def FillDifferenceImage(differenceImage):
height, width = differenceImage.shape[:]
afterDifference = np.ndarray((height + Setting.DefineManager.ADD_IMAGE_HEIGHT * 2,width + Setting.DefineManager.ADD_IMAGE_WIDTH * 2),
dtype = differenceImage.dtype)
afterDifference[:]=Setting.DefineManager.SET_IMAGE_BLACK_COLOR
afterDifference[Setting.DefineManager.ADD_IMAGE_HEIGHT + height + 15:,
Setting.DefineManager.ADD_IMAGE_WIDTH:Setting.DefineManager.ADD_IMAGE_WIDTH + width] = Setting.DefineManager.SET_IMAGE_WHITE_COLOR
afterDifference[Setting.DefineManager.ADD_IMAGE_HEIGHT:Setting.DefineManager.ADD_IMAGE_HEIGHT + height,
Setting.DefineManager.ADD_IMAGE_WIDTH:Setting.DefineManager.ADD_IMAGE_WIDTH + width] = differenceImage[:]
beforeDifference = np.ndarray(afterDifference.shape)
alpha = 10
while True:
kernel = np.ones((Setting.DefineManager.MORPHOLOGY_MASK_SIZE + alpha,Setting.DefineManager.MORPHOLOGY_MASK_SIZE + alpha), np.uint8)
beforeDifference = np.copy(afterDifference)
afterDifference = cv2.morphologyEx(afterDifference, cv2.MORPH_CLOSE, kernel)
afterDifference = cv2.GaussianBlur(afterDifference, (Setting.DefineManager.WIDTH_MASK_SIZE
, Setting.DefineManager.HEIGHT_MASK_SIZE), 0)
thresh, afterDifference = cv2.threshold(afterDifference, Setting.DefineManager.THRESHOLD
, Setting.DefineManager.SET_IMAGE_WHITE_COLOR, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
contourLength = len(GetContour(afterDifference)[0])
ccv.ShowImagesWithName([beforeDifference,afterDifference],[],700)
if contourLength < Setting.DefineManager.END_CONTOUR_COUNT:
break
afterDifference = afterDifference[Setting.DefineManager.ADD_IMAGE_HEIGHT:Setting.DefineManager.ADD_IMAGE_HEIGHT + height,
Setting.DefineManager.ADD_IMAGE_WIDTH:Setting.DefineManager.ADD_IMAGE_WIDTH + width]
finalDifference = cv2.absdiff(differenceImage, afterDifference)
ccv.ShowImagesWithName([differenceImage, afterDifference, finalDifference],['Before','After', 'Added'])
return afterDifference
def BodyLineDraw(bodyHeight, navelPoint, faceRate, image):
drawImage = np.copy(image)
imageHeight, imageWidth = drawImage.shape[:2]
ratioLength = int(bodyHeight * faceRate)
eighthRatioLength = int(bodyHeight * DefineManager.EIGHT_RATIO)
cv2.line(drawImage, (navelPoint[0], 0), (navelPoint[0], imageHeight),
DefineManager.RGB_COLOR_GREEN, 1)
# 배꼽 세로 선
cv2.line(drawImage, (0, navelPoint[1]), (imageWidth, navelPoint[1]),
DefineManager.RGB_COLOR_GREEN, 1)
# 배꼼 가로선
cv2.line(drawImage, (navelPoint[0] - eighthRatioLength, 0),
(navelPoint[0] - eighthRatioLength, imageHeight),
DefineManager.RGB_COLOR_GREEN, 1)
# 왼쪽 어깨선
cv2.line(drawImage, (navelPoint[0] + eighthRatioLength, 0),
(navelPoint[0] + eighthRatioLength, imageHeight),
DefineManager.RGB_COLOR_GREEN, 1)
# 오른쪽 어깨선
cv2.line(drawImage, (0, navelPoint[1] + ratioLength),
(imageWidth, navelPoint[1] + ratioLength),
DefineManager.RGB_COLOR_GREEN, 1)
# 사타구니 선
cv2.line(drawImage, (0, navelPoint[1] - ratioLength),
(imageWidth, navelPoint[1] - ratioLength),
DefineManager.RGB_COLOR_GREEN, 1)
# 가슴선
CustomOpenCV.ShowImagesWithName([drawImage])
def DrawPointToImage(positionData, imageData):
print "DrawPointToImage"
drawImage = np.copy(imageData)
gaussianImage = np.copy(imageData)
gaussianImage[:] = 0
height, width = drawImage.shape[:2]
index = 0
for eachPosition in positionData:
if eachPosition[
DefineManager.X_POSITION_SAVE_POINT] < 0 or eachPosition[
DefineManager.Y_POSITION_SAVE_POINT] < 0:
continue
if eachPosition[
DefineManager.X_POSITION_SAVE_POINT] >= width or eachPosition[
DefineManager.Y_POSITION_SAVE_POINT] >= height:
continue
cv2.circle(imageData,
(int(eachPosition[DefineManager.X_POSITION_SAVE_POINT]),
int(eachPosition[DefineManager.Y_POSITION_SAVE_POINT])), 2,
DefineManager.RGB_COLOR_RED, -1)
cv2.circle(gaussianImage,
(int(eachPosition[DefineManager.X_POSITION_SAVE_POINT]),
int(eachPosition[DefineManager.Y_POSITION_SAVE_POINT])), 2,
DefineManager.RGB_COLOR_WHITE, -1)
cv2.putText(imageData, str(index),
(int(eachPosition[DefineManager.X_POSITION_SAVE_POINT]),
int(eachPosition[DefineManager.Y_POSITION_SAVE_POINT])),
cv2.FONT_HERSHEY_COMPLEX, 0.3,
DefineManager.RGB_COLOR_WHITE)
index = index + 1
CustomOpenCV.ShowImagesWithName([imageData])
def DetectBlackBoardContourFromOriginImage(targetGrayImage):
targetEqualizeGrayImage = GetContour.GetMeanRateImage(targetGrayImage)
morpholgyKernel = np.ones((Setting.DefineManager.MORPHOLOGY_MASK_SIZE,
Setting.DefineManager.MORPHOLOGY_MASK_SIZE),
np.uint8)
targetMorphologyGrayImage = cv2.morphologyEx(targetEqualizeGrayImage,
cv2.MORPH_OPEN,
morpholgyKernel)
CustomOpenCV.ShowImagesWithName(
[CustomOpenCV.ResizeImageAsRate(targetMorphologyGrayImage, 0.5)],
["targetEdgeMorphologyGrayImage"])
# Reduce image noise
targetMorphologyGrayImage = cv2.adaptiveThreshold(
targetMorphologyGrayImage, Setting.DefineManager.SET_IMAGE_WHITE_COLOR,
cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,
Setting.DefineManager.NEIGHBORHOOD_MASK_SIZE, 10)
# Get small size of block's threshold value
targetEdgeMorphologyGrayImage = cv2.Canny(
targetMorphologyGrayImage,
Setting.DefineManager.CANNY_MINIMUM_THRESHOLD,
Setting.DefineManager.CANNY_MAXIMUM_THRESHOLD,
apertureSize=5)
CustomOpenCV.ShowImagesWithName(
[CustomOpenCV.ResizeImageAsRate(targetEdgeMorphologyGrayImage, 0.5)],
["targetEdgeMorphologyGrayImage"])
# Edge detect from bulr processed image
(_, beforeEdgeGrayImageContour,
h) = cv2.findContours(targetEdgeMorphologyGrayImage, cv2.RETR_LIST,
cv2.CHAIN_APPROX_SIMPLE)
# Get image contour
foundedMaxAreaSizeContours = sorted(
beforeEdgeGrayImageContour, key=cv2.contourArea,
reverse=True)[:Setting.DefineManager.GET_MAXIMUM_AREA_SIZE]
return FindSquareObjectFromContourData(foundedMaxAreaSizeContours)
def AngleAsDealWithPointFromContours(contours, drawImage):
pointAngle = []
for contourIndex in contours:
length = len(contourIndex)
strideKey = max(length / Setting.DefineManager.RESEARCH_ANGLE_COUNT,Setting.DefineManager.MINIMUM_STRIDE_KEY)
beforeAngle = 0.0
for index in range(int(length/strideKey) + 1):
pointA = contourIndex[((index-1) * strideKey)%length].ravel()
pointB = contourIndex[((index) * strideKey)%length].ravel()
pointC = contourIndex[((index+1) * strideKey)%length].ravel()
x, y = pointB.ravel()
cv2.circle(drawImage, (x,y), 2, Setting.DefineManager.RGB_COLOR_BLUE, -1)
nowAngle = AngleBetweenThreePoints(pointA,pointB,pointC)
absAngle = abs(beforeAngle - nowAngle)
if absAngle > Setting.DefineManager.ANGLE_AS_DEAL_WITH_POINT :
pointAngle.append(np.asarray([pointB]))
angleText = str(int(nowAngle)) + "," + str(int(absAngle))
thickness = 0.3
cv2.circle(drawImage, (x,y), 2, Setting.DefineManager.RGB_COLOR_RED, -1)
cv2.putText(drawImage, angleText,(x,y),0, thickness,Setting.DefineManager.RGB_COLOR_WHITE)
beforeAngle = nowAngle
ccv.ShowImagesWithName([drawImage],['PointImage'])
return pointAngle
def AngleAsDealWithPointFromContours(contours, drawImage):
pointAngle = []
union = []
contourIndex = contours[0]
length = len(contourIndex)
strideKey = Setting.DefineManager.MINIMUM_STRIDE_KEY
beforeAngle = 0.0
for index in range(int(length / strideKey)):
indexA = (index - 1) * strideKey
indexB = (index) * strideKey
indexC = (index + 1) * strideKey
if indexA < indexB:
for pointIndex in range(indexA, indexB):
union.append(contourIndex[pointIndex % length].ravel())
pointA = contourIndex[indexA % length].ravel()
pointB = contourIndex[indexB % length].ravel()
pointC = contourIndex[indexC % length].ravel()
x, y = pointB.ravel()
cv2.circle(drawImage, (x, y), 2, Setting.DefineManager.RGB_COLOR_BLUE,
-1)
nowAngle = AngleBetweenThreePoints(pointA, pointB, pointC)
absAngle = abs(beforeAngle - nowAngle)
if absAngle > Setting.DefineManager.ANGLE_AS_DEAL_WITH_POINT:
union.append(pointB)
pointAngle.append(union)
union = []
angleText = str(int(nowAngle)) + "," + str(int(absAngle))
thickness = 0.3
cv2.circle(drawImage, (x, y), 2,
Setting.DefineManager.RGB_COLOR_RED, -1)
cv2.putText(drawImage, angleText, (x, y), 0, thickness,
Setting.DefineManager.RGB_COLOR_WHITE)
beforeAngle = nowAngle
pointAngle.append(union)
ccv.ShowImagesWithName([drawImage], ['PointImage'])
return pointAngle
def DetectObjectFromImage(beforeImage, afterImage, beforeGrayImage,
afterGrayImage):
resizeRate = GetContour.SquareDetectAndReturnRateAsSquare(beforeGrayImage)
beforeImage = CustomOpenCV.ResizeImageAsRate(beforeImage, resizeRate)
beforeGrayImage = CustomOpenCV.ResizeImageAsRate(beforeGrayImage,
resizeRate)
afterImage = CustomOpenCV.ResizeImageAsRate(afterImage, resizeRate)
afterGrayImage = CustomOpenCV.ResizeImageAsRate(afterGrayImage, resizeRate)
squareContourData = DetectBackgroundSquare.DetectBackgroundSquareFromImage(
beforeImage) #형광색 인식으로 점 4개 찾는 함수
#squareContourData = DetectBlackBoardContourFromOriginImage(beforeGrayImage)
# 굴곡진 큰 사각형 정사각형으로 보정
perspectiveUpdatedBeforeImage = ImageMatrixMove.ImageMatrixMove(
beforeImage, squareContourData)
perspectiveUpdatedAfterImage = ImageMatrixMove.ImageMatrixMove(
afterImage, squareContourData)
perspectiveUpdatedBeforeImage = CustomOpenCV.ResizeImageAsWidth(
perspectiveUpdatedBeforeImage, DefineManager.IMAGE_WIDTH)
perspectiveUpdatedAfterImage = CustomOpenCV.ResizeImageAsWidth(
perspectiveUpdatedAfterImage, DefineManager.IMAGE_WIDTH)
# Resize image as shape [ rateHeight, DefineManager.IMAGE_WIDTH ]
#CustomOpenCV.ShowImagesWithName([perspectiveUpdatedBeforeImage, perspectiveUpdatedAfterImage],
# ["perspectiveUpdatedBeforeImage", "perspectiveUpdatedAfterImage"])
perspectiveUpdatedBeforeGrayImage = cv2.cvtColor(
perspectiveUpdatedBeforeImage, cv2.COLOR_BGR2GRAY)
perspectiveUpdatedAfterGrayImage = cv2.cvtColor(
perspectiveUpdatedAfterImage, cv2.COLOR_BGR2GRAY)
morphologyKernel = np.ones(
(Setting.DefineManager.MORPHOLOGY_MASK_SIZE + 1,
Setting.DefineManager.MORPHOLOGY_MASK_SIZE + 1), np.uint8)
perspectiveUpdatedBeforeMorphologyGrayImage = cv2.morphologyEx(
perspectiveUpdatedBeforeGrayImage, cv2.MORPH_OPEN, morphologyKernel)
perspectiveUpdatedAfterMorphologyGrayImage = cv2.morphologyEx(
perspectiveUpdatedAfterGrayImage, cv2.MORPH_OPEN, morphologyKernel)
# Reduce image noise
beforeThresholdedBlackBoardImage = cv2.adaptiveThreshold(
perspectiveUpdatedBeforeMorphologyGrayImage,
Setting.DefineManager.SET_IMAGE_WHITE_COLOR,
cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,
Setting.DefineManager.NEIGHBORHOOD_MASK_SIZE, 10)
afterThresholdedBlackBoardImage = cv2.adaptiveThreshold(
perspectiveUpdatedAfterMorphologyGrayImage,
Setting.DefineManager.SET_IMAGE_WHITE_COLOR,
cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,
Setting.DefineManager.NEIGHBORHOOD_MASK_SIZE, 10)
# Adaptive Threshold Image
#CustomOpenCV.ShowImagesWithName([beforeThresholdedBlackBoardImage, afterThresholdedBlackBoardImage], ['beforeThresholdedBlackBoardImage', 'afterThresholdedBlackBoardImage'])
differenceBasedOnThreshImage = cv2.absdiff(
beforeThresholdedBlackBoardImage, afterThresholdedBlackBoardImage)
differenceBasedOnThreshImage[
differenceBasedOnThreshImage > Setting.DefineManager.
EACH_IMAGE_DIFFERENCE_THRESHOLD] = Setting.DefineManager.SET_IMAGE_WHITE_COLOR
# Detect each image difference from Threshold Image
#CustomOpenCV.ShowImagesWithName([differenceBasedOnThreshImage], ["differenceBasedOnThreshImage"])
objectFoundedImage = GetContour.GetObjectImage(
perspectiveUpdatedBeforeImage, perspectiveUpdatedAfterImage)
humanDetectedContour, contourLineDrawImage = GetContour.GetContour(
objectFoundedImage, perspectiveUpdatedAfterImage)
GetContour.FindNavel(humanDetectedContour, contourLineDrawImage)
importantPoint = GetContour.AngleAsDealWithPointFromContours(
humanDetectedContour, contourLineDrawImage)
return [
beforeThresholdedBlackBoardImage, afterThresholdedBlackBoardImage,
differenceBasedOnThreshImage, humanDetectedContour
]
def DetectObjectFromImage(beforeImage, afterImage, beforeGrayImage,
afterGrayImage):
resizeRate = GetContour.SquareDetectAndReturnRateAsSquare(beforeGrayImage)
beforeImage = CustomOpenCV.ResizeImageAsRate(beforeImage, resizeRate)
beforeGrayImage = CustomOpenCV.ResizeImageAsRate(beforeGrayImage,
resizeRate)
afterImage = CustomOpenCV.ResizeImageAsRate(afterImage, resizeRate)
afterGrayImage = CustomOpenCV.ResizeImageAsRate(afterGrayImage, resizeRate)
#squareContourData = DetectBackgroundSquare.DetectBackgroundSquareFromImage(beforeImage) #형광색 인식으로 점 4개 찾는 함수
# in mac
# this function is not working and falling loop.
squareContourData = DetectBlackBoardContourFromOriginImage(beforeGrayImage)
# 굴곡진 큰 사각형 정사각형으로 보정
perspectiveUpdatedBeforeImage = ImageMatrixMove.ImageMatrixMove(
beforeImage, squareContourData)
perspectiveUpdatedAfterImage = ImageMatrixMove.ImageMatrixMove(
afterImage, squareContourData)
perspectiveUpdatedBeforeImage = CustomOpenCV.ResizeImageAsWidth(
perspectiveUpdatedBeforeImage, DefineManager.IMAGE_WIDTH)
perspectiveUpdatedAfterImage = CustomOpenCV.ResizeImageAsWidth(
perspectiveUpdatedAfterImage, DefineManager.IMAGE_WIDTH)
# Resize image as shape [ rateHeight, DefineManager.IMAGE_WIDTH ]
#CustomOpenCV.ShowImagesWithName([perspectiveUpdatedBeforeImage, perspectiveUpdatedAfterImage],
# ["perspectiveUpdatedBeforeImage", "perspectiveUpdatedAfterImage"])
perspectiveUpdatedBeforeGrayImage = cv2.cvtColor(
perspectiveUpdatedBeforeImage, cv2.COLOR_BGR2GRAY)
perspectiveUpdatedAfterGrayImage = cv2.cvtColor(
perspectiveUpdatedAfterImage, cv2.COLOR_BGR2GRAY)
morphologyKernel = np.ones(
(Setting.DefineManager.MORPHOLOGY_MASK_SIZE + 1,
Setting.DefineManager.MORPHOLOGY_MASK_SIZE + 1), np.uint8)
perspectiveUpdatedBeforeMorphologyGrayImage = cv2.morphologyEx(
perspectiveUpdatedBeforeGrayImage, cv2.MORPH_OPEN, morphologyKernel)
perspectiveUpdatedAfterMorphologyGrayImage = cv2.morphologyEx(
perspectiveUpdatedAfterGrayImage, cv2.MORPH_OPEN, morphologyKernel)
# Reduce image noise
beforeThresholdedBlackBoardImage = cv2.adaptiveThreshold(
perspectiveUpdatedBeforeMorphologyGrayImage,
Setting.DefineManager.SET_IMAGE_WHITE_COLOR,
cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,
Setting.DefineManager.NEIGHBORHOOD_MASK_SIZE, 10)
afterThresholdedBlackBoardImage = cv2.adaptiveThreshold(
perspectiveUpdatedAfterMorphologyGrayImage,
Setting.DefineManager.SET_IMAGE_WHITE_COLOR,
cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,
Setting.DefineManager.NEIGHBORHOOD_MASK_SIZE, 10)
# Adaptive Threshold Image
#CustomOpenCV.ShowImagesWithName([beforeThresholdedBlackBoardImage, afterThresholdedBlackBoardImage], ['beforeThresholdedBlackBoardImage', 'afterThresholdedBlackBoardImage'])
differenceBasedOnThreshImage = cv2.absdiff(
beforeThresholdedBlackBoardImage, afterThresholdedBlackBoardImage)
differenceBasedOnThreshImage[
differenceBasedOnThreshImage > Setting.DefineManager.
EACH_IMAGE_DIFFERENCE_THRESHOLD] = Setting.DefineManager.SET_IMAGE_WHITE_COLOR
# Detect each image difference from Threshold Image
#CustomOpenCV.ShowImagesWithName([differenceBasedOnThreshImage], ["differenceBasedOnThreshImage"])
objectFoundedImage = GetContour.GetObjectImage(
perspectiveUpdatedBeforeImage, perspectiveUpdatedAfterImage)
humanDetectedContour, contourLineDrawImage = GetContour.GetContour(
objectFoundedImage, perspectiveUpdatedAfterImage)
faceMinY, faceMaxY = GetContour.DetectFaceAndGetY(
perspectiveUpdatedAfterImage)
navelPoint, faceRate, maxY, minY = GetContour.FindNavel(
humanDetectedContour, faceMaxY, contourLineDrawImage)
height = maxY - minY
importantPoint = GetContour.AngleAsDealWithPointFromContours(
humanDetectedContour, contourLineDrawImage)
beforeDrawImage = np.copy(perspectiveUpdatedBeforeImage)
afterDrawImage = np.copy(perspectiveUpdatedAfterImage)
functionParameter = []
for index in range(len(importantPoint)):
xArray = []
yArray = []
for point in importantPoint[index]:
x, y = point.ravel()
xArray.append(x)
yArray.append(y)
xArray = np.asarray(xArray)
yArray = np.asarray(yArray)
if xArray.shape[0] > 0:
# ax + b = y (a, b 를 받아옴)
functionCharacteristic = sp.polyfit(
xArray, yArray, DefineManager.FUNCTION_DIMENSION)
functionParameter.append(functionCharacteristic)
yRegressionArray = sp.polyval(functionCharacteristic, xArray)
err = np.sqrt(
sum((yArray - yRegressionArray)**2) / yArray.shape[0])
pointA, pointB = GetContour.GetStartAndEndPointsFromLine(
functionCharacteristic, xArray)
cv2.line(beforeDrawImage, pointA, pointB,
DefineManager.RGB_COLOR_GREEN, 1)
cv2.line(afterDrawImage, pointA, pointB,
DefineManager.RGB_COLOR_GREEN, 1)
CustomOpenCV.ShowImagesWithName([beforeDrawImage, afterDrawImage])
return [
perspectiveUpdatedBeforeImage, perspectiveUpdatedAfterImage, height,
navelPoint, humanDetectedContour, functionParameter, beforeDrawImage,
faceRate
]