def Detect(Feature_Manager):
global make_dir_root, timestr, DManager
DManager = Feature_Manager
make_dir_root = Feature_Manager._RootDirectory
image = Feature_Manager._ImageCleaned.copy()
LineSegmentsFeature.Initialize(image)
cornerPts, cornerImageOutput, extractedLinesP, houghlineImageOutput = LineSegmentsFeature.EntityDetection()
uniqueLines = LineSegmentsFeature.SegmentCreator(extractedLinesP)
segLines = LineSegmentsFeature.SeggeratedCreator(uniqueLines)
LineSegmentsFeature.cornerOnSegLine(cornerPts, segLines)
detectedLineSegments = LineSegmentsFeature.DetectLineSegments(segLines)
Segments = Cognition.MergeLineSegments(detectedLineSegments)
LineImg = LineSegmentsFeature.DrawLines(Segments)
LineSegmentsFeature.DisplayOutputs()
return Segments, LineImg
def Extract_Text(img, cnts):
global DimensioanlLines
i = 0
ExtractedTextArea = []
RotatedText = []
for c in cnts:
(x, y, w, h) = cv2.boundingRect(c)
ar = w / float(h)
crWidth = w / float(img.shape[1])
area = cv2.contourArea(c)
if h > 5 and w > 4 and ar > 0.4 and 0.5 > crWidth > 0.001 and area > 20:
roi = img[y:y + h + 1, x:x + w + 1].copy()
Rotate_roi = img[y:y + h + 5, x:x + w + 5].copy()
cv2.imwrite(make_dir_roi + "/segmentedtext" + str(i) + ".png",
roi)
BB = [x, y, w, h]
new_img = TextsFeature.Paste(img, roi)
OrientationAngle = ((Cognition.GetOrientation(
DimensioanlLines, BB)))
output_img_path, detected_text = TextsFeature.RotateByAngle(
new_img, OrientationAngle, make_dir_rotate, i)
p1 = Point2(x - 2, y - 2)
p2 = Point2(x + w + 2, y + h + 2)
DimText = DimensionalTexts()
DimText.ExtractDimensionalText(DimText, detected_text, p1, p2,
OrientationAngle)
ExtractedTextArea.append(DimText)
i += 1
return ExtractedTextArea, RotatedText
def CheckArrowOverlapBetweenTwo(a1, a2):
if a1._ArrowCenter.x != a2._ArrowCenter.x or a1._ArrowCenter.y != a2._ArrowCenter.y:
overlap = Cognition.CheckOverlapByLineSegment(
a1._BoundingBoxP1, a1._BoundingBoxP2, a2._BoundingBoxP1,
a2._BoundingBoxP2)
if overlap == True:
return True
return False
def CheckArrowOverlap(arrowHead):
global ArrowHeadsList
for a in ArrowHeadsList:
if fabs(arrowHead._ArrowCenter.x - a._ArrowCenter.x) > 1 or fabs(
arrowHead._ArrowCenter.y != a._ArrowCenter.y) > 1:
overlap = Cognition.CheckOverlapByLineSegment(
arrowHead._BoundingBoxP1, arrowHead._BoundingBoxP2,
a._BoundingBoxP1, a._BoundingBoxP2)
if overlap == True:
return True
return False
def Detect(Feature_Manager):
lines = Feature_Manager._DetectedLine
dimension = Feature_Manager._DetectedDimension
supportLinesegments = []
entityLinesegments = []
dist_Img = Cognition.DistanceTransform(Feature_Manager._ImageCleaned)
minVal, maxVal, minLoc, maxLoc = cv2.minMaxLoc(dist_Img)
for l in lines:
for seg in l:
PointsBetweenLine = SpecialLineSegments.PixelScanner(
seg.startPoint, seg.endPoint, dist_Img)
sLinesPoints = []
eLinePoints = []
for i in PointsBetweenLine:
t = Cognition.CheckThicknessInVicinity(
i[0], i[1], dist_Img)
pt = Point2(i[0], i[1])
if t is None:
continue
if t <= 0.6 * maxVal:
sLinesPoints.append(pt)
else:
eLinePoints.append(pt)
sortSuppPts = sLinesPoints
sortEntPts = eLinePoints
if (len(sortSuppPts) > 1):
startsupportPt = sortSuppPts[0]
for i in range(0, len(sortSuppPts) - 1):
p1 = sortSuppPts[i]
p2 = sortSuppPts[i + 1]
dist = p1.DistanceTo(p2)
if dist > 30:
Supportlinesegment = Line2(startsupportPt, p1)
supportLinesegments.append(Supportlinesegment)
startsupportPt = p2
Supportlinesegment = Line2(startsupportPt, p2)
supportLinesegments.append(Supportlinesegment)
if (len(sortEntPts) > 1):
startentityPt = sortEntPts[0]
elines = []
for i in range(0, len(sortEntPts) - 1):
eline = []
p1 = sortEntPts[i]
p2 = sortEntPts[i + 1]
dist = p1.DistanceTo(p2)
if dist > 2:
entitylinesegment = Line2(startentityPt, p1)
eline.append(entitylinesegment)
entityLinesegments.append(eline)
startentityPt = p2
entitylinesegment = Line2(startentityPt, p2)
elines.append(entitylinesegment)
entityLinesegments.append(elines)
for d in dimension:
SupportL = []
for a in d._DimensionalLines._ArrowHeads:
BB = Cognition.SortCoordinates(
[a._BoundingBoxP1, a._BoundingBoxP2])
bbMin = BB[0]
bbMax = BB[1]
direction = a._Direction
if direction == "West":
shortListedLines = []
SupportLSW = []
for ls in supportLinesegments:
if bbMin.x + 3 > ls.startPoint.x and fabs(
ls.endPoint.x - ls.startPoint.x) < 3 and fabs(
ls.endPoint.y - ls.startPoint.y) > 5:
shortListedLines.append(ls)
for ls in shortListedLines:
projectedPt = MathUtils.ProjectToLine2(
ls.startPoint, ls.endPoint, bbMin)
projectedDistance = bbMin.DistanceTo(projectedPt)
if projectedDistance < 8: #<7
SupportLSW.append(ls)
SupportL.append(SupportLSW)
elif direction == "East":
shortListedLines = []
SupportLSE = []
for ls in supportLinesegments:
if bbMax.x - 3 < ls.startPoint.x and fabs(
ls.endPoint.x - ls.startPoint.x) < 3 and fabs(
ls.endPoint.y - ls.startPoint.y) > 5:
shortListedLines.append(ls)
for ls in shortListedLines:
projectedPt = MathUtils.ProjectToLine2(
ls.startPoint, ls.endPoint, bbMax)
projectedDistance = bbMax.DistanceTo(projectedPt)
if projectedDistance < 8:
SupportLSE.append(ls)
SupportL.append(SupportLSE)
elif direction == "North":
shortListedLines = []
SupportLSN = []
for ls in supportLinesegments:
if bbMin.y + 3 > ls.startPoint.y and fabs(
ls.endPoint.y - ls.startPoint.y) < 3 and fabs(
ls.endPoint.x - ls.startPoint.x) > 5:
shortListedLines.append(ls)
for ls in shortListedLines:
projectedPt = MathUtils.ProjectToLine2(
ls.startPoint, ls.endPoint, bbMin)
projectedDistance = bbMin.DistanceTo(projectedPt)
if projectedDistance < 8:
SupportLSN.append(ls)
SupportL.append(SupportLSN)
elif direction == "South":
SupportLSS = []
shortListedLines = []
for ls in supportLinesegments:
if bbMax.y - 3 < ls.startPoint.y and fabs(
ls.endPoint.y - ls.startPoint.y) < 3 and fabs(
ls.endPoint.x - ls.startPoint.x) > 5:
shortListedLines.append(ls)
for ls in shortListedLines:
projectedPt = MathUtils.ProjectToLine2(
ls.startPoint, ls.endPoint, bbMax)
projectedDistance = bbMax.DistanceTo(projectedPt)
if projectedDistance < 8:
SupportLSS.append(ls)
SupportL.append(SupportLSS)
d._SupportLines = SupportL
Feature_Manager._DetectedLine = entityLinesegments
def main(argv1):
img_path = argv1
#img_path = "..\\TestData\\1.png"
img_path = os.path.abspath(img_path)
dir = os.path.dirname(img_path)
os.chdir(dir)
currentDir = os.getcwd()
from Core.Features.Texts.TextsFeature import TextsFeature
from Core.Features.Arrowheads.ArrowHeadsFeature import ArrowHeadsFeature
from Core.Features.Circles.CirclesFeature import CirclesFeature
from Core.Features.LineSegments.LineSegmentsFeature import LineSegmentsFeature
from Core.Features.Cognition.DimensionalLinesFeature import DimensionalLinesFeature
from Core.Features.Cognition.Cognition import Cognition
from Core.Features.Cognition.SupportLinesFeature import SupportLinesFeature
from Core.Features.FeatureManager import FeatureManager
from Core.Utils.Eraser import Eraser
from Core.Utils.I2CWriter import I2CWriter
from Core.Utils.DXFWriter import DXFWriter
timestr = time.strftime("%Y%m%d-%H%M%S")
Start_time = time.strftime("%H hr - %M min - %S sec")
print("Image2CAD Script Started at " + Start_time + "...")
base = os.path.basename(img_path)
folder_name = os.path.splitext(base)[0]
print("Image Loaded: " + img_path + "...")
print("Making Required Directory...")
make_dir_Output = r"./Output"
if not os.path.exists(make_dir_Output):
os.mkdir(make_dir_Output)
make_dir_folder = r"./Output/" + folder_name
make_dir_root = r"./Output/" + folder_name + r"/" + timestr
if not os.path.exists(make_dir_folder):
os.mkdir(make_dir_folder)
os.mkdir(make_dir_root)
print("Initializing Feature Manager...")
FM = FeatureManager()
FM._ImagePath = img_path
FM._RootDirectory = make_dir_root
img = cv2.imread(FM._ImagePath)
FM._ImageOriginal = img
FM._ImageCleaned = img.copy()
FM._ImageDetectedDimensionalText = img.copy()
FM._ImageDetectedCircle = img.copy()
Erased_Img = img.copy()
AD_Time = time.strftime("%H hr - %M min - %S sec")
print("Arrow Detection Started at " + AD_Time + "...")
BB_Arrows, Arrow_Img = ArrowHeadsFeature.Detect(FM)
FM._DetectedArrowHead = BB_Arrows
FM._ImageDetectedArrow = Arrow_Img
print("Arrow Detection Complete...")
cv2.imshow("Detected Arrows", FM._ImageDetectedArrow)
cv2.waitKey(0)
for i in BB_Arrows:
P1 = i._BoundingBoxP1
P2 = i._BoundingBoxP2
Erased_Img = Eraser.EraseBox(FM._ImageCleaned, P1, P2)
FM._ImageCleaned = Erased_Img
DL_Time = time.strftime("%H hr - %M min - %S sec")
print("Dimensional Line Detection Started at " + DL_Time + "...")
segments, DimensionalLine_Img = DimensionalLinesFeature.Detect(FM)
FM._ImageDetectedDimensionalLine = DimensionalLine_Img
FM._DetectedDimensionalLine = segments
print("Dimensional Line Detection Complete...")
cv2.imshow("Detected Dimensional Lines", FM._ImageDetectedDimensionalLine)
cv2.waitKey(0)
for j in segments:
for i in j._Leaders:
P1 = i.startPoint
P2 = i.endPoint
Erased_Img = Eraser.EraseLine(FM._ImageCleaned, P1, P2)
FM._ImageCleaned = Erased_Img
print("Correlating ArrowHead Direction...")
Cognition.ArrowHeadDirection(FM)
print("Correlating ArrowHead Direction Complete...")
TE_Time = time.strftime("%H hr - %M min - %S sec")
print("Text Area Extraction Started at " + TE_Time + "...")
ExtractedTextArea, TextArea_Img = TextsFeature.Detect(FM)
FM._ImageDetectedDimensionalText = TextArea_Img
FM._DetectedDimensionalText = ExtractedTextArea
print("Text Area Extraction Complete...")
cv2.imshow("Detected Text Area", FM._ImageDetectedDimensionalText)
cv2.waitKey(0)
for i in ExtractedTextArea:
P1 = i._TextBoxP1
P2 = i._TextBoxP2
Erased_Img = Eraser.EraseBox(FM._ImageCleaned, P1, P2)
FM._ImageCleaned = Erased_Img
DC_Time = time.strftime("%H hr - %M min - %S sec")
print("Correlation of Dimensions Started at " + DC_Time + "...")
Dimension_correlate = Cognition.ProximityCorrelation(FM)
FM._DetectedDimension = Dimension_correlate
print("Correlation of Dimensions complete...")
LD_Time = time.strftime("%H hr - %M min - %S sec")
print("Line Detection Started at " + LD_Time + "...")
segments, DetectedLine_Img = LineSegmentsFeature.Detect(FM)
FM._DetectedLine = segments
FM._ImageDetectedLine = DetectedLine_Img
print("Line Detection Complete...")
cv2.imshow("Detected Lines", FM._ImageDetectedLine)
cv2.waitKey(0)
print("Correlation of Support Lines Started...")
SupportLinesFeature.Detect(FM)
print("Correlation of Support Lines Complete...")
print("Correction of Broken Ends Stage 1 Started...")
Cognition.CorrectEnds(FM)
print("Correction of Broken Ends Stage 1 Complete...")
print("Correction of Broken Ends Stage 2 Started...")
Cognition.JoinLineSegmentsWithinProximityTolerance(FM)
print("Correction of Broken Ends Stage 2 Complete...")
for i in segments:
for ls in i:
P1 = ls.startPoint
P2 = ls.endPoint
Erased_Img = Eraser.EraseLine(FM._ImageCleaned, P1, P2)
FM._ImageCleaned = Erased_Img
print("Entity Correlation Started...")
Cognition.EntityCorrelation(FM)
print("Entity Correlation Complete...")
CD_Time = time.strftime("%H hr - %M min - %S sec")
print("Circle Detection Started at " + CD_Time + "...")
detectedcircle, DetectedCircle_Img = CirclesFeature.Detect(FM)
FM._ImageDetectedCircle = DetectedCircle_Img
FM._DetectedCircle = detectedcircle
print("Circle Detection Complete...")
cv2.imshow("Detected circles", FM._ImageDetectedCircle)
cv2.waitKey(0)
for i in detectedcircle:
center = i._centre
radius = i._radius
Erased_Img = Eraser.EraseCircle(FM._ImageCleaned, center, radius)
FM._ImageCleaned = Erased_Img
print("Exporting Extracted Data to I2C File...")
I2CWriter.Write(FM)
print("Exporting Complete...")
print("Exporting Extracted Data to DXF File...")
DXFWriter.Write(FM)
print("Exporting Complete...")
print("Image2CAD Script Execution Complete...")