Python gdal.GDT_Byte方法代码示例

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def writeRaster(arr, out_path, template):
    no_data = 0
    # First of all, gather some information from the template file
    data = gdal.Open(template)
    [cols, rows] = arr.shape
    trans = data.GetGeoTransform()
    proj = data.GetProjection()
    # nodatav = 0 #data.GetNoDataValue()
    # Create the file, using the information from the template file
    outdriver = gdal.GetDriverByName("GTiff")
    # http://www.gdal.org/gdal_8h.html
    # GDT_Byte = 1, GDT_UInt16 = 2, GDT_UInt32 = 4, GDT_Int32 = 5, GDT_Float32 = 6,
    outdata   = outdriver.Create(str(out_path), rows, cols, 1, gdal.GDT_UInt32)
    # Write the array to the file, which is the original array in this example
    outdata.GetRasterBand(1).WriteArray(arr)
    # Set a no data value if required
    outdata.GetRasterBand(1).SetNoDataValue(no_data)
    # Georeference the image
    outdata.SetGeoTransform(trans)
    # Write projection information
    outdata.SetProjection(proj)
    return arr


# raster to vector 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def CreateMultiBandGeoTiff(OutPath, Array):
    '''
    Author: Jake Shermeyer
    Array has shape:
        Channels, Y, X?
    '''
    driver = gdal.GetDriverByName('GTiff')
    DataSet = driver.Create(OutPath, Array.shape[2], Array.shape[1],
                            Array.shape[0], gdal.GDT_Byte,
                            ['COMPRESS=LZW'])
    for i, image in enumerate(Array, 1):
        DataSet.GetRasterBand(i).WriteArray(image)
    del DataSet

    return OutPath


############################################################################### 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def createImageDS(filename, x_min, y_min, x_max, y_max, pixel_size,  srs=None):
    # Create the destination data source
    x_res = int((x_max - x_min) / pixel_size) # resolution
    y_res = int((y_max - y_min) / pixel_size) # resolution
    ds = gdal.GetDriverByName('GTiff').Create(filename, x_res,
            y_res, 1, gdal.GDT_Byte)
    ds.SetGeoTransform((
            x_min, pixel_size, 0,
            y_max, 0, -pixel_size,
        ))
    if srs:
        # Make the target raster have the same projection as the source
        ds.SetProjection(srs.ExportToWkt())
    else:
        # Source has no projection (needs GDAL >= 1.7.0 to work)
        ds.SetProjection('LOCAL_CS["arbitrary"]')

    # Set nodata
    band = ds.GetRasterBand(1)
    band.SetNoDataValue(0)

    return ds 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def getNumpyType(self, pixelType = gdal.GDT_Byte):
        '''
        Translates the gdal raster type to numpy type
        pixelType: gdal raster type
        '''
        if pixelType == gdal.GDT_Byte:
            return numpy.uint8
        elif pixelType == gdal.GDT_UInt16:
            return numpy.uint16
        elif pixelType == gdal.GDT_Int16:
            return numpy.int16
        elif pixelType == gdal.GDT_UInt32:
            return numpy.uint32
        elif pixelType == gdal.GDT_Int32:
            return numpy.int32
        elif pixelType == gdal.GDT_Float32:
            return numpy.float32
        elif pixelType == gdal.GDT_Float64:
            return numpy.float64 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def getNumpyType(self, pixelType = gdal.GDT_Byte):
        """
        Translates the gdal raster type to numpy type
        pixelType: gdal raster type
        """
        if pixelType == gdal.GDT_Byte:
            return numpy.uint8
        elif pixelType == gdal.GDT_UInt16:
            return numpy.uint16
        elif pixelType == gdal.GDT_Int16:
            return numpy.int16
        elif pixelType == gdal.GDT_UInt32:
            return numpy.uint32
        elif pixelType == gdal.GDT_Int32:
            return numpy.int32
        elif pixelType == gdal.GDT_Float32:
            return numpy.float32
        elif pixelType == gdal.GDT_Float64:
            return numpy.float64 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def write_data(self, data, fileName, colorTable):
		fileName 	= os.path.join(self.outpath, fileName)
		driver 		= gdal.GetDriverByName( "GTiff" )
		dst_ds 		= driver.Create( fileName, self.RasterXSize, self.RasterYSize, 1, gdal.GDT_Byte, [ 'COMPRESS=DEFLATE' ] )
		band 		= dst_ds.GetRasterBand(1)

		if self.geotransform:
			dst_ds.SetGeoTransform( self.geotransform )
			
		if self.projection:
			dst_ds.SetProjection( self.projection )

		if colorTable:
			print "Add colortable"
			band.SetRasterColorTable(self.ct)

		band.WriteArray(data, 0, 0)
			
		if verbose:
			print "Written", fileName

		ds 		= None 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def _str_of_gdt(gdt):
    return {
        gdal.GDT_Byte: 'GDT_Byte',
        gdal.GDT_Int16: 'GDT_Int16',
        gdal.GDT_Int32: 'GDT_Int32',
        gdal.GDT_UInt16: 'GDT_UInt16',
        gdal.GDT_UInt32: 'GDT_UInt32',
        gdal.GDT_Float32: 'GDT_Float32',
        gdal.GDT_Float64: 'GDT_Float64',
        gdal.GDT_CFloat32: 'GDT_CFloat32',
        gdal.GDT_CFloat64: 'GDT_CFloat64',
        gdal.GDT_CInt16: 'GDT_CInt16',
        gdal.GDT_CInt32: 'GDT_CInt32',
    }[gdt] 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def polygonize(img,shp_path):
    # mapping between gdal type and ogr field type
    type_mapping = {gdal.GDT_Byte: ogr.OFTInteger,
                    gdal.GDT_UInt16: ogr.OFTInteger,
                    gdal.GDT_Int16: ogr.OFTInteger,
                    gdal.GDT_UInt32: ogr.OFTInteger,
                    gdal.GDT_Int32: ogr.OFTInteger,
                    gdal.GDT_Float32: ogr.OFTReal,
                    gdal.GDT_Float64: ogr.OFTReal,
                    gdal.GDT_CInt16: ogr.OFTInteger,
                    gdal.GDT_CInt32: ogr.OFTInteger,
                    gdal.GDT_CFloat32: ogr.OFTReal,
                    gdal.GDT_CFloat64: ogr.OFTReal}

    ds = gdal.Open(img)
    prj = ds.GetProjection()
    srcband = ds.GetRasterBand(1)
    dst_layername = "Shape"
    drv = ogr.GetDriverByName("ESRI Shapefile")
    dst_ds = drv.CreateDataSource(shp_path)
    srs = osr.SpatialReference(wkt=prj)

    dst_layer = dst_ds.CreateLayer(dst_layername, srs=srs)
    raster_field = ogr.FieldDefn('id', type_mapping[srcband.DataType])
    dst_layer.CreateField(raster_field)
    gdal.Polygonize(srcband, srcband, dst_layer, 0, [], callback=None)
    del img, ds, srcband, dst_ds, dst_layer


# convert images in a selected folder to shapefiles 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def polygonize(img,shp_path):
    # mapping between gdal type and ogr field type
    type_mapping = {gdal.GDT_Byte: ogr.OFTInteger,
                    gdal.GDT_UInt16: ogr.OFTInteger,
                    gdal.GDT_Int16: ogr.OFTInteger,
                    gdal.GDT_UInt32: ogr.OFTInteger,
                    gdal.GDT_Int32: ogr.OFTInteger,
                    gdal.GDT_Float32: ogr.OFTReal,
                    gdal.GDT_Float64: ogr.OFTReal,
                    gdal.GDT_CInt16: ogr.OFTInteger,
                    gdal.GDT_CInt32: ogr.OFTInteger,
                    gdal.GDT_CFloat32: ogr.OFTReal,
                    gdal.GDT_CFloat64: ogr.OFTReal}

    ds = gdal.Open(img)
    prj = ds.GetProjection()
    srcband = ds.GetRasterBand(1)

    dst_layername = "Shape"
    drv = ogr.GetDriverByName("ESRI Shapefile")
    dst_ds = drv.CreateDataSource(shp_path)
    srs = osr.SpatialReference(wkt=prj)

    dst_layer = dst_ds.CreateLayer(dst_layername, srs=srs)
    # raster_field = ogr.FieldDefn('id', type_mapping[srcband.DataType])
    raster_field = ogr.FieldDefn('id', type_mapping[gdal.GDT_Int32])
    dst_layer.CreateField(raster_field)
    gdal.Polygonize(srcband, srcband, dst_layer, 0, [], callback=None)
    del img, ds, srcband, dst_ds, dst_layer


# extract sinks from dem 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def write_geotiff(fname, data, geo_transform, projection, data_type=gdal.GDT_Byte):

    """
    Create a GeoTIFF file with the given data.
    :param fname: Path to a directory with shapefiles
    :param data: Number of rows of the result
    :param geo_transform: Returned value of 
	gdal.Dataset.GetGeoTransform (coefficients for transforming between 
	pixel/line (P,L) raster space, and projection coordinates (Xp,Yp) space.
    :param projection: Projection definition string (Returned by 
	gdal.Dataset.GetProjectionRef)
    """

    driver = gdal.GetDriverByName('GTiff')
    rows, cols = data.shape
    dataset = driver.Create(fname, cols, rows, 1, data_type)
    dataset.SetGeoTransform(geo_transform)
    dataset.SetProjection(projection)
    band = dataset.GetRasterBand(1)
    band.WriteArray(data)

    metadata = {
        'TIFFTAG_COPYRIGHT': 'CC BY 4.0',
        'TIFFTAG_DOCUMENTNAME': 'classification',
        'TIFFTAG_IMAGEDESCRIPTION': 'Supervised classification.',
        'TIFFTAG_SOFTWARE': 'Python, GDAL, scikit-learn'
    }
    dataset.SetMetadata(metadata)

    dataset = None  # Close the file
    return 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def create_geotiff(np_arr, gps_bounds, out_file_path, base_dir):
    try:
        nrows,ncols = np.shape(np_arr)
        # gps_bounds: (lat_min, lat_max, lng_min, lng_max)
        xres = (gps_bounds[3] - gps_bounds[2])/float(ncols)
        yres = (gps_bounds[1] - gps_bounds[0])/float(nrows)
        geotransform = (gps_bounds[2],xres,0,gps_bounds[1],0,-yres) #(top left x, w-e pixel resolution, rotation (0 if North is up), top left y, rotation (0 if North is up), n-s pixel resolution)

        output_path = out_file_path

        output_raster = gdal.GetDriverByName('GTiff').Create(output_path, ncols, nrows, 3, gdal.GDT_Byte)

        output_raster.SetGeoTransform(geotransform) # specify coordinates
        srs = osr.SpatialReference() # establish coordinate encoding
        srs.ImportFromEPSG(4326) # specifically, google mercator
        output_raster.SetProjection( srs.ExportToWkt() ) # export coordinate system to file

        # TODO: Something wonky w/ uint8s --> ending up w/ lots of gaps in data (white pixels)
        output_raster.GetRasterBand(1).WriteArray(np_arr.astype('uint8')) # write red channel to raster file
        output_raster.GetRasterBand(1).FlushCache()
        output_raster.GetRasterBand(1).SetNoDataValue(-99)
        
        output_raster.GetRasterBand(2).WriteArray(np_arr.astype('uint8')) # write green channel to raster file
        output_raster.GetRasterBand(2).FlushCache()
        output_raster.GetRasterBand(2).SetNoDataValue(-99)

        output_raster.GetRasterBand(3).WriteArray(np_arr.astype('uint8')) # write blue channel to raster file
        output_raster.GetRasterBand(3).FlushCache()
        output_raster.GetRasterBand(3).SetNoDataValue(-99)


        # for test: once we've saved the image, make sure to append this path to our list of TIFs
        tif_file = os.path.join(base_dir, tif_list_file)
        f = open(tif_file,'a+')
        f.write(output_path + '\n')
    except Exception as ex:
        fail('Error creating GeoTIFF: ' + str(ex)) 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def readBlock(self, band, sizeX, sizeY = 1, offsetY = 0, pixelType = gdal.GDT_Byte):
        '''
        Reads image block
        band: band used
        sizeX: x block size
        sizeY: y block size
        offsetY: Y offset
        pixelType: pixel type
        '''
        numpytype = self.getNumpyType(pixelType)

        bandscanline =band.ReadRaster( 0, offsetY, sizeX, sizeY, sizeX, sizeY, pixelType )
        pixelArray=numpy.fromstring(bandscanline, dtype=numpytype)
        
        return pixelArray 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def writeBlock(self, band, block, sizeX, sizeY = 1, offsetY = 0, pixelType = gdal.GDT_Byte):
        '''
        Writes image block
        band: band used
        sizeX: x block size
        sizeY: y block size
        offsetY: Y offset
        pixelType: pixel type
        '''
        numpytype = self.getNumpyType(pixelType)

        band.WriteRaster(0, offsetY, sizeX, sizeY, block.astype(numpytype).tostring()) 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def readBlock(self, band, sizeX, sizeY = 1, offsetY = 0, pixelType = gdal.GDT_Byte):
        """
        Reads image block
        band: band used
        sizeX: x block size
        sizeY: y block size
        offsetY: Y offset
        pixelType: pixel type
        """
        numpytype = self.getNumpyType(pixelType)

        bandscanline =band.ReadRaster( 0, offsetY, sizeX, sizeY, sizeX, sizeY, pixelType )
        pixelArray=numpy.fromstring(bandscanline, dtype=numpytype)
        
        return pixelArray 

# 需要导入模块: from osgeo import gdal [as 别名]
# 或者: from osgeo.gdal import GDT_Byte [as 别名]
def CreateTopojsonFile(self, fileName, src_ds, projection, geotransform, ct, data, pres, xorg, ymax, water ):
	
		driver 				= gdal.GetDriverByName( "GTiff" )
		dst_ds_dataset		= driver.Create( fileName, src_ds.RasterXSize, src_ds.RasterYSize, 1, gdal.GDT_Byte, [ 'COMPRESS=DEFLATE' ] )
		
		dst_ds_dataset.SetGeoTransform( geotransform )
		dst_ds_dataset.SetProjection( projection )

		o_band				= dst_ds_dataset.GetRasterBand(1)
	
		o_band.SetRasterColorTable(ct)
		o_band.WriteArray(data, 0, 0)

		dst_ds_dataset = None
		print "Created", fileName

		cmd = "gdal_translate -q -of PNM -expand gray " + fileName + " "+fileName+".bmp"
		self.execute(cmd)

		# -i  		invert before processing
		# -t 2  	suppress speckles of up to this many pixels. 
		# -a 1.5  	set the corner threshold parameter
		# -z black  specify how to resolve ambiguities in path decomposition. Must be one of black, white, right, left, minority, majority, or random. Default is minority
		# -x 		scaling factor
		# -L		left margin
		# -B		bottom margin

		cmd = str.format("potrace -i -z black -a 1.5 -t 3 -b geojson -o {0} {1} -x {2} -L {3} -B {4} ", fileName+".geojson", fileName+".bmp", pres, xorg, ymax ); 
		self.execute(cmd)
	
		cmd = str.format("topojson -o {0} --simplify-proportion 0.75 -p water={1} -- water={2}", fileName+".topojson", water, fileName+".geojson" ); 
		self.execute(cmd)
	
		# convert it back to json
		cmd = "topojson-geojson --precision 4 -o %s %s" % ( self.geojsonDir, fileName+".topojson" )
		self.execute(cmd)
	
		# rename file
		output_file = "water_level_%d.geojson" % water
		cmd = "mv %s %s" % (os.path.join(self.geojsonDir,"water.json"), os.path.join(self.geojsonDir, output_file))
		self.execute(cmd)