diff --git "a/D\303\251FI/DepositMethods/Camenen2013.py" "b/D\303\251FI/DepositMethods/Camenen2013.py"
index de09d076e035bfc993f8f19bed0020a381a0eaee..36daf0515ca95d91ed11a227876b21e3b01971f2 100644
--- "a/D\303\251FI/DepositMethods/Camenen2013.py"
+++ "b/D\303\251FI/DepositMethods/Camenen2013.py"
@@ -8,7 +8,7 @@
__author__ = "Thomas DREVET"
__copyright__ = "Copyright 2019, Irstea"
__credits__= "Benoit CAMENEN"
-__version__ = "1.0"
+__version__ = "2.0"
__maintainer__ = "Thomas DREVET"
__email__ = "thomas.drevet@irstea.fr"
__status__ = "Production"
@@ -19,7 +19,7 @@ __status__ = "Production"
import math
import numpy as np
-def Segmentation(OrthoImageGS, ScaleWrd2Pxl, MaskSize, Step, SedimentMask):
+def Segmentation(OrthoImageGS, ScaleWrd2Pxl, MaskSize, Step, SedimentMask, HistThresholds):
"""
Input:
+ OrthoImageGS: Orthorectified image (in gray scale) - array
@@ -27,15 +27,16 @@ def Segmentation(OrthoImageGS, ScaleWrd2Pxl, MaskSize, Step, SedimentMask):
+ MaskSize: Size of the mask used in the method - int
+ Step: Size of the step used in the method - int
+ SedimentMask: Mask representing the sediment bed - array
+ + HistThresholds: vector that contains ph1, ph2, ph3 and mh1 - 4x1 vector
Output:
+ DepositMap: Map of the sediment bed - array
"""
# Set the threshold values
- ThreshGravel_Deposits = 155
- ThreshChannels_Deposits = 130
- ThreshChannels_Trees = 50
- LimitGravel_Deposit = 0.03
+ ThreshGravel_Deposits = HistThresholds[0]
+ ThreshChannels_Deposits = HistThresholds[1]
+ ThreshChannels_Trees = HistThresholds[2]
+ LimitGravel_Deposit = HistThresholds[3]
# Get the width and the height of the input orthorectified image
width, height = OrthoImageGS.shape[:2]
@@ -48,14 +49,14 @@ def Segmentation(OrthoImageGS, ScaleWrd2Pxl, MaskSize, Step, SedimentMask):
DepositMap = np.zeros((width, height))
# For all the steps in the deposit map...
- for i in range (NbStepX):
- for j in range (NbStepY):
+ for i in range (int(NbStepX)):
+ for j in range (int(NbStepY)):
# Calculate position of the studied step
Xpos = int(MaskSize/2 + (i)*Step)
Ypos = int(MaskSize/2 + (j)*Step)
# Extract the studied part of the orthorectified image and reshape it
- WindowedImage = OrthoImageGS[Xpos-round(MaskSize/2) : Xpos+round(MaskSize/2)+1, Ypos-round(MaskSize/2) : Ypos+round(MaskSize/2)+1]
+ WindowedImage = OrthoImageGS[Xpos-int(round(MaskSize/2)) : Xpos+int(round(MaskSize/2))+1, Ypos-int(round(MaskSize/2)) : Ypos+int(round(MaskSize/2))+1]
WindowedImage = np.reshape(WindowedImage, (-1))
# Compute the histogram and get the bins edges
@@ -87,12 +88,12 @@ def Segmentation(OrthoImageGS, ScaleWrd2Pxl, MaskSize, Step, SedimentMask):
# Compute the deposit map value
Val = 1*(pHist <= ThreshChannels_Trees) + \
- 40*((pHist <= ThreshChannels_Deposits)*(mHist > LimitGravel_Deposit)) + \
+ 40*((pHist <= ThreshChannels_Deposits)*(pHist > ThreshChannels_Trees)*(mHist > LimitGravel_Deposit)) + \
170*((pHist > ThreshChannels_Trees)*(pHist <= ThreshChannels_Deposits)*(mHist <= LimitGravel_Deposit)) + \
210*((pHist > ThreshChannels_Deposits)*(pHist <= ThreshGravel_Deposits)*(mHist <= LimitGravel_Deposit)) + \
255*((pHist > ThreshGravel_Deposits)*(mHist <= LimitGravel_Deposit)) + \
100*((pHist > ThreshChannels_Deposits)*(mHist > LimitGravel_Deposit))
- DepositMap[round(Xpos-MaskSize/2) : round(Xpos+MaskSize/2), round(Ypos-MaskSize/2) : round(Ypos+MaskSize/2)] = Val
+ DepositMap[int(round(Xpos-MaskSize/2)) : int(round(Xpos+MaskSize/2)), int(round(Ypos-MaskSize/2)) : int(round(Ypos+MaskSize/2))] = Val
# For all pixels from the orthorectified image...
for i in range(width):
diff --git "a/D\303\251FI/DepositMethods/Carbonneau2004.py" "b/D\303\251FI/DepositMethods/Carbonneau2004.py"
new file mode 100644
index 0000000000000000000000000000000000000000..f16735f3f3ab2c7a6a538f26b8837adb521da7af
--- /dev/null
+++ "b/D\303\251FI/DepositMethods/Carbonneau2004.py"
@@ -0,0 +1,103 @@
+# -*- coding: utf-8 -*-
+"""
+""Carbonneau2004.py: It contains the segmentation method, developped by P. Carbonneau, to detect deposits on an orthorectified image:
+
+ + Segmentation: Method based on thresholding developped by P. Carbonneau
+"""
+
+__author__ = "Thomas DREVET"
+__copyright__ = "Copyright 2019, Irstea"
+__credits__= "Patrice CARBONNEAU"
+__version__ = "2.0"
+__maintainer__ = "Thomas DREVET"
+__email__ = "thomas.drevet@irstea.fr"
+__status__ = "Production"
+
+
+# Import the libraries
+import math
+import numpy as np
+from skimage import color
+
+
+def Segmentation(OrthoImage, SedimentMask, PatchSize):
+ """
+ Input:
+ + OrthoImage: Orthorectified image - array
+ + SedimentMask: Mask representing the sediment bed - array
+ + PatchSize: Size of the patch used in the method - int
+ Output:
+ + DepositMap: Map of the sediment bed - array
+ """
+
+ # Convert the image in HSV
+ OrthoImageHSV = color.rgb2hsv(OrthoImage)
+
+ # Extract the brightness channel
+ OrthoImageV = OrthoImageHSV[:, :, 2]
+
+ # Get the width and the height of the input orthorectified image
+ width, height = OrthoImageV.shape[:2]
+
+ # For all pixels from the orthorectified image...
+ for i in range(width):
+ for j in range(height):
+
+ # Check if the pixel is inside the sediment mask...
+ if (SedimentMask[i, j] == 0):
+ # If not, Set the Bright value to null
+ OrthoImageV[i, j] = 0
+
+ # Compute the number of patches
+ NbPatchX = math.floor((width)/PatchSize)
+ NbPatchY = math.floor((height)/PatchSize)
+
+ # Create the empty deposit map
+ DepositMap = np.zeros((width, height))
+
+ # For all the steps in the deposit map...
+ for PatchX in range (NbPatchX):
+ for PatchY in range (NbPatchY):
+
+ # Check if the patch is inside the sediment bed
+ if (np.ndarray.min(SedimentMask[PatchX*PatchSize:(PatchX+1)*PatchSize, PatchY*PatchSize:(PatchY+1)*PatchSize]) == 0.0):
+ # if not, set the deposit map value to 0
+ DepositMap[PatchX*PatchSize:(PatchX+1)*PatchSize, PatchY*PatchSize:(PatchY+1)*PatchSize] = 0.0
+ # if yes...
+ else:
+ # Create an empty semi-variogram
+ SV = np.zeros((2*PatchSize, 2*PatchSize), dtype = float)
+
+ # For all the lags of the semi-variogram...
+ for p in range (-PatchSize+1, PatchSize):
+ for q in range (-PatchSize+1, PatchSize):
+
+ # Initialize the value to store the sum used in the semi-variogram
+ sumSV = 0
+ # For all the pixels inside the patch...
+ for i in range (math.floor(1+(abs(p)-p)/2)+math.floor((2*PatchX)*PatchSize/2), math.floor(PatchSize-(abs(p)+p)/2+math.floor((2*PatchX)*PatchSize/2))):
+ for j in range (math.floor(1+(abs(q)-q)/2)+math.floor((2*PatchY)*PatchSize/2), math.floor(PatchSize-(abs(q)+q)/2)+math.floor((2*PatchY)*PatchSize/2)):
+ # Compute the semi-variogram sum
+ sumSV =+ (OrthoImageV[i+p, j+q]-OrthoImageV[i, j])**2
+ # Store the semi-variogram value corresponding to the studied lag
+ SV[p+math.floor(PatchSize/2)-1, q+math.floor(PatchSize/2)-1] = sumSV/(2*(PatchSize-abs(p))*(PatchSize-abs(q)))
+ # Store in the deposit map the value corresponding to the maximum value (sill) of the semi-variogram
+ DepositMap[PatchX*PatchSize:(PatchX+1)*PatchSize, PatchY*PatchSize:(PatchY+1)*PatchSize] = np.ndarray.max(SV)
+
+ # Normalize the deposit map with values between 0 and 255
+ maxDM = np.max(DepositMap)
+ DepositMap[:, :] = np.round(DepositMap[:, :]/maxDM*255)
+
+ # For all pixels from the orthorectified image...
+ for i in range(width):
+ for j in range(height):
+
+ # Check if the pixel is inside the sediment mask...
+ if (DepositMap[i, j] == 0.0):
+ # Replace their value by 255 for a better display
+ DepositMap[i, j] = 255
+
+ # Convert the deposit map in int
+ DepositMap = DepositMap.astype(np.uint8)
+ # Return the deposit map
+ return DepositMap
\ No newline at end of file
diff --git "a/D\303\251FI/DepositMethods/DepositTools.py" "b/D\303\251FI/DepositMethods/DepositTools.py"
new file mode 100644
index 0000000000000000000000000000000000000000..d1069ff9aca86a63424a709c3803c2d9f373b5e2
--- /dev/null
+++ "b/D\303\251FI/DepositMethods/DepositTools.py"
@@ -0,0 +1,118 @@
+# -*- coding: utf-8 -*-
+"""
+""DepositTools.py: It contains several tools that are useful to perform deposit segmentation:
+ + ExportSegmentAsGeoTiff: Function that permits to export a segmentation map under the Geotiff format
+ + GeoTiff2shpFile: Function that permits to convert a GeoTiff segmentation map into several shp files
+"""
+
+__author__ = "Thomas DREVET"
+__copyright__ = "Copyright 2019, Irstea"
+__version__ = "1.5"
+__maintainer__ = "Thomas DREVET"
+__email__ = "thomas.drevet@irstea.fr"
+__status__ = "Production"
+
+
+
+# Import the libraries
+import gdal
+from osgeo import osr, ogr
+import numpy as np
+
+def ExportSegmentAsGeoTiff(SegmentMap, pathSaveSegment, MapBound, ScaleWrd2Pxl, EPSG, MaskColor):
+ """
+ Input:
+ + SegmentMap: Segmentation map - array
+ + pathSaveSegment: path to where we have to save the map - string
+ + MapBound: Boundaries (xmin, xmax; ymin, ymin) of the segmentation - 2x2 array
+ + ScaleWrd2Pxl: Pixel size (in m) - float
+ + EPSG: Spatial reference - string
+ + MaskColor: Mask color to be removed - int
+ """
+ # Get the width and the height of the map
+ width, height = SegmentMap.shape[:2]
+
+ # Get the different classes obtained by the segmentation
+ Class = np.unique(SegmentMap)
+
+ # Remove the mask color
+ if (MaskColor in Class):
+ Class = np.delete(Class, np.where(MaskColor == Class)[0][0])
+ NbClass = len(Class)
+
+ # Create a Geotiff driver in gdal, following the properties
+ driver = gdal.GetDriverByName("GTiff")
+ OutTiff = driver.Create(pathSaveSegment, height, width, (NbClass), gdal.GDT_Byte)
+
+ # Set the Geographic transformation
+ OutTiff.SetGeoTransform((MapBound[0, 0], ScaleWrd2Pxl, 0, MapBound[1, 1], 0, -ScaleWrd2Pxl))
+
+ # Select the World Coordinate system
+ SpatialRef = osr.SpatialReference()
+ SpatialRef.ImportFromEPSG(EPSG)
+ wkt = SpatialRef.ExportToWkt()
+ OutTiff.SetProjection(wkt)
+
+ # For all the classes (except the mask one)...
+ for n in range (0, NbClass):
+ # Initialize a empty matrix to store the binarize map of the class
+ BinMap = np.zeros((width, height), dtype=int)
+ # Compute the binarize map of the class
+ for i in range (width):
+ for j in range (height):
+ if (SegmentMap[i, j]==Class[n]):
+ BinMap[i, j] = 255
+
+ # Create a raster band to store the binarize map of the class
+ Band = OutTiff.GetRasterBand((n+1))
+ # Store the binarize map of the class
+ Band.WriteArray(BinMap[:, :])
+ # Remove the 0 values to have the transparency
+ Band.SetNoDataValue(0.0)
+
+ # Clean the gdal driver
+ OutTiff.FlushCache()
+ OutTiff = None
+
+
+def GeoTiff2shpFile(pathSegMapGeoTiff, pathSaveShp):
+ """
+ Input:
+ + pathSegMapGeoTiff: path to the GeoTiff file - string
+ + pathSaveShp: path to where we have to save the shp file - string
+ """
+ # Open the GeoTiff file using gdal
+ GeoTiffMap = gdal.Open(pathSegMapGeoTiff)
+
+ # Extract the Spatial reference system
+ proj = osr.SpatialReference(wkt=GeoTiffMap.GetProjection())
+ EPSG = proj.GetAttrValue('AUTHORITY', 1)
+
+ # Extract the number of classes
+ NbClass = GeoTiffMap.RasterCount
+
+ # Create a gdal driver to save the data as a shp file
+ Driver = ogr.GetDriverByName("ESRI Shapefile")
+
+ # For all the classes...
+ for i in range (1, NbClass+1):
+ # Create the shp file to store the class
+ DataSource = Driver.CreateDataSource(pathSaveShp + "_" + str(i) + ".shp")
+
+ # Select the World Coordinate system
+ SpatialRef = osr.SpatialReference()
+ SpatialRef.ImportFromEPSG(int(EPSG))
+
+ # Create the layer inside the shp file
+ Layer = DataSource.CreateLayer("Segmentation_" + str(i), SpatialRef)
+
+ # Extract the data from raster band
+ Data = GeoTiffMap.GetRasterBand(i)
+ # Polygonize the data and store them in the layer
+ gdal.Polygonize(Data, Data, Layer, i, [], callback=None)
+
+ # Clean the gdal driver
+ DataSource.FlushCache()
+ DataSource = None
+
+
\ No newline at end of file
diff --git "a/D\303\251FI/Orthorectification/OrthoTools.py" "b/D\303\251FI/Orthorectification/OrthoTools.py"
index 5801756e43fd79a543f082b87f672d87d7cb6cf6..cd1d9b2e7ce5df171c5395772807007e13b209d1 100644
--- "a/D\303\251FI/Orthorectification/OrthoTools.py"
+++ "b/D\303\251FI/Orthorectification/OrthoTools.py"
@@ -5,7 +5,7 @@
+ GetExtrinsicParameters: It permits to obtain the extrensic parameters from the image
+ FindNearest: It permits to return the value and its index of the nearest element of a matrix
+ ComputeOrthorectificatuion: It permits to obtain the orthorectification of the image knowing the parameters
- + ExportAsGeoTiff: It permits to export the image under the geotiff format
+ + ExportOrthoAsGeoTiff: It permits to export the image under the geotiff format
"""
__author__ = "Thomas DREVET"
@@ -20,8 +20,8 @@ import numpy as np
import cv2
import math
from ReadODS import ReadMiresCoord, ReadMiresImag
-import gdal
-from osgeo import osr
+#import gdal
+from osgeo import osr, gdal
def GetExtrinsicParameters(pathMiresImageODS, pathMiresCoordODS, IntrinsicMatrix, DistortCoeffs):
@@ -179,14 +179,14 @@ def ComputeOrthorectification(Image, OrthoLocation, ScaleWrd2Pxl, DTM, Intrinsic
return np.transpose(OrthoImage, (1, 0, 2))
-def ExportAsGeoTiff(OrthoImage, pathSaveImage, OrthoBoundaries, ScaleWrd2Pxl, EPSG, ColorTransparency):
+def ExportOrthoAsGeoTiff(OrthoImage, pathSaveImage, OrthoBoundaries, ScaleWrd2Pxl, EPSG, ColorTransparency):
"""
Input:
+ OrthoImage: Orthorectified image - array
+ pathSaveImage: path to where we have to save the image - string
+ OrthoBoundaries: Boundaries (xmin, xmax; ymin, ymin) of the orthorectification - 2x2 array
+ ScaleWrd2Pxl: Wanted pixel size (in m) - float
- + EPSG: Spacial reference - string
+ + EPSG: Spacial reference - int
+ ColorTransparency: Color to set as transparent - 3x1 array
"""
@@ -203,8 +203,9 @@ def ExportAsGeoTiff(OrthoImage, pathSaveImage, OrthoBoundaries, ScaleWrd2Pxl, EP
# Select the World Coordinate system
SpatialRef = osr.SpatialReference()
- SpatialRef.SetWellKnownGeogCS(EPSG)
- OutTiff.SetProjection(SpatialRef.ExportToWkt())
+ SpatialRef.ImportFromEPSG(EPSG)
+ wkt = SpatialRef.ExportToWkt()
+ OutTiff.SetProjection(wkt)
# Export the R, G, B values on the raster band
R = OutTiff.GetRasterBand(1)
diff --git "a/D\303\251FI/Orthorectification/Orthorectification.py" "b/D\303\251FI/Orthorectification/Orthorectification.py"
index 83e81cc6323eaf5b2304fad6bdbb177ec6e57fe4..ac7c7e1692564ea10b6ea76c8033451f15900904 100644
--- "a/D\303\251FI/Orthorectification/Orthorectification.py"
+++ "b/D\303\251FI/Orthorectification/Orthorectification.py"
@@ -17,18 +17,18 @@ import numpy as np
import imageio
import os
import cv2
-from OrthoTools import GetExtrinsicParameters, ComputeOrthorectification, ExportAsGeoTiff
+from OrthoTools import GetExtrinsicParameters, ComputeOrthorectification, ExportOrthoAsGeoTiff
from ReadTXT import ReadIntParam, ReadDTM
import matplotlib.pyplot as plt
# Set the path to the image
-pathImage = "C:\\Users\\thomas.drevet\\Documents\\Images_Cameras\\camera2\\IMAG0092.JPG"
+pathImage = "C:\\Users\\thomas.drevet\\Documents\\Images_Cameras\\camera2\\IMAG0592.JPG"
# Set the path to DTM file
-pathDTM = "C:\\Users\\thomas.drevet\\Documents\\Seafile\\DeFI\\Données_Géoréférencement\\Flat_DTM_StMarie.txt"
+pathDTM = "C:\\Users\\thomas.drevet\\Documents\\Seafile\\DeFI\\Donnees_Georeferencement\\Flat_DTM_StMarie.txt"
# Set the path to the ODS file containing the mires locations
-pathMiresImageODS = "C:\\Users\\thomas.drevet\\Documents\\GéoMires\\camera2\\IMAG0092.ods"
+pathMiresImageODS = "C:\\Users\\thomas.drevet\\Documents\\GéoMires\\camera2\\IMAG0592.ods"
# Set the path to the ODS file containing the mires world coordinates
-pathMiresCoordODS = "C:\\Users\\thomas.drevet\\Documents\\Seafile\\DeFI\\Données_Géoréférencement\\coordonnees-mires-saintemarie.ods"
+pathMiresCoordODS = "C:\\Users\\thomas.drevet\\Documents\\Seafile\\DeFI\\Donnees_Georeferencement\\coordonnees-mires-saintemarie.ods"
# Set the pixel size (in m)
ScaleWrd2Pxl = 0.05
# Set the Orthorectification boundaries
@@ -104,4 +104,4 @@ if (savePNG == True):
# Save the orthorectified image as a GeoTiff, if requested
if (saveGeoTiff == True):
- ExportAsGeoTiff(OrthoImage, "OrthoImage2_0092.tif", OrthoBoundaries, ScaleWrd2Pxl, "EPSG:3945", BkGrdColor)
+ ExportOrthoAsGeoTiff(OrthoImage, "OrthoImage2_0592.tif", OrthoBoundaries, ScaleWrd2Pxl, 3945, BkGrdColor)
diff --git "a/D\303\251FI/TestDepositMethod.py" "b/D\303\251FI/TestDepositMethod.py"
index 83c28b234e7c7309c7a8c941e3ea837cc8226d26..5c4d0523ccecd3b84c763c4e4f8c99d104ae30e1 100644
--- "a/D\303\251FI/TestDepositMethod.py"
+++ "b/D\303\251FI/TestDepositMethod.py"
@@ -5,7 +5,7 @@
__author__ = "Thomas DREVET"
__copyright__ = "Copyright 2019, Irstea"
-__version__ = "2.0"
+__version__ = "2.1"
__maintainer__ = "Thomas DREVET"
__email__ = "thomas.drevet@irstea.fr"
__status__ = "Production"
@@ -16,12 +16,13 @@ __status__ = "Production"
import imageio
from skimage import color
from DepositMethods.Camenen2013 import Segmentation as CamenenSeg
-#from DepositMethods.Carbonneau2004 import Segmentation as CarbonneauSeg
+from DepositMethods.Carbonneau2004 import Segmentation as CarbonneauSeg
+from DepositMethods.DepositTools import ExportSegmentAsGeoTiff, GeoTiff2shpFile
import matplotlib.pyplot as plt
import numpy as np
# Set the path to the image
-pathOrthoImage = "C:\\Users\\thomas.drevet\\Documents\\Seafile\\DeFI\\Images_Orthorectifiees\\OrthoImage2_0592.png"
+pathOrthoImage = "C:\\Users\\thomas.drevet\\Desktop\\OrthoImage2_0592.tif"
# Set the path to the sediment mask
@@ -34,28 +35,27 @@ ScaleWrd2Pxl = 0.05
MaskSize = 20
# Set the Step value
-Step = 7
+Step = 10
-# Set the Patch size
-PatchSize = 7
+# Set the Camenen histogram thresholds
+CamenenHistThr = [155, 130, 50, 0.03]
-# Set the Histogram Equalizer choice
-HistStretch = True
+# Set the Patch size
+PatchSize = 20
# Read the orthorectified image and convert it in gray scale
OrthoImage = imageio.imread(pathOrthoImage)
-OrthoImageGS = color.rgb2gray(OrthoImage)*255
+OrthoImageGS = np.around(color.rgb2gray(OrthoImage)*255).astype(np.uint8)
# Read the sediment mask and convert it in gray scale
SedMask = imageio.imread(pathSedMask)
-SedMaskGS = color.rgb2gray(SedMask)*255
+SedMaskGS = np.around(color.rgb2gray(SedMask)*255).astype(np.uint8)
# Compute the deposit map with the Camenen method
-DepositMapCamenen = CamenenSeg(OrthoImageGS, ScaleWrd2Pxl, MaskSize, Step, SedMaskGS)
-DepositMapCamenen.astype(np.uint8)
+DepositMapCamenen = CamenenSeg(OrthoImageGS, ScaleWrd2Pxl, MaskSize, Step, SedMaskGS, CamenenHistThr)
# Compute the deposit map with the Carbonneau 2004 method
-DepositMapCarbonneau = CarbonneauSeg(OrthoImage, SedMaskGS, HistStretch, PatchSize)
+DepositMapCarbonneau = CarbonneauSeg(OrthoImage[:, :, 0:3], SedMaskGS, PatchSize)
# Display the orthorectified image and the deposit map
Inp = plt.figure(0)
@@ -66,10 +66,12 @@ MapCamenen = plt.figure(1)
plt.imshow(DepositMapCamenen, cmap='gray')
plt.title("Map Camenen")
-#MapCarbonneau = plt.figure(1)
-#plt.imshow(DepositMapCarbonneau , cmap='gray')
-#plt.title("Map Carbonneau")
+MapCarbonneau = plt.figure(2)
+plt.imshow(DepositMapCarbonneau , cmap='gray')
+plt.title("Map Carbonneau")
# Save the deposit map
-imageio.imsave("Camenen2_0592.png", DepositMapCamenen)
-#imageio.imsave("Carbonneau2_0592.png", DepositMapCarbonneau)
\ No newline at end of file
+ExportSegmentAsGeoTiff(DepositMapCamenen, "C:\\Users\\thomas.drevet\\Documents\\Divers\\DMCamenen2_0592.tif", np.array([[1959500.00, 1959535.00], [4242750.00, 4242800.00]]), ScaleWrd2Pxl, 3945, 0)
+GeoTiff2shpFile("C:\\Users\\thomas.drevet\\Documents\\Divers\\DMCamenen2_0592.tif","C:\\Users\\thomas.drevet\\Documents\\Divers\\CamenenTest")
+imageio.imsave("Camenen_Drone1cm.png", DepositMapCamenen)
+imageio.imsave("Carbonneau_Drone1cm_1m.png", DepositMapCarbonneau)
\ No newline at end of file