def wrapper(inVector): outDir = "/home/trashtos/CleaningTiles/SegmentationFinal/tile_row10col20" coverVector = "/media/trashtos/Meerkat/0000/0000/0000_0000.shp" outVector = os.path.join(outDir, os.path.basename(inVector)) if os.path.exists(outVector): pass else: try: vectorClip(inVector, coverVector, outVector) except: print ("error in file", inVector) return (outVector)
#### inImage= "/home/trashtos/CleaningTiles/SegmentationFinal/tile_row29col8_subarea_segIdeal.tif" refImage = "/media/trashtos/Meerkat/cleanTiles/Rows29/Cols8/tile_row29col8_stack_cubic_HCIR.tif" outImage = "/home/trashtos/CleaningTiles/SegmentationFinal/tile_row29col8_subarea_segIdeal_R.tif" clipReproject(inImage, refImage, outImage) import subprocess cmd = "gdal_polygonize.py " + outImage + """ -f "ESRI Shapefile" """ + os.path.splitext(outImage)[0] + ".shp" subprocess.call(cmd, shell = True) inVector = os.path.splitext(outImage)[0] + ".shp" coverVector = "/media/trashtos/Meerkat/0000/0000/0000_0000.shp" outVector = "/home/trashtos/CleaningTiles/SegmentationFinal/tile_row29col8_subarea_segIdeal_OK.shp" vectorClip(inVector, coverVector, outVector) # values of this one values = segQuality(outVector, refImage) df = pd.DataFrame(values) df.to_csv(outVector[:-4] + "_pd.txt", header = False, index = False) ### import numpy as np #df = pd.read_csv("/home/trashtos/CleaningTiles/summary_tile_row29col8_nonzero_SORTED.csv") df = pd.read_csv("/home/trashtos/CleaningTiles/summary_tile_row29col8_nonzero_2out_sorted.csv") df['NnumObj'] = np.round_(df['NnumObj'], decimals=3) df['NinterVar'] = np.round_(df['NinterVar'], decimals=3)