import cv2 as cv
import miscutils
filename = r'D:\Users\me\Downloads\croppedcloud.jpg'
resizeFactor = 0.2
cloud = cv.resize(cv.imread(filename), (0, 0),
fx=resizeFactor,
fy=resizeFactor)
mapped = miscutils.brMap(cloud)
thresh = miscutils.hytaThreshold(mapped)
cv.imshow('threshold', thresh)
cv.imshow('cloud', cloud)
while (cv.waitKey() == 0):
pass
#this code is bad
import cv2 as cv
import numpy as np
import miscutils
import random
image = cv.imread(
r"C:\Users\ktsun\AppData\Local\Programs\Python\Python38-32\cloud.jpg")
cv.imshow('orig', image)
#CHANGE AS NEEDED (do not set too high or else your computer will explode)
radius = 1
threshold = 0.25
ret, image = cv.threshold(miscutils.brMap(image), threshold, 1,
cv.THRESH_BINARY)
image = np.array(image, dtype='float32')
image = cv.cvtColor(image, cv.COLOR_GRAY2BGR)
cv.imshow('thresh', image)
for i in range(0, image.shape[0]):
for j in range(0, image.shape[1]):
pixel = image[i][j]
if pixel[0] == 0:
colorFound = False
color = np.array([0, 0, 0])
vDist = 0
#vertical search
for y in range(i - radius, i + radius):
if y < 0 or y > image.shape[0]:
continue
import miscutils
import cv2 as cv
import numpy as np
import copy
cloudOld = cv.resize(cv.imread(r'D:\Users\me\Downloads\alignedleft.jpg'),(0,0),fx=0.4,fy=0.4)
cloudNew = cv.resize(cv.imread(r'D:\Users\me\Downloads\alignedright.jpg'),(0,0),fx=0.4,fy=0.4)
mappedOld = miscutils.brMap(cloudOld)
mappedNew = miscutils.brMap(cloudNew)
thOld = miscutils.hytaThreshold(mappedOld)
thNew = miscutils.hytaThreshold(mappedNew)
grayOld = cv.cvtColor(cloudOld,cv.COLOR_BGR2GRAY)
grayNew = cv.cvtColor(cloudNew,cv.COLOR_BGR2GRAY)
pOld = cv.goodFeaturesToTrack(grayOld,100,0.3,7,mask=thOld)
pNew,st,err = cv.calcOpticalFlowPyrLK(grayOld,grayNew,pOld,None)
goodOld=pOld[st==1]
goodNew=pNew[st==1]
for i in range(len(goodOld)):
cv.arrowedLine(cloudOld,tuple(goodOld[i]),tuple(goodNew[i]),(0,255,0), thickness=2)
cv.imshow('optical flow', cloudOld)
while(cv.waitKey())==0:
pass
cv.destroyAllWindows()
def binary(img, fixedThresh=None, sdthresh=None):
return cv.threshold(img, fixedThresh, 255, cv.THRESH_BINARY_INV)[1]
methods['binary'] = binary
methods['otsu'] = kwargsWrapper(
lambda img: cv.threshold(cv.GaussianBlur(img, (5, 5), 0), 0, 255, cv.
THRESH_BINARY_INV + cv.THRESH_OTSU)[1])
methods['hybrid otsu'] = hybridFactory(methods['otsu'])
methods['mce'] = kwargsWrapper(lambda img: cv.threshold(
img, filters.threshold_li(img), 255, cv.THRESH_BINARY_INV)[1])
methods['hybrid mce'] = hybridFactory(methods['mce'])
maps = {}
maps['br'] = lambda x: np.array(miscutils.brMap(x) * 255, dtype='uint8')
maps['saturation'] = lambda img: cv.cvtColor(img, cv.COLOR_BGR2HSV)[:, :, 1]
params = {}
params['br'] = {'fixedThresh': int(0.25 * 255), 'sdthresh': 0.03}
params['saturation'] = {'fixedThresh': 29, 'sdthresh': 4.5}
imDirectory = r'C:\Users\me\cloud-vision\threshtester\images'
files = os.listdir(imDirectory)
gtDirectory = r'C:\Users\me\cloud-vision\threshtester\2GT'
results = {
mapName: {
methodName: {result: 0
for result in confusion}
for methodName in methods
}
for mapName in maps
}
import miscutils
import cv2 as cv
import numpy as np
import copy
import matplotlib.pyplot as plt
cloud=cv.imread(r'C:\Users\ktsun\AppData\Local\Programs\Python\Python38-32\stuff\cloud.jpg')
img=np.array(miscutils.brMap(cloud)*255,dtype='uint8')
blur = cv.GaussianBlur(img,(5,5),0)
ret,th = cv.threshold(blur,0,255,cv.THRESH_BINARY_INV+cv.THRESH_OTSU)
contours, hier = cv.findContours(th, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
imContours = copy.deepcopy(cloud)
cv.drawContours(imContours, contours, -1, (0,0,255),2)
# removes contours which are children of other contours
indices = filter(lambda x: hier[0][x][3] < 0, range(len(hier[0])))
contoursFiltered = list(map(lambda x: contours[x],indices))
imFiltered = copy.deepcopy(cloud)
cv.drawContours(imFiltered, contoursFiltered, -1, (0,0,255),2)
# finds bounding rectangles of filtered contours
boundRects = list(map(lambda x: cv.boundingRect(x),contoursFiltered))
for rect in boundRects:
cv.rectangle(cloud,(rect[0],rect[1]),(rect[0]+rect[2],rect[1]+rect[3]),(0,255,0),2)
cv.imshow('rect',cloud)
cv.imshow('contours',imContours)
cv.imshow('filtered',imFiltered)
##following orb code from opencv docs
img2 = cv.imread(r'C:\Users\ktsun\AppData\Local\Programs\Python\Python38-32\stuff\cloud.jpg',cv.IMREAD_GRAYSCALE) # trainImage
for rect in boundRects:
cloud=cv.imread(r'C:\Users\ktsun\AppData\Local\Programs\Python\Python38-32\stuff\cloud.jpg')
import copy
import cv2 as cv
import miscutils
import numpy as np
BLOCKROWS = 7
filenames = [
r'C:\Users\me\cloud-vision\examples\aligned1.jpg',
r'C:\Users\me\cloud-vision\examples\aligned2.jpg',
r'C:\Users\me\cloud-vision\examples\aligned3.jpg'
]
ims = [
cv.resize(cv.imread(file), (0, 0), fx=0.5, fy=0.5) for file in filenames
]
mapped = [miscutils.brMap(im) for im in ims]
diff2 = mapped[2] - mapped[1]
diff1 = mapped[1] - mapped[0]
diff1 = np.array((diff1 - diff1.min()) / (diff1.max() - diff1.min()) * 255,
dtype='uint8')
diff2 = np.array((diff2 - diff2.min()) / (diff2.max() - diff2.min()) * 255,
dtype='uint8')
thresh1 = cv.threshold(diff1, 0, 255, cv.THRESH_BINARY + cv.THRESH_OTSU)[1]
thresh2 = cv.threshold(diff2, 0, 255, cv.THRESH_BINARY + cv.THRESH_OTSU)[1]
cv.imshow('thresh1', thresh1)
cv.imshow('thresh2', thresh2)
cv.waitKey(0) & 0xFF
blockHeight = int(diff1.shape[0] / BLOCKROWS)
blockWidth = int(diff1.shape[1] / BLOCKROWS)
im1 = copy.deepcopy(ims[1])
for i in range(BLOCKROWS):
(top, bottom) = tuple(np.array((i, i + 1)) * blockHeight)
for j in range(BLOCKROWS):