#print('3',three)
#total pixel count
total = len(pix_val)
#Percentage of each value
a = (five * 100 / total)
b = (seven * 100 / total)
c = (four * 100 / total)
d = (three * 100 / total)
if (a + c == 100 or a + c == 99):
print("Good")
if ((a > c > d > b or a > d > c > b)):
sd_file = os.path.join(sd_dir2, os.path.basename(in_file))
raster.WriteRaster(reading, sd_file)
print(sd_file)
elif (c > a > d > b or c > d > a > b):
sd_file = os.path.join(sd_dir2, os.path.basename(in_file))
raster.WriteRaster(reading, sd_file)
print(sd_file)
elif (d > a > c > b or d > c > a > b):
sd_file = os.path.join(sd_dir2, os.path.basename(in_file))
raster.WriteRaster(reading, sd_file)
print(sd_file)
elif (c > b > a):
sd_file = os.path.join(sd_dir2, os.path.basename(in_file))
raster.WriteRaster(reading, sd_file)
print(sd_file)
elif (a > b > c):
in_files.sort()
sd_dir = "/home/pavithra/Desktop/Rasterimages/NEW_SD/SD_B12"
for in_file in in_files:
r_band = raster.ReadRaster(in_file)
data = r_band.data
out_sd = ndimage.generic_filter(data, np.var, size=3)**0.5
sd_file = os.path.join(sd_dir, os.path.basename(in_file))
r_band_sd = raster.Raster(out_sd,
extent=r_band.extent,
projection=r_band.projection)
raster.WriteRaster(r_band_sd, sd_file)
print(sd_file)
#Applying Guassian filter
in_dirtwo = "/home/pavithra/Desktop/Rasterimages/NEW_SD/SD_B12/*.tif"
in_filestwo = glob.glob(in_dirtwo)
in_filestwo.sort()
sd_dirtwo = "/home/pavithra/Desktop/Rasterimages/NEW_Sharpened_data/B12"
for in_file in in_filestwo:
r_bandtwo = raster.ReadRaster(in_file)
datatwo = r_bandtwo.data
blurred_f = ndimage.gaussian_filter(datatwo, 2)
im = raster.ReadRaster(
'/home/pavithra/Desktop/Rasterimages/NEW_Feature_data/B02/T14QQF_20181220T165719_B02_10m.tif'
)
sd_dir = "/home/pavithra/Desktop/Satyukt"
data = im.data
print(data[1][2])
print(data.shape)
#955 is the number of pixels in row and 1190 in the column
for i in range(0, 955):
for j in range(0, 1190):
if (data[i][j] <= 65):
data[i][j] = 255
else:
data[i][j] = 0
print(data)
sd_file = os.path.join(sd_dir, os.path.basename('20th Dec 2018_B2.tif'))
r_band_sd = raster.Raster(data, extent=im.extent, projection=im.projection)
raster.WriteRaster(r_band_sd, sd_file)
print(sd_file)
for ik_file in sd_files:
one = os.path.basename(in_file)
on = one.rsplit('_',2)
two = os.path.basename(ik_file)
tw = two.rsplit('_',2)
if(on[0] == tw[0]):
r_band = raster.ReadRaster(ik_file)
data = r_band.data
#data1 = r_band.astype(np.uint8)
for i in range(len(data)):
for j in range(len(data[0])):
if(data[i,j]>3000):
data[i,j] = np.nan
else:
data[i,j] = data[i,j]
sd_file = os.path.join(sd_datacc, os.path.basename(ik_file))
r_band_cc = raster.Raster(data, extent=r_band.extent, projection=r_band.projection)
raster.WriteRaster(r_band_cc, sd_file)
print(sd_file)
else:
print('file not matched')