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preProcess.py
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preProcess.py
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from numpy.core.numeric import cross
from classes import Image, Feature, Cell
import logging
import numpy as np
from numpy.linalg.linalg import inv, norm
import cv2 as cv
def run(imageFile, featureFile, beta, isDisplay) :
print("==========================================================", flush=True)
print(" PREPROCESSING ", flush=True)
print("==========================================================", flush=True)
images = loadImages(imageFile)
calibrateImages(images)
setCell(images, beta, isDisplay)
featureDetection(images, featureFile, beta, isDisplay)
return images
def loadImages(filename) :
images = []
file = open(filename, 'r')
id = 0
lines = file.readlines()
for line in lines :
words = line.split()
name = words[0]
ins = np.array([
[float(words[1]), float(words[2]), float(words[3])],
[float(words[4]), float(words[5]), float(words[6])],
[float(words[7]), float(words[8]), float(words[9])]
])
ex = np.array([
[float(words[10]), float(words[11]), float(words[12]), float(words[19])],
[float(words[13]), float(words[14]), float(words[15]), float(words[20])],
[float(words[16]), float(words[17]), float(words[18]), float(words[21])]
])
img = Image(name, ins, ex, id)
images.append(img)
id += 1
logging.info(f'Total Images : {len(images)}')
return images
def calibrateImages(images) :
for image in images :
logging.info(f'IMAGE {image.id:02d}:Calibrating images...')
ins = image.ins
ex = image.ex
pmat = ins @ ex
R = np.array([
[ex[0][0], ex[0][1], ex[0][2]],
[ex[1][0], ex[1][1], ex[1][2]],
[ex[2][0], ex[2][1], ex[2][2]]
])
t = np.array([
ex[0][3],
ex[1][3],
ex[2][3]
])
center = -inv(R) @ t
center = np.array([
center[0],
center[1],
center[2],
1
])
zaxis = np.array(pmat[2])
zaxis[3] = 0
ftmp = norm(zaxis)
zaxis /= ftmp
zaxis = np.array([zaxis[0], zaxis[1], zaxis[2]])
xaxis = np.array([pmat[0][0], pmat[0][1], pmat[0][2]])
yaxis = cross(zaxis, xaxis)
yaxis /= norm(yaxis)
xaxis = cross(yaxis, zaxis)
image.pmat = pmat
image.center = center
image.xaxis = xaxis
image.yaxis = yaxis
image.zaxis = zaxis
def featureDetection(images, filename, beta, isDisplay) :
file = open(filename, 'r')
lines = file.readlines()
for image in images :
logging.info(f'IMAGE {image.id:02d}:Detecting features...')
img = cv.imread(image.name)
if isDisplay :
x = beta
y = beta
width = img.shape[1]
height = img.shape[0]
while x < width :
cv.line(img, (x, 0), (x, height), (0, 255, 0), 1)
x += beta
while y < height :
cv.line(img, (0, y), (width, y), (0, 255, 0), 1)
y += beta
for line in lines :
words = line.split()
if image.name == words[0] :
feats = []
i = 0
while i < int(words[1]) * 2 :
feat = Feature(int(words[2+i]), int(words[3+i]), image)
if isDisplay :
cv.circle(img, (feat.x, feat.y), 4, (0, 0, 255), -1)
feats.append(feat)
a = -2
while a < 3 :
b = -2
while b < 3 :
image.cells[int(feat.y/beta+b)][int(feat.x/beta+a)].feats.append(feat)
if isDisplay :
coord = image.cells[int(feat.y/beta+b)][int(feat.x/beta+a)].center
cv.circle(img, (int(coord[0]), int(coord[1])), 2, (255, 0, 0), -1)
b += 1
a += 1
i += 2
image.feats = feats
if isDisplay :
cv.imshow(f'Image {image.id:02d}', img)
cv.waitKey(0)
cv.destroyAllWindows()
def setCell(images, beta, isDisplay) :
for image in images :
logging.info(f'IMAGE {image.id:02d}:Applying cells')
img = cv.imread(image.name)
width = img.shape[1]
height = img.shape[0]
cells = np.empty((int(height/beta), int(width/beta)), dtype=Cell)
y = 0
i = 0
while y < height :
x = 0
j = 0
while x < width :
center = np.array([x+beta/2, y+beta/2])
cell = Cell(center, image)
if isDisplay :
cv.circle(img, (int(center[0]), int(center[1])), 2, (0, 0, 255), -1)
cells[i][j] = cell
j += 1
x += beta
i += 1
y += beta
image.cells = cells
if isDisplay :
x = beta
y = beta
while x < width :
cv.line(img, (x, 0), (x, height), (0, 255, 0), 1)
x += beta
while y < height :
cv.line(img, (0, y), (width, y), (0, 255, 0), 1)
y += beta
cv.imshow(f'Image {image.id:02d}', img)
cv.waitKey(0)
cv.destroyAllWindows()