def main2D_3D_2D_LR_Hair():
'''1. read origin obj and image'''
objPath = '../../github/vrn-07231340/obj/trump-12.obj'
objLines, vLines, fLines = readObj(objPath)
imgPath = '../../github/vrn-07231340/examples/scaled/trump-12.jpg'
img = cv2.imread(imgPath)
'''2. origin 2D landmark --> origin 3D landmark'''
''' BUT ONE 2D LANDMARK --> MORE THAN ONE 3D LANDMARK'''
''' HOW TO CHOOSE THE BEST ONE ?'''
''' OPTION 1: 选Z最大的3D landmark'''
'''2.1 origin 2D landmark [x, y]'''
originLandmark2DList = getLandmark2D(img)
'''2.2 origin 3D landmark list [[[x, y], [(line1, vLine1), (line2, vLine2)]], ... ]'''
originLandmark3DList = getLandmark3D(originLandmark2DList, vLines)
'''2.3 OPTION 1: 选Z最大的3D landmark'''
originLandmark3DList = optionChooseZMax(originLandmark3DList)
'''3. nod'''
nodAngle = 15
nodCenterMode = 'maxY'
nodObjLines = nod(objPath, nodAngle, nodCenterMode)
'''4. nod 3D landmark list'''
'''nodLandmark3DList: [[x0, y0], [x0, y0, z0], [x1, y1], [x1, y1, z1], (line, vLine)]'''
'''len(nodLandmark3DList): number of landmarks both on 2D and 3D'''
'''[x0, y0]: original landmark on 2D img'''
'''[x0, y0, z0]: original landmark on 3D model'''
'''[x1, y1]: nod landmark on 2D img'''
'''[x1, y1, z1]: nod landmark on 3D model'''
'''(line, vLine): the line(th) nod vLine'''
nodVLines = objLines2vLines(nodObjLines)
nodLandmark3DList = getNodLandmark3D(nodVLines, originLandmark3DList)
'''5. nod 3D landmark --> nod 2D landmark + 8 edge points'''
nodLandmark2D = []
for nodLandmark3D in nodLandmark3DList:
nodLandmark2D.append(nodLandmark3D[2])
nodLandmark2D = addEdgeLandmark(nodLandmark2D, img)
'''6. origin 2D landmarks + 8 edge points'''
originLandmark2D = []
for nodLandmark3D in nodLandmark3DList:
originLandmark2D.append((nodLandmark3D[0][0], nodLandmark3D[0][1]))
originLandmark2D = addEdgeLandmark(originLandmark2D, img)
assert len(originLandmark2D) == len(nodLandmark2D)
'''7. face 2D landmarks + hair 2D landmarks'''
# hairLandmark2DList, nodHairLandmark2DList = main2D_3D_2D_ManuallySelectHair()
hairLandmark2DList, nodHairLandmark2DList = main2D_3D_2D_LR_MeshHair()
'''7.1 origin face 2D landmarks + origin hair 2D landmarks'''
originLandmark2D = originLandmark2D+hairLandmark2DList
# drawPointsOnImg(originLandmark2D, img, 'g')
'''7.2 nod face 2D landmarks + nod hair 2D landmarks'''
nodLandmark2D = nodLandmark2D+nodHairLandmark2DList
# drawPointsOnImg(nodLandmark2D, img, 'r')
'''7.3 save origin and nod 2D landmarks txt'''
originLandmark2DTxtPath = './originLandmark2D.txt'
originLandmark2DTxt = open(originLandmark2DTxtPath, 'w')
for i in originLandmark2D:
originLandmark2DTxt.write('{} {}\n'.format(i[0], i[1]))
originLandmark2DTxt.close()
nodLandmark2DTxtPath = './nodLandmark2D.txt'
nodLandmark2DTxt = open(nodLandmark2DTxtPath, 'w')
for i in nodLandmark2D:
nodLandmark2DTxt.write('{} {}\n'.format(i[0], i[1]))
nodLandmark2DTxt.close()
'''8. delaunay triangle for [origin landmarks (face + hair)] + (eight edge points)'''
triList = generateTriList(originLandmark2D, img)
# print triList
'''8.1 save tri txt'''
triTxtPath = './nodTri.txt'
triTxt = open(triTxtPath, 'w')
for i in triList:
triTxt.write('{}\n'.format(i))
triTxt.close()
'''9. warp'''
imgMorph = morph_modify_for_2D3D2D_low_resolution(
originLandmark2D, nodLandmark2D, img, triList)
# imshow('imgMorph', imgMorph)
cv2.imwrite('./nod.jpg', imgMorph)
def main2D_3D_2D_LR_Hair():
'''1. read origin obj and image'''
objPath = '../../github/vrn-07231340/obj/trump-12.obj'
objLines, vLines, fLines = readObj(objPath)
imgPath = '../../github/vrn-07231340/examples/scaled/trump-12.jpg'
img = cv2.imread(imgPath)
imgHRPath = '../../github/vrn-07231340/examples/trump-12.jpg'
imgHR = cv2.imread(imgHRPath)
'''2. origin 2D landmark --> origin 3D landmark'''
''' BUT ONE 2D LANDMARK --> MORE THAN ONE 3D LANDMARK'''
''' HOW TO CHOOSE THE BEST ONE ?'''
''' OPTION 1: 选Z最大的3D landmark'''
'''2.1 origin 2D landmark [x, y]'''
originLandmark2DList = getLandmark2D(img)
'''2.2 origin 3D landmark list [[[x, y], [(line1, vLine1), (line2, vLine2)]], ... ]'''
originLandmark3DList = getLandmark3D(originLandmark2DList, vLines)
'''2.3 OPTION 1: 选Z最大的3D landmark'''
originLandmark3DList = optionChooseZMax(originLandmark3DList)
'''3. nod'''
nodAngle = 15
nodCenterMode = 'maxY'
nodObjLines = nod(objPath, nodAngle, nodCenterMode)
'''4. nod 3D landmark list'''
'''nodLandmark3DList: [[x0, y0], [x0, y0, z0], [x1, y1], [x1, y1, z1], (line, vLine)]'''
'''len(nodLandmark3DList): number of landmarks both on 2D and 3D'''
'''[x0, y0]: original landmark on 2D img'''
'''[x0, y0, z0]: original landmark on 3D model'''
'''[x1, y1]: nod landmark on 2D img'''
'''[x1, y1, z1]: nod landmark on 3D model'''
'''(line, vLine): the line(th) nod vLine'''
nodVLines = objLines2vLines(nodObjLines)
nodLandmark3DList = getNodLandmark3D(nodVLines, originLandmark3DList)
'''5. nod 3D landmark --> nod 2D landmark'''
nodLandmark2D = []
for nodLandmark3D in nodLandmark3DList:
nodLandmark2D.append(nodLandmark3D[2])
'''6. origin 2D landmarks'''
originLandmark2D = []
for nodLandmark3D in nodLandmark3DList:
originLandmark2D.append((nodLandmark3D[0][0], nodLandmark3D[0][1]))
assert len(originLandmark2D) == len(nodLandmark2D)
'''7. face 2D landmarks + hair 2D landmarks'''
# hairLandmark2DList, nodHairLandmark2DList = main2D_3D_2D_ManuallySelectHair()
hairLandmark2DList, nodHairLandmark2DList, edgePoints, ellipseVerts, outerEllipseVerts = main2D_3D_2D_LR_MeshHair(
)
assert len(hairLandmark2DList) == len(nodHairLandmark2DList)
'''7.1 origin face 2D landmarks + origin hair 2D landmarks'''
originLandmark2D = originLandmark2D + hairLandmark2DList
'''7.2 nod face 2D landmarks + nod hair 2D landmarks'''
nodLandmark2D = nodLandmark2D + nodHairLandmark2DList
'''7.3 save origin and nod 2D landmarks txt'''
# originLandmark2DTxtPath = './originLandmark2D.txt'
# originLandmark2DTxt = open(originLandmark2DTxtPath, 'w')
# for i in originLandmark2D:
# originLandmark2DTxt.write('{} {}\n'.format(i[0], i[1]))
# originLandmark2DTxt.close()
# nodLandmark2DTxtPath = './nodLandmark2D.txt'
# nodLandmark2DTxt = open(nodLandmark2DTxtPath, 'w')
# for i in nodLandmark2D:
# nodLandmark2DTxt.write('{} {}\n'.format(i[0], i[1]))
# nodLandmark2DTxt.close()
'''8. add edge points'''
'''8.1 OPTION1: 8 IMAGE EDGE POINTS'''
''' 如果在加头发关键点之前加8个edge points，第7个edge point（图像最上面那个）会被往下warp一点'''
''' 如果在加头发关键点之后加8个edge points，第7个edge point经过warp后仍在原处，形成一个小三角'''
# originLandmark2D = addEdgeLandmark(originLandmark2D, img)
# nodLandmark2D = addEdgeLandmark(nodLandmark2D, img)
'''8.2 OPTION2: OUTER ELLIPSE'''
# a = copy.copy(originLandmark2D)
originLandmark2D = originLandmark2D + edgePoints
nodLandmark2D = nodLandmark2D + edgePoints
# drawPointsOnImg(originLandmark2D, img, 'b')
# drawPointsOnImg(a, img, 'r')
# drawPointsOnImg(nodLandmark2D, img, 'g')
# drawPointsOnImg(ellipseVerts, img, 'g', cover=True)
# drawPointsOnImg(outerEllipseVerts, img, 'r', cover=True)
# drawPointsOnImg(originLandmark2D, img, 'g', cover=True)
# drawPointsOnImg(edgePoints, img, 'b', radius=3)
# drawPointsOnImg(nodLandmark2D, img, 'r')
'''9. delaunay triangle for [origin landmarks (face + hair)] + (eight edge points)'''
# triList = generateTriList(originLandmark2D, img)
# '''9.1 save tri txt'''
# triTxtPath = './nodTri.txt'
# triTxt = open(triTxtPath, 'w')
# for i in triList:
# triTxt.write('{}\n'.format(i))
# triTxt.close()
'''10. warp LR'''
# imgMorph = morph_modify_for_2D3D2D_low_resolution(
# originLandmark2D, nodLandmark2D, img, triList)
# imshow('imgMorph', imgMorph)
# cv2.imwrite('./nod.jpg', imgMorph)
# return originLandmark2D, nodLandmark2D, triList
'''LR to HR'''
originLandmark2DHR = LR2HR(img, imgHR, originLandmark2D)
for (x, y), (xmin, ymin) in zip(originLandmark2DHR, originLandmark2D):
if float(x) >= 640 or float(y) >= 640:
print(int(xmin), int(ymin))
cv2.circle(img, (int(xmin), int(ymin)), 3, (0, 255, 0), -1)
imshow('img', img)
nodLandmark2DHR = LR2HR(img, imgHR, nodLandmark2D)
'''8. add 8 egde points'''
# nodLandmark2DHR = addEdgeLandmark(nodLandmark2DHR, imgHR)
# originLandmark2DHR = addEdgeLandmark(originLandmark2DHR, imgHR)
# drawPointsOnImg(originLandmark2DHR, imgHR, 'g')
# drawPointsOnImg(nodLandmark2DHR, imgHR, 'r')
'''8.1 remove >= 640'''
originLandmark2DHR = [(i[0], i[1]) for i in originLandmark2DHR
if i[0] < imgHR.shape[0] and i[1] < imgHR.shape[1]]
nodLandmark2DHR = [(i[0], i[1]) for i in nodLandmark2DHR
if i[0] < imgHR.shape[0] and i[1] < imgHR.shape[1]]
'''9. delaunay triangle for [origin landmarks (face + hair)] + (edge points)'''
triList = generateTriList(originLandmark2DHR, imgHR)
'''9.1 save tri txt'''
triTxtPath = './nodTri.txt'
triTxt = open(triTxtPath, 'w')
for i in triList:
triTxt.write('{}\n'.format(i))
triTxt.close()
'''10. warp HR'''
imgMorph = morph_modify_for_2D3D2D_low_resolution(originLandmark2DHR,
nodLandmark2DHR, imgHR,
triList)
# imshow('imgMorph', imgMorph)
# cv2.imwrite('./nod.jpg', imgMorph)
return originLandmark2DHR, nodLandmark2DHR, triList
def main2D_3D_2D_HR_NodHair():
'''1. read origin obj and image'''
objPath = '../../github/vrn-07231340/obj/trump-12.obj'
objLines, vLines, fLines = readObj(objPath)
imgLRPath = '../../github/vrn-07231340/examples/scaled/trump-12.jpg'
imgLR = cv2.imread(imgLRPath)
imgHRPath = '../../github/vrn-07231340/examples/trump-12.jpg'
imgHR = cv2.imread(imgHRPath)
'''2. origin LR 2D landmark --> origin 3D landmark'''
'''2.1 origin LR 2D landmark list [x, y]'''
originLandmark2DLRList = getLandmark2D(imgLR)
'''2.2 origin 3D landmark list [[[x, y], [(line1, vLine1), (line2, vLine2)]], ... ]'''
originLandmark3DList = getLandmark3D(originLandmark2DLRList, vLines)
'''2.3 OPTION 1: 相同(x, y)的情况下，选z最大的3D landmark'''
originLandmark3DList = optionChooseZMax(originLandmark3DList)
'''3. 3D model nod'''
nodAngle = 10
nodCenterMode = 'maxY'
nodObjLines = nod(objPath, nodAngle, nodCenterMode)
'''4. nod 3D landmark list'''
nodVLines = objLines2vLines(nodObjLines)
nodLandmark3DList = getNodLandmark3D(nodVLines, originLandmark3DList)
'''5. nod 3D landmark --> nod LR 2D landmark'''
nodLandmark2DLR = [i[2] for i in nodLandmark3DList]
'''6. origin 2D landmark'''
originLandmark2DLR = [(i[0][0], i[0][1]) for i in nodLandmark3DList]
assert len(originLandmark2DLR) == len(nodLandmark2DLR)
'''7. LR --> HR: origin and nod face landmark'''
originLandmark2DHR = lr2hr(imgLR, imgHR, originLandmark2DLR)
nodLandmark2DHR = lr2hr(imgLR, imgHR, nodLandmark2DLR)
'''8. HR: collar detection'''
_, collarPoint = collarDetection(imgHR, minSize=1200, offset=15)
'''9. HR: hair detection'''
originHairPoints = hairDetection(imgHR, minSize=20000)
'''10. HR: nod hair points'''
'''??? nod center ???'''
nodAngleHair = 18
# drawPointsOnImg(originHairPoints, imgHR, 'r', radius=3)
# nodHairPoints = nodHairHR(
# objLines, nodAngleHair, nodCenterMode, originHairPoints, minZ=100.0)
nodHairPoints = nodHairHR_m(
nodAngleHair, collarPoint, originHairPoints, minZ=100.0)
# for (x, y), (i, j) in zip(nodHairPoints, nodHairPoints_m):
# if x == i and y == j:
# pass
# else:
# print 'yes'
'''10. HR: all origin points and nod points'''
originPoints = originLandmark2DHR+originHairPoints
nodPoints = nodLandmark2DHR+nodHairPoints
assert len(originPoints) == len(nodPoints)
# drawPointsOnImg(originPoints, imgHR, 'g', radius=2)
'''11. inner ellipse'''
left = min(originPoints, key=lambda x: x[0])[0]
right = max(originPoints, key=lambda x: x[0])[0]
up = min(originPoints, key=lambda x: x[1])[1]
bottom = max(originPoints, key=lambda x: x[1])[1]
innerEllipseCenterX = int((left+right)/2.0)
innerEllipseCenterY = int((up+bottom)/2.0)
innerEllipseSemiX = int((right-left)/2.0)
innerEllipseSemiY = int((bottom-up)/2.0)
rr, cc = ellipse_perimeter(innerEllipseCenterX, innerEllipseCenterY,
innerEllipseSemiY, innerEllipseSemiX, orientation=np.pi*1.5)
innerEllipseVerts = np.dstack([rr, cc])[0]
'''12. outer ellipse'''
'''12.1 ratio = outer ellipse / inner ellipse'''
''' 椭圆心和衣领的线段 和 椭圆的交点'''
minDistance = np.inf
for pt in innerEllipseVerts:
distance = twoPointsDistance(pt, collarPoint)
if distance < minDistance:
minDistance = distance
ratio = twoPointsDistance((innerEllipseCenterX, innerEllipseCenterY), collarPoint) / \
twoPointsDistance(
(innerEllipseCenterX, innerEllipseCenterY), pt)
'''12.2 outer ellipse'''
outerEllipseSemiX = int(ratio*innerEllipseSemiX)
outerEllipseSemiY = int(ratio*innerEllipseSemiY)
rr, cc = ellipse_perimeter(innerEllipseCenterX, innerEllipseCenterY,
outerEllipseSemiY, outerEllipseSemiX, orientation=np.pi*1.5)
outerEllipseVerts = np.dstack([rr, cc])[0]
'''13. edge points on outer ellipse'''
edgePoints = edgePointsOnOuterEllipse(outerEllipseVerts)
'''14. final origin and nod HR points '''
originPointsFinal = originPoints+edgePoints
nodPointsFinal = nodPoints+edgePoints
assert len(originPointsFinal) == len(nodPointsFinal)
drawPointsOnImg(originPointsFinal, imgHR, 'b', radius=2)
drawPointsOnImg(originPoints, imgHR, 'r', radius=2)
drawPointsOnImg(nodPointsFinal, imgHR, 'g', radius=2)
'''15. tri.txt'''
triList = generateTriList(originPointsFinal, imgHR,
triTxtPath='./nodTri.txt')
'''16. warp'''
imgMorph = morph_modify_for_2D3D2D_low_resolution(
originPointsFinal, nodPointsFinal, imgHR, triList)
imshow('imgMorph', imgMorph)
cv2.imwrite('./imgMorph_{}2.png'.format(nodAngleHair), imgMorph)
return originPointsFinal, nodPointsFinal, triList