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)
