nodes/fssorc-ComfyUI_FaceShaper
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add align type:JawLine

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yanghantao
2024-09-19 14:31:39 +08:00
parent 16d7c1fff2
commit 4fdc17c08c
1 changed files with 205 additions and 44 deletions
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__init__.py
+205 -44
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@@ -871,7 +871,7 @@ class FaceShaperMatchV2:
"source_crop_info": ("CROPINFO", ),
"target_crop_info": ("CROPINFO", ),
"landmarkType": (["ALL","OUTLINE"], ),
"AlignType":(["Width","Height","Landmarks"], ),
"AlignType":(["Width","Height","Landmarks","JawLine"], ),
},
}
@@ -881,6 +881,85 @@ class FaceShaperMatchV2:
CATEGORY = "FaceShaper"
def LandMark203_to_68(self,source):
#jawLine
out = [source[108]]
for i in range(0,7):
out.append((source[110+i*2]+source[111+i*2])/2)
out.append(source[126])
for i in range(0,7):
out.append((source[128+i*2]+source[129+i*2])/2)
out.append(source[144])
#leftEyeBow
out.append(source[145])
out.append((source[148]+source[162])/2)
out.append((source[150]+source[160])/2)
out.append((source[152]+source[158])/2)
out.append(source[155])
#rightEyeBow
out.append(source[165])
out.append((source[168]+source[182])/2)
out.append((source[170]+source[180])/2)
out.append((source[172]+source[177])/2)
out.append(source[175])
#nose
out.append(source[199])
out.append((source[199]+source[200])/2)
out.append(source[200])
out.append(source[201])
out.append(source[189])
out.append(source[190])
out.append(source[202])
out.append(source[191])
out.append(source[192])
#leftEye
out.append(source[0])
out.append(source[3])
out.append(source[8])
out.append(source[12])
out.append(source[16])
out.append(source[21])
#rightEye
out.append(source[24])
out.append(source[28])
out.append(source[33])
out.append(source[36])
out.append(source[39])
out.append(source[45])
#UpperLipUp
out.append(source[48])
out.append(source[51])
out.append(source[54])
out.append(source[57])
out.append(source[60])
out.append(source[63])
out.append(source[66])
#LowerLipDown
out.append(source[69])
out.append(source[72])
out.append(source[75])
out.append(source[78])
out.append(source[81])
out.append(source[84])
out.append(source[87])
out.append(source[90])
out.append(source[93])
out.append(source[96])
out.append(source[99])
out.append(source[102])
out.append(source[105])
return out
def run(self,source_image,source_crop_info, target_crop_info,landmarkType,AlignType):
@@ -898,18 +977,65 @@ class FaceShaperMatchV2:
#print(len(landmarks1))
#len(lendmarks1) will always be 203
#V2版本改了检测工具，因此只用203个点
if landmarkType == "ALL" or AlignType == "Landmarks":
leftEye1=np.mean( landmarks1[0:23],axis=0)
rightEye1=np.mean( landmarks1[24:47],axis=0)
leftEye2=np.mean( landmarks2[0:23],axis=0)
rightEye2=np.mean( landmarks2[24:47],axis=0)
jaw1=landmarks1[108:144]
jaw2=landmarks2[108:144]
#203个点太多，影响液化算法的运行效率，再次转换成68个点
use_68_points=True
if(use_68_points):
landmarks1 = self.LandMark203_to_68(landmarks1)
landmarks2 = self.LandMark203_to_68(landmarks2)
landmarks1 = landmarks1[0:65]
landmarks2 = landmarks2[0:65]
#else:
if(use_68_points):
leftEye1=np.mean( landmarks1[36:42],axis=0)
rightEye1=np.mean( landmarks1[42:48],axis=0)
leftEye2=np.mean( landmarks2[36:42],axis=0)
rightEye2=np.mean( landmarks2[42:48],axis=0)
jaw1=landmarks1[0:17]
jaw2=landmarks2[0:17]
centerOfJaw1=np.mean( jaw1,axis=0)
centerOfJaw2=np.mean( jaw2,axis=0)
else:
#保留这个是为了以后要是想改回来
leftEye1=np.mean( landmarks1[0:24],axis=0)
rightEye1=np.mean( landmarks1[24:48],axis=0)
leftEye2=np.mean( landmarks2[0:24],axis=0)
rightEye2=np.mean( landmarks2[24:48],axis=0)
jaw1=landmarks1[108:145]
jaw2=landmarks2[108:145]
centerOfJaw1=np.mean( jaw1,axis=0)
centerOfJaw2=np.mean( jaw2,axis=0)
else:
landmarks1 = landmarks1[108:144]
landmarks2 = landmarks2[108:144]
# if landmarkType == "ALL": # or AlignType == "Landmarks" or AlignType == "JawLine":
# if(len(landmarks1)==203):
# #保留这个是为了以后要是想改回来
# leftEye1=np.mean( landmarks1[0:24],axis=0)
# rightEye1=np.mean( landmarks1[24:48],axis=0)
# leftEye2=np.mean( landmarks2[0:24],axis=0)
# rightEye2=np.mean( landmarks2[24:48],axis=0)
# jaw1=landmarks1[108:145]
# jaw2=landmarks2[108:145]
# centerOfJaw1=np.mean( jaw1,axis=0)
# centerOfJaw2=np.mean( jaw2,axis=0)
# else:
# leftEye1=np.mean( landmarks1[36:42],axis=0)
# rightEye1=np.mean( landmarks1[42:48],axis=0)
# leftEye2=np.mean( landmarks2[36:42],axis=0)
# rightEye2=np.mean( landmarks2[42:48],axis=0)
# jaw1=landmarks1[0:17]
# jaw2=landmarks2[0:17]
# centerOfJaw1=np.mean( jaw1,axis=0)
# centerOfJaw2=np.mean( jaw2,axis=0)
# else:
# if(len(landmarks1)==203):
# #保留这个是为了以后要是想改回来
# landmarks1 = landmarks1[108:145]
# landmarks2 = landmarks2[108:145]
# else:
# landmarks1 = landmarks1[0:17]
# landmarks2 = landmarks2[0:17]
#画面划分成16*16个区域，然后去掉边界框以外的区域。
src_points = np.array([
@@ -919,12 +1045,10 @@ class FaceShaperMatchV2:
])
#上面这些区域同时被加入src和dst，使这些区域不被拉伸（效果是图片边缘不被拉伸）
src_points = src_points[(src_points[:, 0] <= w/8) | (src_points[:, 0] >= 7*w/8) | (src_points[:, 1] >= 7*h/8)| (src_points[:, 1] <= h/8)]
#mark_img = self.draw_landmarks(mark_img, src_points, color=(255, 0, 255))
src_points = src_points[(src_points[:, 0] <= w/8) | (src_points[:, 0] >= 7*w/8) | (src_points[:, 1] >= 7*h/8)| (src_points[:, 1] <= h/8)]
dst_points = src_points.copy()
#不知道原作者为何把这个数组叫dst，其实这是变形前的坐标，即原图的坐标
dst_points = np.append(dst_points,landmarks1,axis=0)
#变形目标人物的landmarks，先计算边界框
landmarks2=np.array(landmarks2)
@@ -934,6 +1058,8 @@ class FaceShaperMatchV2:
max_y = np.max(landmarks2[:, 1])
#得到目标人物的边界框的长宽比
ratio2 = (max_x - min_x) / (max_y - min_y)
middlePoint2 = [ (max_x + min_x) / 2, (max_y + min_y) / 2]
#print("ratio2",ratio2)
#变形原始人物的landmarks，边界框
landmarks1=np.array(landmarks1)
@@ -945,41 +1071,80 @@ class FaceShaperMatchV2:
ratio1 = (max_x - min_x) / (max_y - min_y)
middlePoint = [ (max_x + min_x) / 2, (max_y + min_y) / 2]
landmarks1_cpy = landmarks1.copy()
#print("ratio1",ratio1)
if AlignType=="Width":
#保持人物脸部边界框中心点不变，垂直方向上缩放，使边界框的比例变得跟目标人物的边界框比例一致
landmarks1_cpy[:, 1] = (landmarks1_cpy[:, 1] - middlePoint[1]) * ratio1 / ratio2 + middlePoint[1]
elif AlignType=="Height":
#保持人物脸部边界框中心点不变，水平方向上缩放，使边界框的比例变得跟目标人物的边界框比例一致
landmarks1_cpy[:, 0] = (landmarks1_cpy[:, 0] - middlePoint[0]) * ratio2 / ratio1 + middlePoint[0]
elif AlignType=="Landmarks":
MiddleOfEyes1 = (leftEye1+rightEye1)/2
MiddleOfEyes2 = (leftEye2+rightEye2)/2
distance1 = ((leftEye1[0] - rightEye1[0]) ** 2 + (leftEye1[1] - rightEye1[1]) ** 2) ** 0.5
distance2 = ((leftEye2[0] - rightEye2[0]) ** 2 + (leftEye2[1] - rightEye2[1]) ** 2) ** 0.5
factor = distance1 / distance2
MiddleOfEyes2 = np.array(MiddleOfEyes2)
landmarks1_cpy = (landmarks2 - MiddleOfEyes2) * factor + MiddleOfEyes1
#保持人物脸部边界框中心点不变，垂直方向上缩放，使边界框的比例变得跟目标人物的边界框比例一致
if(landmarkType=="ALL"):
dst_points = np.append(dst_points,landmarks1,axis=0)
target_points = landmarks1.copy()
else:
dst_points = np.append(dst_points,jaw1,axis=0)
jaw1=np.array(jaw1)
target_points = jaw1.copy()
target_points[:, 1] = (target_points[:, 1] - middlePoint[1]) * ratio1 / ratio2 + middlePoint[1]
src_points = np.append(src_points,target_points,axis=0)#不知道原作者为何把这个数组叫src，其实这是变形后的坐标
centerOfJaw2 = np.array(centerOfJaw2)
jawLineTarget = (landmarks2[108:144] - centerOfJaw2) * factor + centerOfJaw1
landmarks1_cpy[108:144] = jawLineTarget
#不知道原作者为何把这个数组叫src，其实这是变形后的坐标
src_points = np.append(src_points,landmarks1_cpy,axis=0)
#print(landmarks1_cpy)
elif AlignType=="Height":
#保持人物脸部边界框中心点不变，水平方向上缩放，使边界框的比例变得跟目标人物的边界框比例一致
if(landmarkType=="ALL"):
dst_points = np.append(dst_points,landmarks1,axis=0) #不知道原作者为何把这个数组叫dst，其实这是变形前的坐标，即原图的坐标
target_points = landmarks1.copy()
else:
dst_points = np.append(dst_points,jaw1,axis=0)#不知道原作者为何把这个数组叫dst，其实这是变形前的坐标，即原图的坐标
jaw1=np.array(jaw1)
target_points = jaw1.copy()
target_points[:, 0] = (target_points[:, 0] - middlePoint[0]) * ratio2 / ratio1 + middlePoint[0]
src_points = np.append(src_points,target_points,axis=0)#不知道原作者为何把这个数组叫src，其实这是变形后的坐标
elif AlignType=="Landmarks":
if(landmarkType=="ALL"):
#以双眼中心为基准点，按双眼距离计算缩放系数。效果是变形前后眼睛位置不变
MiddleOfEyes1 = (leftEye1+rightEye1)/2
MiddleOfEyes2 = (leftEye2+rightEye2)/2
distance1 = ((leftEye1[0] - rightEye1[0]) ** 2 + (leftEye1[1] - rightEye1[1]) ** 2) ** 0.5
distance2 = ((leftEye2[0] - rightEye2[0]) ** 2 + (leftEye2[1] - rightEye2[1]) ** 2) ** 0.5
factor = distance1 / distance2
MiddleOfEyes2 = np.array(MiddleOfEyes2)
target_points = (landmarks2 - MiddleOfEyes2) * factor + MiddleOfEyes1
#面部轮廓线则以轮廓线中心点为基准点，缩放系数还是从双眼距离计算
centerOfJaw2 = np.array(centerOfJaw2)
jawLineTarget = (landmarks2[108:144] - centerOfJaw2) * factor + centerOfJaw1
target_points[108:144] = jawLineTarget
dst_points = np.append(dst_points,landmarks1,axis=0)#不知道原作者为何把这个数组叫dst，其实这是变形前的坐标，即原图的坐标
else:
#此时只有轮廓线landMark。对齐两个landMark的中心点，然后用2替换掉1
dst_points = np.append(dst_points,jaw1,axis=0)#不知道原作者为何把这个数组叫dst，其实这是变形前的坐标，即原图的坐标
target_points=(jaw2-centerOfJaw2)+centerOfJaw1
src_points = np.append(src_points,target_points,axis=0)#不知道原作者为何把这个数组叫src，其实这是变形后的坐标
elif AlignType=="JawLine":
lenOfJaw=len(jaw1)
distance1= ((jaw1[0][0] - jaw1[lenOfJaw-1][0]) ** 2 + (jaw1[0][1] - jaw1[lenOfJaw-1][1]) ** 2) ** 0.5
distance2= ((jaw2[0][0] - jaw2[lenOfJaw-1][0]) ** 2 + (jaw2[0][1] - jaw2[lenOfJaw-1][1]) ** 2) ** 0.5
factor = distance1 / distance2
if landmarkType == "ALL":
dst_points = np.append(dst_points,landmarks1,axis=0)
target_points=(landmarks2-jaw2[0])*factor+jaw1[0]
src_points = np.append(src_points,target_points,axis=0)
else:
dst_points = np.append(dst_points,jaw1,axis=0)
target_points=(jaw2-jaw2[0])*factor+jaw1[0]
src_points = np.append(src_points,target_points,axis=0)
mark_img = draw_pointsOnImg(image1, dst_points, color=(255, 255, 0),radius=4)
mark_img = draw_pointsOnImg(mark_img, src_points, color=(255, 0, 0),radius=3)
mark_img = drawLineBetweenPoints(mark_img, dst_points,src_points)
#mark_img = draw_landmarks(image1, landmarks1, color=(255, 0, 0),radius=3)
#mark_img2 = draw_landmarks(image1, source_crop_info["crop_info_list"][0]['lmk_crop'], color=(255, 0, 0),radius=3)
# Create the RBF interpolator instance
#### 开始对图片进行液化变形
#Tried many times, finally find out these array should be exchange w,h before go into RBFInterpolator
src_points[:, [0, 1]] = src_points[:, [1, 0]]
dst_points[:, [0, 1]] = dst_points[:, [1, 0]]
rbfy = RBFInterpolator(src_points,dst_points[:,1],kernel="thin_plate_spline")
rbfx = RBFInterpolator(src_points,dst_points[:,0],kernel="thin_plate_spline")
@@ -994,16 +1159,12 @@ class FaceShaperMatchV2:
map_x = rbfx(flatten).reshape(height,width).astype(np.float32)
# Apply the remapping to the image using OpenCV
warped_image = cv2.remap(image1, map_y, map_x, cv2.INTER_LINEAR)
######### 液化变形结束
warped_image = torch.from_numpy(warped_image.astype(np.float32) / 255.0).unsqueeze(0)
mark_img = torch.from_numpy(mark_img.astype(np.float32) / 255.0).unsqueeze(0)
#mark_img2= torch.from_numpy(mark_img2.astype(np.float32) / 255.0).unsqueeze(0)
output.append(warped_image)
output.append(mark_img)
#output.append(mark_img2)
#print("warped_image",warped_image.shape)
#print("mark_img",mark_img.shape)
return (output)