prl900

from osgeo import gdal
from osgeo import ogr
from osgeo import gdalconst

#This raster is the model for our output (CRS, extent)
ndsm = 'geotif_output_extent_proj.tif'
#This shapefile contains the features we want to burn
shp = 'shapefile_features_fields.shp'

data = gdal.Open(ndsm, gdalconst.GA_ReadOnly)

prl900

from pylab import *
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.cbook import get_sample_data
from matplotlib._png import read_png
import imageio
from PIL import Image

img1 = imageio.imread("image1.jpg")
img1 = img1/255

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import logging, os

logging.disable(logging.WARNING)
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"

import tensorflow as tf

from tensorflow.keras import models
from tensorflow.keras import layers
from tensorflow.keras.layers import BatchNormalization, Conv2D, UpSampling2D, MaxPooling2D, Dropout