我试图将 MP 姿势地标（33 个值）映射/翻译到 BVH 层次结构，但由于某些原因，我的模型不断翻转和弯曲。我遇到的挑战，
如果有人可以帮助回答这些问题中的任何一个，甚至可以指出正确的资源，那就太棒了。提前致谢！
HIERARCHY
ROOT hip
{
OFFSET 0 0 0
CHANNELS 6 Xposition Yposition Zposition Zrotation Yrotation Xrotation
JOINT abdomen
{
OFFSET 0 20.6881 -0.73152
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT chest
{
OFFSET 0 11.7043 -0.48768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT neck
{
OFFSET 0 22.1894 -2.19456
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT head
{
OFFSET -0.24384 7.07133 1.2192
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT leftEye
{
OFFSET 4.14528 8.04674 8.04672
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1 0 0
}
}
JOINT rightEye
{
OFFSET -3.6576 8.04674 8.04672
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1 0 0
}
}
}
}
JOINT rCollar
{
OFFSET -2.68224 19.2634 -4.8768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rShldr
{
OFFSET -8.77824 -1.95073 1.46304
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rForeArm
{
OFFSET -28.1742 -1.7115 0.48768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rHand
{
OFFSET -22.5879 0.773209 7.07136
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rThumb1
{
OFFSET -1.2192 -0.487915 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rThumb2
{
OFFSET -3.37035 -0.52449 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.78271 -1.18214 1.43049
}
}
}
JOINT rIndex1
{
OFFSET -7.75947 0.938293 5.60832
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rIndex2
{
OFFSET -2.54057 -0.884171 1.56538
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.62519 -0.234802 1.16502
}
}
}
JOINT rMid1
{
OFFSET -8.24714 1.18213 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rMid2
{
OFFSET -3.10165 -0.590103 1.0647
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -2.48547 -0.328903 0.83742
}
}
}
JOINT rRing1
{
OFFSET -8.82822 0.546677 1.51678
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rRing2
{
OFFSET -2.60934 -0.819778 -0.0198488
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -2.33842 -0.294052 0.168128
}
}
}
JOINT rPinky1
{
OFFSET -8.27202 -0.0477905 -0.4584
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rPinky2
{
OFFSET -1.82734 -0.647385 -0.700984
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.69225 -0.51767 -0.607171
}
}
}
}
}
}
}
JOINT lCollar
{
OFFSET 2.68224 19.2634 -4.8768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lShldr
{
OFFSET 8.77824 -1.95073 1.46304
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lForeArm
{
OFFSET 28.1742 -1.7115 0.48768
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lHand
{
OFFSET 22.5879 0.773209 7.07136
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lThumb1
{
OFFSET 1.2192 -0.487915 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lThumb2
{
OFFSET 3.37035 -0.52449 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.78271 -1.18214 1.43049
}
}
}
JOINT lIndex1
{
OFFSET 7.75947 0.938293 5.60832
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lIndex2
{
OFFSET 2.54057 -0.884171 1.56538
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.62519 -0.234802 1.16502
}
}
}
JOINT lMid1
{
OFFSET 8.24714 1.18213 3.41376
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lMid2
{
OFFSET 3.10165 -0.590103 1.0647
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 2.48547 -0.328903 0.83742
}
}
}
JOINT lRing1
{
OFFSET 8.82822 0.546677 1.51678
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lRing2
{
OFFSET 2.60934 -0.819778 -0.0198488
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 2.33842 -0.294052 0.168128
}
}
}
JOINT lPinky1
{
OFFSET 8.27202 -0.0477905 -0.4584
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lPinky2
{
OFFSET 1.82734 -0.647385 -0.700984
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.69225 -0.51767 -0.607171
}
}
}
}
}
}
}
}
}
JOINT rButtock
{
OFFSET -8.77824 4.35084 1.2192
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rThigh
{
OFFSET 0 -1.70687 -2.19456
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rShin
{
OFFSET 0 -36.8199 0.73152
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT rFoot
{
OFFSET 0.73152 -45.1104 -5.12064
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET -1.1221 -3.69964 12.103
}
}
}
}
}
JOINT lButtock
{
OFFSET 8.77824 4.35084 1.2192
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lThigh
{
OFFSET 0 -1.70687 -2.19456
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lShin
{
OFFSET 0 -36.8199 0.73152
CHANNELS 3 Zrotation Xrotation Yrotation
JOINT lFoot
{
OFFSET -0.73152 -45.1104 -5.12064
CHANNELS 3 Zrotation Xrotation Yrotation
End Site
{
OFFSET 1.1221 -3.69964 12.103
}
}
}
}
}
}
def rot(a, b):
c = b - a
c /= np.linalg.norm(c)
thetaZ = np.arctan2(c[1], c[0])
thetaX = np.arctan2(c[2], c[0]**2 + c[1]**2)
thetaY = np.arctan2(c[2], np.sqrt(c[0]**2 + c[1]**2))
thetaZdeg = float('{:.3f}'.format(np.rad2deg(thetaZ))[:-1])
thetaXdeg = float('{:.3f}'.format(np.rad2deg(thetaX))[:-1])
thetaYdeg = float('{:.3f}'.format(np.rad2deg(thetaY))[:-1])
return [thetaZdeg, thetaXdeg, thetaYdeg]
def dataLoad2(i, j, res1, res2):
return str((res1[i] + res2[j] / 2)[2]) + " " + str((res1[i] + res2[j] / 2)[1]) + " " + str((res1[i] + res2[j] / 2)[0]) + " "
def dataLoad(i, res):
try:
return str(res[i][2]) + " " + str(res[i][1]) + " " + str(res[i][0]) + " "
except:
return str(res[2]) + " " + str(res[1]) + " " + str(res[0]) + " "
def writeBVH(res):
hip = dataLoad2(24, 23, res, res)
chest = dataLoad2(11, 12, res, res)
temp = list(np.array([eval(i) for i in hip.split(' ')[:-1]]) + np.array([eval(i) for i in chest.split(' ')[:-1]]) / 2)
abdomen = dataLoad(0, temp)
mouth = dataLoad2(10, 9, res, res)
temp = list(np.array([eval(i) for i in mouth.split(' ')[:-1]]) + np.array([eval(i) for i in chest.split(' ')[:-1]]) / 2)
neck = dataLoad(0, temp)
head = dataLoad(0, res)
lefteye = dataLoad(2, res)
righteye = dataLoad(5, res)
rcollar = dataLoad2(12, 10, res, res)
rshldr = dataLoad(12, res)
rforearm = dataLoad(14, res)
rhand = dataLoad(16,res)
rthumb1 = dataLoad2(16, 22, res, res)
rthumb2 = dataLoad(22, res)
rindex1 = dataLoad2(16, 20, res, res)
rindex2 = dataLoad(20, res)
''' Edit These After Using Hand Landmarks '''
rmid1 = dataLoad2(16, 20, res, res)
rmid2 = dataLoad(20, res)
rring1 = dataLoad2(16, 20, res, res)
rring2 = dataLoad(20, res)
''' Edit These After Using Hand Landmarks '''
rpinky1 = dataLoad2(16, 18, res, res)
rpinky2 = dataLoad(18, res)
lcollar = dataLoad2(11, 9, res, res)
lshldr = dataLoad(11, res)
lforearm = dataLoad(13, res)
lhand = dataLoad(15,res)
lthumb1 = dataLoad2(15, 21, res, res)
lthumb2 = dataLoad(21, res)
lindex1 = dataLoad2(15, 19, res, res)
lindex2 = dataLoad(19, res)
''' Edit These After Using Hand Landmarks '''
lmid1 = dataLoad2(15, 19, res, res)
lmid2 = dataLoad(19, res)
lring1 = dataLoad2(15, 19, res, res)
lring2 = dataLoad(19, res)
''' Edit These After Using Hand Landmarks '''
lpinky1 = dataLoad2(15, 17, res, res)
lpinky2 = dataLoad(17, res)
rbuttock = dataLoad(24, res)
rthigh = dataLoad2(24, 26, res, res)
rshin = dataLoad(26, res)
rfoot = dataLoad(28, res)
lbuttock = dataLoad(23, res)
lthigh = dataLoad2(23, 25, res, res)
lshin = dataLoad(25, res)
lfoot = dataLoad(27, res)
return hip+hip+abdomen+chest+neck+head+lefteye+righteye+rcollar+rshldr+rforearm+rhand+rthumb1+rthumb2+rindex1+rindex2+rmid1+rmid2+rring1+rring2+rpinky1+rpinky2+lcollar+lshldr+lforearm+lhand+lthumb1+lthumb2+lindex1+lindex2+lmid1+lmid2+lring1+lring2+lpinky1+lpinky2+rbuttock+rthigh+rshin+rfoot+lbuttock+lthigh+lshin+lfoot+"\n"
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_pose = mp.solutions.pose
# For static images:
IMAGE_FILES = []
BG_COLOR = (192, 192, 192) # gray
with mp_pose.Pose(
static_image_mode=True,
model_complexity=2,
enable_segmentation=True,
min_detection_confidence=0.5) as pose:
for idx, file in enumerate(IMAGE_FILES):
image = cv2.imread(file)
image_height, image_width, _ = image.shape
# Convert the BGR image to RGB before processing.
results = pose.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
if not results.pose_landmarks:
continue
print(
f'Nose coordinates: ('
f'{results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].x * image_width}, '
f'{results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].y * image_height})'
)
annotated_image = image.copy()
# Draw segmentation on the image.
# To improve segmentation around boundaries, consider applying a joint
# bilateral filter to "results.segmentation_mask" with "image".
condition = np.stack((results.segmentation_mask,) * 3, axis=-1) > 0.1
bg_image = np.zeros(image.shape, dtype=np.uint8)
bg_image[:] = BG_COLOR
annotated_image = np.where(condition, annotated_image, bg_image)
# Draw pose landmarks on the image.
mp_drawing.draw_landmarks(
annotated_image,
results.pose_landmarks,
mp_pose.POSE_CONNECTIONS,
landmark_drawing_spec=mp_drawing_styles.get_default_pose_landmarks_style())
cv2.imwrite('/tmp/annotated_image' + str(idx) + '.png', annotated_image)
# Plot pose world landmarks.
mp_drawing.plot_landmarks(
results.pose_world_landmarks, mp_pose.POSE_CONNECTIONS)
temp = [0.00] * 132
count = 0
with open("test.bvh", "a") as bvh:
# For webcam input:
cap = cv2.VideoCapture(0)
with mp_pose.Pose(
min_detection_confidence=0.5,
min_tracking_confidence=0.5) as pose:
while cap.isOpened():
success, image = cap.read()
if not success:
print("Ignoring empty camera frame.")
# If loading a video, use 'break' instead of 'continue'.
continue
# To improve performance, optionally mark the image as not writeable to
# pass by reference.
image.flags.writeable = False
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
results = pose.process(image)
if results.pose_landmarks:
count += 1
res = np.array([[res.x, res.y, res.z] for res in results.pose_landmarks.landmark])
t = writeBVH(res)
t = t.split(' ')[:-1]
res = [[float('{:.3f}'.format(float(t[0]))[:-1]), float('{:.3f}'.format(float(t[1]))[:-1]), float('{:.3f}'.format(float(t[2]))[:-1])]]
t = np.array(list(map(float, t))).reshape(44,3)
temp = np.array(list(map(float, temp))).reshape(44,3)
for i in range(1, 44):
res.append(rot(t[i], temp[i]))
res = list(np.array(res).flatten())
(res[4], res[5]) = (res[5], res[4])
s = ''
for i in res:
s += str(i) + ' '
s += '\n'
bvh.write(s)
temp = list(temp.flatten())
# Draw the pose annotation on the image.
image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
mp_drawing.draw_landmarks(
image,
results.pose_landmarks,
mp_pose.POSE_CONNECTIONS,
landmark_drawing_spec=mp_drawing_styles.get_default_pose_landmarks_style())
# Flip the image horizontally for a selfie-view display.
cv2.imshow('MediaPipe Pose', cv2.flip(image, 1))
if cv2.waitKey(5) & 0xFF == 27:
break
cap.release()
cv2.destroyAllWindows()
print(count)