#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
#######################################
#### LSPyIV --TRANSFORMATION MODULE
#######################################
Python LSPIV tools
Contains all definitions/functions that deals with
transformations between coordinate systems (image/world)
"""
import numpy as np
import os
from tkinter import Tk
from tkinter.filedialog import askopenfilename
class GRP:
"""Groud Reference Points class"""
def __init__(self):
# World coordinates
self.X = -99.99
self.Y = -99.99
self.Z = -99.99
# Image coordinates
self.i = -99
self.j = -99
class imgRef:
"""Image References for transformations"""
def __init__(self):
self.xyMin = (-99.99,-99.99)
self.xyMax = (-99.99,-99.99)
self.res = -99.99
self.ninj = (-99,-99) # Size of ORIGINAL image
class camera:
"""Camera class. contains many informations that could also be used for other purposes"""
def __init__(self):
self.position = [] # usually 3-D vector (numpy array)
self.angles = [] # usually 3D vector (numpy array)
self.intrinsic = {} # dict containing intrinsic parameters
self.scale = -99 # used for orthophotographic camera (equals to zoom factor)
self.fps = -99
self.resolution = -99 # resolution of the camera (usually in m/pix or pix/m)
self.resolutionInfo = "" # enter here the unit of resolution to avoid confusions
self.imagesize = () # size of image (tuple)
self.a = [] # a matrix from DLT, used to convert world to image space
self.a_inv = [] # a_inv matrix, used to convert from image to world coordinates
self.xy0 = () # Position of lowest image corner in world unit
def read_a(self,filename = ""):
"""
Reads the file containing the a matrix for transformation between space and image coodinate s
Parameters
----------
filename : [str], optional
Path to the file 'coeff.dat'. If "" then a GUI will be opened to select file
The default is "".
Returns
-------
- errno [int]
Error number. Possible values :
- 0 - no errors
- 1 - wrong format contains file coeff.dat
"""
# ---- Initialisation
isExist = os.path.exists(filename) # Check if file exists
if (filename == "") or (isExist == False):
# Open GUI to find file - tkinker lib is used
Tk().withdraw()
filename = askopenfilename(title = "Select coeff.dat", filetypes = (("coeff file","coeff.dat"),("all files","*.*"))) # Get file path
if (filename[-4:] != ".dat" ):
print("ERROR : file format doesn't match\n")
return 1
# ---- Read coeff.dat
fCoeff = open(filename,"r")
lstExtract = fCoeff.read()
lstExtract = lstExtract.strip()
lstExtract = lstExtract.split("\n")
fCoeff.close()
if(int(lstExtract[0]) == 11):
#-------------------
self.a = np.zeros(11,dtype = float)
# from verif_ortho.f90
self.a[0] = np.float(lstExtract[1])
self.a[1] = np.float(lstExtract[2])
self.a[2] = np.float(lstExtract[3])
self.a[3] = np.float(lstExtract[4])
self.a[4] = np.float(lstExtract[8])
self.a[5] = np.float(lstExtract[9])
self.a[6] = np.float(lstExtract[10])
self.a[7] = np.float(lstExtract[11])
self.a[8] = np.float(lstExtract[5])
self.a[9] = np.float(lstExtract[6])
self.a[10] = np.float(lstExtract[7])
else:
print("ERROR: wrong format from file 'coeff.dat'\n")
return 1
return 0
def read_a_inv(self,filename = ""):
"""
Reads the file containing the a_inv matrix for transformation between space and image coodinate s
Parameters
----------
filename : [str], optional
Path to the file 'coeff.dat'. If "" then a GUI will be opened to select file
The default is "".
Returns
-------
- errno [int]
Error number. Possible values :
- 0 - no errors
- 1 - wrong format contains file coeff.dat
"""
# ---- Initialisation
isExist = os.path.exists(filename) # Check if file exists
if (filename == "") or (isExist == False):
# Open GUI to find file - tkinker lib is used
Tk().withdraw()
filename = askopenfilename(title = "Select coeff_inv.dat", filetypes = (("coeff_inv file","coeff_inv.dat"),("all files","*.*"))) # Get file path
if (filename[-4:] != ".dat" ):
print("ERROR : file format doesn't match\n")
return 1
# ---- Read coeff.dat
fVerif = open(filename,"r")
# Burn first line (header)
ligne = fVerif.readline()
# Initialize arrays
ligne = fVerif.readline()
extract = ligne[:-1].split(' ')
fVerif.close()
# Arrange extracted data
extract = [nb for nb in extract if nb!='']
self.a_inv = np.array(extract,dtype = np.float64)
return 0
def image2space(self,imgIndx,xy0 = True,ni = True):
"""
Converts image indexes to world units with information of the camera and xy0.
Assume that the input image is already ortho-rectified (i.e. image can be assumed to be a plan XY)
Parameters
----------
- imgIndx : [npArrayInt]
Indexes of the images to be transformed. --> shape : [(ind),(i,j)]
WARNING : image coordinate are expected.
Values from Fudaa-LSPIV are usually given in a mathematical coordinate space with (0,0) located down left
So the i index need to be "invert" --> correctiIndex = imageSize(i) - iIndexFudaa
- camera : [lspiv.transform.camera()]
Contains the information of the camera
- xyz0 : [npArrayFloat]
Offset (in meters) apply on the values X, Y for transformation
Returns
-------
- SpaceCoord [npArrayFloat]
X,Y values in meters
- errno [int]
In case of an error this function returns an integer
- 1 - Information missing on the camera : no resolution and no scaling
- 2 - Image isn't squarred, problem with scaling...
- 3 - ResolutionInfo of the camera isn't recognize
"""
if self.resolutionInfo == "":
# Case no resolution is entered, use simple scaling (typical blender case with othographic camera)
if self.scale == -99:
print("ERROR : Information missing on the camera : no resolution and no scaling")
return 1
# Image size is assumed to be squared
if self.imagesize[0]!=self.imagesize[1]:
print("ERROR : Image isn't squarred, problem with scaling...")
return 1
res = self.imagesize[0] / self.scale
elif self.resolutionInfo == "m/pix":
# Case resolution is given in meter/pixels (typical units from Fudaa-LSPIV project)
res = 1/self.resolution
elif self.resolutionInfo == "pix/m":
# Case resolution is given in pixels/meter
res = self.resolution
else:
print("ERROR : resolution information of the camera isn't recognize. Expected : 'm/pix' or 'pix/m'")
return 3
# If no xy0 are passed to the function they're calculated from the camera data
if isinstance(xy0,bool) and self.scale != -99:
xy0 = (self.position - (0.5*self.scale))[:2]
if len(imgIndx)==0:
print("WARNING : imgIndx is empty...")
# Swap column to get (j,i) as j is x and i is y
if ni == True:
ni = np.max(imgIndx[:,0])
JIimgIndx = np.array([imgIndx[:,1],ni-imgIndx[:,0]]).T
out = (JIimgIndx/res) + xy0
return out
def velSpace2dispImage(self,spaceVel,xy0 = np.nan):
"""
Converts image indexes to world units with information of the camera and xy0.
Assume that the input image is already ortho-rectified (i.e. image can be assumed to be a plan XY)
Parameters
----------
- imgIndx : [npArrayInt]
Indexes of the images to be transformed. --> shape : [(ind),(i,j)]
WARNING : image coordinate are expected.
Values from Fudaa-LSPIV are usually given in a mathematical coordinate space with (0,0) located down left
So the i index need to be "invert" --> correctiIndex = imageSize(i) - iIndexFudaa
- camera : [lspiv.transform.camera()]
Contains the information of the camera
- xyz0 : [npArrayFloat]
Offset (in meters) apply on the values X, Y for transformation
Returns
-------
- SpaceCoord [npArrayFloat]
X,Y values in meters
- errno [int]
In case of an error this function returns an integer
- 1 - Information missing on the camera : no resolution and no scaling
- 2 - Image isn't squarred, problem with scaling...
- 3 - ResolutionInfo of the camera isn't recognize
"""
# if isinstance(camera,transform.camera):
# print("\nERROR : wrong format of camera passed to the function. Expected : lspiv.transform.camera ")
# return 1
if self.resolutionInfo == "":
# Case no resolution is entered, use simple scaling (typical blender case with othographic camera)
if self.scale == -99:
print("\nERROR : Information missing on the camera : no resolution and no scaling")
return 1
# Image size is assumed to be squared
if self.imagesize[0]!=self.imagesize[1]:
print("\nERROR : Image isn't squarred, problem with scaling...")
return 1
res = self.imagesize[0] / self.scale
elif self.resolutionInfo == "m/pix":
# Case resolution is given in meter/pixels (typical units from Fudaa-LSPIV project)
res = 1/self.resolution
elif self.resolutionInfo == "pix/m":
# Case resolution is given in pixels/meter
res = self.resolution
else:
print("\nERROR : resolution information of the camera isn't recognize. Expected : 'm/pix' or 'pix/m'")
return 3
# If no xy0 are passed to the function they're calculated from the camera data
if np.isnan(xy0):
xy0 = (self.position - (0.5*self.scale))[:2]
if len(spaceVel)==0:
print("\nWARNING : Values are empty...")
# Compute displacement based on camera info
XYdisp = spaceVel / self.fps
JIspaceV = (XYdisp)*res
# Swap column to get (i,j) as x is j and y is i
IJindex = np.array([JIspaceV[:,1],JIspaceV[:,0]]).T
# Invert i ax
IJindex[:,0] = -IJindex[:,0]
return IJindex
###################
#### FUNCTIONS
###################
def read_a(filename = ""):
"""
Reads the file containing the a matrix for transformation between space and image coodinate s
Parameters
----------
filename : [str], optional
Path to the file 'coeff.dat'. If "" then a GUI will be opened to select file
The default is "".
Returns
-------
- errno [int]
Error number. Possible values :
- 0 - no errors
- 1 - wrong format contains file coeff.dat
"""
# ---- Initialisation
isExist = os.path.exists(filename) # Check if file exists
if (filename == "") or (isExist == False):
# Open GUI to find file - tkinker lib is used
Tk().withdraw()
filename = askopenfilename(title = "Select coeff.dat", filetypes = (("coeff file","coeff.dat"),("all files","*.*"))) # Get file path
if (filename[-4:] != ".dat" ):
print("ERROR : file format doesn't match\n")
return 1
# ---- Read coeff.dat
fCoeff = open(filename,"r")
lstExtract = fCoeff.read()
lstExtract = lstExtract.strip()
lstExtract = lstExtract.split("\n")
fCoeff.close()
if(int(lstExtract[0]) == 11):
#-------------------
a = np.zeros(11,dtype = float)
# from verif_ortho.f90
a[0] = np.float(lstExtract[1])
a[1] = np.float(lstExtract[2])
a[2] = np.float(lstExtract[3])
a[3] = np.float(lstExtract[4])
a[4] = np.float(lstExtract[8])
a[5] = np.float(lstExtract[9])
a[6] = np.float(lstExtract[10])
a[7] = np.float(lstExtract[11])
a[8] = np.float(lstExtract[5])
a[9] = np.float(lstExtract[6])
a[10] = np.float(lstExtract[7])
else:
print("ERROR: wrong format from file 'coeff.dat'\n")
return 1
return a
def read_a_inv(filename = ""):
"""
Reads the file containing the a_inv matrix for transformation between space and image coodinate s
Parameters
----------
filename : [str], optional
Path to the file 'coeff.dat'. If "" then a GUI will be opened to select file
The default is "".
Returns
-------
- errno [int]
Error number. Possible values :
- 0 - no errors
- 1 - wrong format contains file coeff.dat
"""
# ---- Initialisation
isExist = os.path.exists(filename) # Check if file exists
if (filename == "") or (isExist == False):
# Open GUI to find file - tkinker lib is used
Tk().withdraw()
filename = askopenfilename(title = "Select coeff_inv.dat", filetypes = (("coeff_inv file","coeff_inv.dat"),("all files","*.*"))) # Get file path
if (filename[-4:] != ".dat" ):
print("ERROR : file format doesn't match\n")
return 1
# ---- Read coeff.dat
fVerif = open(filename,"r")
# Burn first line (header)
ligne = fVerif.readline()
# Initialize arrays
ligne = fVerif.readline()
extract = ligne[:-1].split(' ')
fVerif.close()
# Arrange extracted data
extract = [nb for nb in extract if nb!='']
a_inv = np.array(extract,dtype = np.float64)
return a_inv
# Space coordinates to image coordinate (from Fudaa-LSPIV source)
def space2CRT(a,x,y,h):
xp=((a[0]*x)+(a[1]*y)+(a[2]*h+a[3])) / ((a[8]*x)+(a[9]*y)+(a[10]*h+1))
yp=((a[4]*x)+(a[5]*y)+((a[6]*h)+a[7])) / ((a[8]*x)+(a[9]*y)+(a[10]*h+1))
return (yp,xp)
# Image to space coordinate
def CRT2space(a_inv,i,j):
x = (a_inv[0]*j+a_inv[1]*i+a_inv[2]) / (a_inv[3]*j+a_inv[4]*i+a_inv[5])
y = (a_inv[6]*j+a_inv[7]*i+a_inv[8]) / (a_inv[3]*j+a_inv[4]*i+a_inv[5])
return (x,y)
def CRT2space2D(a_inv,i,j):
x = (a_inv[0]*j+a_inv[1]*i+a_inv[2]) / (a_inv[6]*j+a_inv[7]*i+1)
y = (a_inv[3]*j+a_inv[4]*i+a_inv[5]) / (a_inv[6]*j+a_inv[7]*i+1)
return (x,y)
def read_grid(filename = ""):
"""
Reads grid.dat file and arrange it following the indexing order.
Parameters
----------
filename : [str], optional
Path to the file 'coeff.dat'. If "" then a GUI will be opened to select file
The default is "".
indexing : [str], optional
Defines the order used to store data.
- "ij" : traditionnal ij indexing (used for images)
- "raw": Fudaa-LSPIV indexing (raw values in grid.dat)
Returns
-------
- errno [int]
Error number. Possible values :
- 0 - no errors
- 1 - wrong format contains file coeff.dat
"""
# ---- Initialisation
isExist = os.path.exists(filename) # Check if file exists
if (filename == "") or (isExist == False):
# Open GUI to find file - tkinker lib is used
Tk().withdraw()
filename = askopenfilename(title = "Select grid.dat", filetypes = (("grid file","grid.dat"),("all files","*.*"))) # Get file path
if (filename[-4:] != ".dat" ):
print("ERROR : file format doesn't match\n")
return 1
# ---- Read coeff.dat
fGrid = open(filename,"r")
lstExtract = fGrid.read()
lstExtract = lstExtract.strip()
lstExtract = lstExtract.split("\n")
fGrid.close()
i,j = [],[]
# Extract fi,fj (fudaa i and fudaa j)
for el in lstExtract:
fj,fi = el.split()
i.append(int(fi))
j.append(int(fj))
return i,j
def bicubic_at(ip,jp,im):
i = int(ip)
j = int(jp)
sum_fx = 0
for k in range(4):
for l in range(4):
sx = abs(j+k-2-jp)
sy = abs(i+l-2-ip)
if ((sx >= 0) and (sx < 1)):
#Cx = un - deux*(sx*sx) + (sx*sx*sx)
Cx = 1. + (sx-2.)*sx*sx
elif ((sx >= 1) and (sx < 2)):
#Cx = four - huit*sx + cinq*(sx*sx) - (sx*sx*sx)
Cx = 4. + ((5. - sx)*sx - 8.)*sx
elif (sx > 2):
Cx = 0.
if ((sy >= 0) and (sy < 1)):
#Cy = un - deux*(sy*sy) + (sy*sy*sy)
Cy = 1 + (sy-2)*sy*sy
elif ((sy >= 1) and (sy < 2)):
#!Cy = four - huit*sy + cinq*(sy*sy) - (sy*sy*sy)
Cy = 4 + ((5. -sy)*sy - 8.)*sy
elif (sy > 2):
Cy = 0.
fx = im[i+l-1,j+k-1]*Cx*Cy
sum_fx = sum_fx+fx
if (int(sum_fx) > 255):
sum_fx = 255
if (int(sum_fx) < 0):
sum_fx = 0
return int(sum_fx)
def readGRPtable(filename):
# Open GRP file
try:
f = open(filename,"r")
buff = f.read()
f.close()
except Exception as e:
print("ERROR reading file coeff.dat : " + str(e))
return 1
# Get number of GRP
i0 = buff.find("\n")
i1 = i0 + buff[i0+1:].find("\n")
nbGRP = int(buff[i0+1:i1+1])
# Read file
if0 = buff.find("j")
tmp = np.array(buff[if0+2:].split(),float)
# Re-arrange data
lstGRP = tmp.reshape((nbGRP,5))
return lstGRP
def writeGRPtable(GRP,filename,ni,nj):
buff = "GRP V2.0 {} {}\n".format(int(ni),int(nj))
buff += "{}\nX\tY\tZ\ti\tj\n".format(int(np.shape(GRP)[0]))
for el in GRP:
buff += "%.3f\t%.3f\t%.3f\t%d\t%d\n"%(el[0],el[1],el[2],int(el[3]),int(el[4]))
# Open GRP file
try:
f = open(filename,"w")
f.write(buff)
f.close()
except Exception as e:
print("ERROR reading file coeff.dat : " + str(e))
return 1
return 0