def main(nom):
# lecture de l'interpretation
if nom == "":
tkinter.Tk().withdraw()
nom = filedialog.askopenfilename(
title="Fichier contenant l'interpretation ?"
) # ,filetypes=(("fichiers shape","*.shp")))
interp, larg, haut = lecture_inter(nom)
# lecture de l'image tif georeferencee
nom_se = nom[:nom.rfind(".")]
nom_image = nom_se + ".tif"
# creation de l'image interpretee georeferencee
info_geo = gr.MultiBandRaster(nom_image, load_data=False)
im_gen = gr.SingleBandRaster.from_array(interp, info_geo.trans,
info_geo.proj.srs, gdal.GDT_Int16)
im_gen.save_geotiff(nom_se + "_int.tif", dtype=gdal.GDT_Int16)
def load(filename, grid):
""" Load a MAR NetCDF file with the specified grid type using GeoRaster.
DEPRECATED
Parameters:
filename : string, the path to the file with the relevant sub-dataset
referencing, e.g.
'NETCDF:"MARv3.5.2-10km-monthly-ERA-Interim-1979.nc":AL'
grid : string, corresponding to entry in grids dictionary.
Returns:
MultiBandRaster instance, over full domain, all bands loaded
"""
if gr_avail:
spatial_ref = osr.SpatialReference()
spatial_ref.ImportFromProj4(grids[grid]['spatial_ref'])
rast = georaster.MultiBandRaster(
filename,
spatial_ref=spatial_ref,
geo_transform=grids[grid]['geo_transform'])
# Flip the raster bands to restore correct orientation
for i in rast.bands:
rast.r[:, :, i - 1] = np.flipud(rast.r[:, :, i - 1])
return rast
else:
print('GeoRaster dependency not available.')
raise ImportError
final = np.asarray((np.reshape(pred_acc, (Y, X))), np.float32)
#
# write file to output directory
# /output/filename.tif
file_name = PATH_OUTPUT + 'pred_' + list_Filenames[i]
border = (16, 16, 15, 15)
image_temp = Image.fromarray(final)
image_temp1 = np.asarray(
ImageOps.expand(image_temp, border)
) # add border to resize to original value,convert to array, again
# print('final.shape', image_temp1.size)
# image_temp1.save(file_name)
# Insert GEOTIFF information back into image before saving
info_geo = gr.MultiBandRaster(imagePath[i], load_data=False)
im_gen = gr.SingleBandRaster.from_array(image_temp1, info_geo.trans,
info_geo.proj.srs, gdal.GDT_Int16)
im_gen.save_geotiff(PATH_OUTPUT + 'geo_pred_' + list_Filenames[i])
print('processing', list_Filenames[i])
count = 1
#pred_acc.clear()
time_elapsed = (time.perf_counter() - time_start)
HMS_time = time.strftime("%H:%M:%S", time.gmtime(time_elapsed))
memMb = resource.getrusage(
resource.RUSAGE_SELF).ru_maxrss / 1024.0 / 1024.0
print("[INFO] TIME USED: ", HMS_time)
print("[INFO] MEMORY USAGE: {:.1f} MByte".format(memMb))
# print('pred',predictions)
# TEST SLIDING WINDOW WITH OVERLAY.....
# clone = image.copy()
parser.add_argument('-vmax', dest='vmax', type=str, default='default', help='float, the maximum value for colorscale, or can be expressed as a percentile e.g. 95% (default is calculated max value).')
parser.add_argument('-band', dest='band', type=int, default=0, help='int, which band to display (start at 0) for multiband images (Default is 0).')
parser.add_argument('-nocb', dest='nocb', help='If set, will not display a colorbar (Default is to display the colorbar).',action='store_true')
parser.add_argument('-clabel', dest='clabel', type=str, default='', help='str, the label for the colorscale (Default is empty).')
parser.add_argument('-title', dest='title', type=str, default='', help='str, figure title (Default is empty).')
parser.add_argument('-figsize', dest='figsize', type=str, default='default', help='str, figure size, must be a tuple of size 2, either written with quotes, or two numbers seperated by coma, no space (Default is from rcParams).')
parser.add_argument('-max_size', dest='max_size', type=int, default=2000, help='int, image size is limited to max_size**2 for faster reading/displaying (Default is 2000).')
parser.add_argument('-save', dest='save', type=str, default='', help='str, filename to the output filename to save to disk (Default is displayed on screen).')
parser.add_argument('-dpi', dest='dpi', type=str, default='default', help='int, dpi value to use when saving figure (Default is from rcParams).')
parser.add_argument('-nodata', dest='nodata', type=str, default='default', help='float, no data value (Default is read from file metadata).')
parser.add_argument('-noresampl', dest='noresampl', default=False, action='store_true', help='True or False, if False then allow dynamic image downscaling, if True, prevent it.')
args = parser.parse_args()
## Load image metadata ##
img = raster.MultiBandRaster(args.filename,load_data=False)
xmin, xmax, ymin, ymax = img.extent
if args.nodata=='default':
nodata = img.ds.GetRasterBand(1).GetNoDataValue()
else:
try:
nodata = float(args.nodata)
except ValueError:
print("ERROR: nodata must be a float, currently set to %s" %args.nodata)
sys.exit(1)
## Resample if image is too large ##
if (img.nx*img.ny>args.max_size**2) & (not args.noresampl):
step = max(int(img.nx/args.max_size),int(img.ny/args.max_size))