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import pandas as pd
BODY_IDENTIFIERS = {
"nose": 0,
"neck": -1,
"rightEye": 5,
"leftEye": 2,
"rightEar": 8,
"leftEar": 7,
"rightShoulder": 12,
"leftShoulder": 11,
"rightElbow": 14,
"leftElbow": 13,
"rightWrist": 16,
"leftWrist": 15
}
HAND_IDENTIFIERS = {
"wrist": 0,
"indexTip": 8,
"indexDIP": 7,
"indexPIP": 6,
"indexMCP": 5,
"middleTip": 12,
"middleDIP": 11,
"middlePIP": 10,
"middleMCP": 9,
"ringTip": 16,
"ringDIP": 15,
"ringPIP": 14,
"ringMCP": 13,
"littleTip": 20,
"littleDIP": 19,
"littlePIP": 18,
"littleMCP": 17,
"thumbTip": 4,
"thumbIP": 3,
"thumbMP": 2,
"thumbCMC": 1
}
class mp_holistic_data:
def __init__(self, column_names):
self.data_hub = {}
for n in column_names[1:-1]:
self.data_hub[n] = []
def hand_append_zero(self, handedness):
for k in self.data_hub.keys():
if "_" + handedness + "_" in k:
self.data_hub[k].append(0)
def hand_append_value(self, handedness, hand_landmarks):
for name, lm_idx in HAND_IDENTIFIERS.items():
lm = hand_landmarks.landmark[lm_idx]
for xy, xy_value in zip(['_X', '_Y'], [lm.x, lm.y]):
k = name + '_' + handedness + xy
self.data_hub[k].append(xy_value)
def get_series(self):
return pd.Series(self.data_hub)
def extract_data(self, holistic_results):
def neck(pose_results):
ls = pose_results.pose_landmarks.landmark[11]
rs = pose_results.pose_landmarks.landmark[12]
no = pose_results.pose_landmarks.landmark[0]
if (ls.visibility > 0.5) & (rs.visibility > 0.5) & (no.visibility > 0.5):
# This indicates the neck better. But it does not affect the result.
cx = (ls.x + rs.x) / 2
cy = (ls.y + rs.y) / 2
dx = no.x - cx
dy = no.y - cy
x = cx + 0.3 * dx
y = cy + 0.3 * dy
# x = (ls.x+rs.x)/2
# y = (ls.y+rs.y)/2
else:
x = 0
y = 0
return [x, y]
# for the frame that can not extract skeleton from
if not holistic_results.pose_landmarks:
return
for name, lm_idx in BODY_IDENTIFIERS.items():
if name == "neck":
xy_value = neck(holistic_results)
else:
lm = holistic_results.pose_landmarks.landmark[lm_idx]
visible = float(lm.visibility >= 0.5)
xy_value = [lm.x * visible, lm.y * visible]
for xy_id, xy in zip(['_X', '_Y'], xy_value):
s_name = name + xy_id
self.data_hub[s_name].append(xy)
for handedness, lm in zip(['Right', 'Left'],
[holistic_results.right_hand_landmarks, holistic_results.left_hand_landmarks]):
if lm:
self.hand_append_value(handedness, lm)
else:
self.hand_append_zero(handedness)
return |