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import pandas as pd | |
import numpy as np | |
import cv2 | |
def extract_landmarks(image, mp_pose, cols): | |
pre_list = [] | |
with mp_pose.Pose(static_image_mode=True, enable_segmentation=True) as pose: | |
result = pose.process( | |
cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) | |
try: | |
# xy = bounding_box(result.pose_landmarks.landmark) | |
for landmark in result.pose_landmarks.landmark: | |
pre_list.append(landmark) | |
predict = True | |
except AttributeError: | |
return True, pd.DataFrame(), None | |
if predict == True: | |
gen1116 = np.array([ | |
[ | |
pre_list[m].x, | |
pre_list[m].y, | |
pre_list[m].z, | |
pre_list[m].visibility | |
] for m in range(11, 17) | |
]).flatten().tolist() | |
gen2333 = np.array([ | |
[ | |
pre_list[m].x, | |
pre_list[m].y, | |
pre_list[m].z, | |
pre_list[m].visibility | |
] for m in range(23, 33) | |
]).flatten().tolist() | |
gen1116.extend(gen2333) | |
all_list = [ | |
pre_list[0].x, | |
pre_list[0].y, | |
pre_list[0].z, | |
pre_list[0].visibility, | |
] | |
all_list.extend(gen1116) | |
return False, pd.DataFrame([all_list], columns=cols), result.pose_landmarks | |
# def bounding_box(landmarks): | |
# w = 1280 | |
# h = 720 | |
# xy = [0, 0, w, h] | |
# for landmark in landmarks: | |
# x, y = int(landmark.x * w), int(landmark.y * h) | |
# if x > xy[0]: | |
# xy[0] = x | |
# if x < xy[2]: | |
# xy[2] = x | |
# if y > xy[1]: | |
# xy[1] = y | |
# if y < xy[3]: | |
# xy[3] = y | |
# return xy | |