def index():
if request.method == "POST":
print(request.files)
if ('file4' not in request.files) or ('file8' not in request.files):
flash('No files Selected.')
return redirect(request.url)
file4 = request.files['file4']
file8 = request.files['file8']
# if user does not select file, browser also
# submit an empty part without filename
if file4.filename == '' or file8.filename == '':
flash('Please Select files for both band')
return redirect(request.url)
if file4 and file8 and allowed_file(file4.filename) and allowed_file(
file8.filename):
filename4 = secure_filename(file4.filename)
filename8 = secure_filename(file8.filename)
dest = Path('static/NDVI.tiff')
try:
ndvi(filename4, filename8, str(dest))
except Exception as ex:
flash("Internal Error")
print(ex)
redirect(request.url)
else:
return send_from_directory('static',
'NDVI.tiff',
as_attachment=True)
else:
flash("Only tiff and jp2 files are allowed.")
redirect(request.url)
return render_template("base.html")
from gdal import Open
from ndvi import ndvi
# Abrindo banda NIR
nir_tiff = Open(r'NIR_IMAGE.tif')
#nir_tiff = Open(r'nir.tif')
nir_band = nir_tiff.GetRasterBand(1)
# Abrindo banda RED.
red_tiff = Open(r'RED_IMAGE.tif')
#red_tiff = Open(r'red.tif')
red_band = red_tiff.GetRasterBand(1)
# Get the rows and cols from one of the images (both should always be the same)
rows, cols, geotransform = nir_tiff.RasterYSize, nir_tiff.RasterXSize, nir_tiff.GetGeoTransform()
print(geotransform)
# Arquivo de saida 16-bit (0-255)
out_tiff_int16 = r'NDVI_16.tif'
# Arquivo de saida 32-bit floating point (-1 to 1)
out_tiff_float32 = r'NDVI_32.tif'
# Gerando imagem NDVI 16-bit integer
ndvi(nir_band, red_band, rows, cols, geotransform, out_tiff_int16, gdal.GDT_UInt16)
# Gerando imagem NDVI 32-bit floating point
ndvi(nir_band, red_band, rows, cols, geotransform, out_tiff_float32, gdal.GDT_Float32)
print('done')
import gdal
from gdal import Open
from ndvi import ndvi
# Open NIR image and get its only band.
nir_tiff = Open(r'NIR_IMAGE.tif')
nir_band = nir_tiff.GetRasterBand(1)
# Open red image and get its only band.
red_tiff = Open(r'RED_IMAGE.tif')
red_band = red_tiff.GetRasterBand(1)
# Get the rows and cols from one of the images (both should always be the same)
rows, cols, geotransform = nir_tiff.RasterYSize, nir_tiff.RasterXSize, nir_tiff.GetGeoTransform()
print(geotransform)
# Set an output for a 16-bit unsigned integer (0-255)
out_tiff_int16 = r'NDVI_INT16.tif'
# Set the output for a 32-bit floating point (-1 to 1)
out_tiff_float32 = r'NDVI_FLOAT32.tif'
# Run the function for unsigned 16-bit integer
ndvi(nir_band, red_band, rows, cols, geotransform, out_tiff_int16, gdal.GDT_UInt16)
# Run the function for 32-bit floating point
ndvi(nir_band, red_band, rows, cols, geotransform, out_tiff_float32, gdal.GDT_Float32)
print('done')
print(red_band)
blue_tiff = Open(r'BLUE_IMAGE.tif')
blue_band = blue_tiff.GetRasterBand(1)
green_tiff = Open(r'GREEN_IMAGE.tif')
green_band = green_tiff.GetRasterBand(1)
swir_tiff = Open(r'SWIR_IMAGE.tif')
swir_band = swir_tiff.GetRasterBand(1)
mir_tiff = Open(r'MIR_IMAGE.tif')
mir_band = mir_tiff.GetRasterBand(1)
(rows, cols) = (nir_tiff.RasterYSize, nir_tiff.RasterXSize)
ndvi_value = ndvi(nir_band, red_band, rows, cols)
print(ndvi_value)
ndv = nan_to_num(result)
print(ndv, "sd")
result = ndvi_value
row = len(result) - 1
col = len(result[0]) - 729
i = 0
sum = 0
for i in range(row):
j = 0
for j in range(col):
prev = sum
sum += result[i, j]
denom = row * col
ndvi_value = sum / denom
import gdal
from gdal import Open
from ndvi import ndvi
# Open NIR image and get its only band.
nir_tiff = Open(r'NIR_IMAGE.tif')
nir_band = nir_tiff.GetRasterBand(1)
# Open red image and get its only band.
red_tiff = Open(r'RED_IMAGE.tif')
red_band = red_tiff.GetRasterBand(1)
# Get the rows and cols from one of the images (both should always be the same)
rows, cols, geotransform = nir_tiff.RasterYSize, nir_tiff.RasterXSize, nir_tiff.GetGeoTransform(
)
print(geotransform)
# Set the output for a 32-bit floating point (-1 to 1)
out_tiff_float32 = r'NDVI_FLOAT32.tif'
# Run the function for 32-bit floating point
ndvi(nir_band, red_band, rows, cols, geotransform, out_tiff_float32)
print('done')
def do_ndvi():
"do_ndvi(): function to read MODIS refl HDF file and calculate NDVI"
ifile = 'MOD09GA.A2004154.h19v10.005.2008152141836.hdf'
title = ifile
ofile = 0
red = 'sur_refl_b01_1'
nir = 'sur_refl_b02_1'
xmin = 0
xmax = 500
ymin = 0
ymax = 500
xlabel = 'Col'
ylabel = 'Row'
# min and max values for colourbar on plot
ndvimin = 0.1
ndvimax = 0.8
# default plot value
plot = 1
if options.ifile:
ifile = options.ifile
if options.ofile:
ofile = options.ofile
if options.sdsName:
sdsName = options.sdsName
# read HDF file
md = hdf_utils.r(ifile)
if options.v:
# o/p file datasets
sys.stderr.write('ifile: %s\n' % (ifile))
md.datasets()
sds_red = md.select(red)
sds_nir = md.select(nir)
# do we have extract i.e. xmin, xmax, ymin, ymax?
if options.xmin:
xmin = options.xmin
if options.ymin:
ymin = options.ymin
if options.xmax:
xmax = options.xmax
if options.ymax:
ymax = options.ymax
# scale ndvi values?
if options.ndvimin:
ndvimin = options.ndvimin
if options.ndvimax:
ndvimax = options.ndvimax
if options.xlabel:
xlabel = options.xlabel
if options.ylabel:
ylabel = options.ylabel
if options.title:
title = options.title
# check dims
if (sds_red.dimensions('XDim').values()[0][0] !=
sds_nir.dimensions('XDim').values()[0][0]) or (
sds_red.dimensions('YDim').values()[0][0] !=
sds_nir.dimensions('YDim').values()[0][0]):
sys.stderr.write(
'%s: dimension error - x, y dims of SDS %s and %s do not match\n' %
(ifile, red, nir))
# get extract if required, and cast to float32
if (options.xmin or options.ymin or options.xmax or options.ymax):
sds_red = np.float32(sds_red[xmin:xmax, ymin:ymax])
sds_nir = np.float32(sds_nir[xmin:xmax, ymin:ymax])
n = np.zeros([xmax - xmin, ymax - ymin])
else:
xdim = sds_red.dimensions('XDim').values()[0][0]
ydim = sds_red.dimensions('YDim').values()[0][0]
sds_red = np.float32(sds_red[0:xdim, 0:ydim])
sds_nir = np.float32(sds_nir[0:xdim, 0:ydim])
n = np.zeros([xdim, ydim])
# calculate ndvi from bands 1, 2
n = ndvi.ndvi(sds_red, sds_nir)
# clip if required
np.clip(n, -1., 1., out=n)
if options.v:
# o/p file datasets
sys.stderr.write('ifile: %s\n' % (ifile))
md.datasets()
if options.plot:
# o/p file datasets
plot = 1
if plot:
plot_me.plot(n, title, xlabel, ylabel, 'NDVI', ofile, ndvimin, ndvimax)
