  # closes file (important)
    band = None
    ds = None

    print("Successfully exported geological map to  " +path)