目录
0、项目介绍
mediapipe中有人体姿态检测的功能，今天我们就将实现最最基础的人体姿态估计项目，它的应用还是有很多的，比如：AI锻炼检测标准、老人跌倒检测等，这些方面其实已经有了很多的参考资料了，当然在我知道的当中用yolo的倒是挺多的。那么今天我们将会通过人物跳舞的视频进行一个姿态的检测。
1、效果展示
可以看见GIF图片中人物跳舞视频检测到的人体姿态骨架。（窗口大小的问题，膝盖下的点没有检测到）
2、项目搭建
如上图，你完全按这个模式照搬过去，完整的视频已经被我拆分好了，大家有兴趣的可以从我的GitHub中获得完整视频与拆分好的视频。
3、项目代码讲解与介绍
Basics.py
-
import cv2
-
import mediapipe
as mp
-
import time
-
-
mpDraw = mp.solutions.drawing_utils
-
mpPose = mp.solutions.pose
-
pose = mpPose.Pose()
-
-
cap = cv2.VideoCapture(
'Pose_videos/02.mp4')
-
pTime =
0
-
while
True:
-
success, img = cap.read()
-
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-
results = pose.process(imgRGB)
-
# print(results.pose_landmarks)
-
if results.pose_landmarks:
-
mpDraw.draw_landmarks(img, results.pose_landmarks, mpPose.POSE_CONNECTIONS)
-
for
id, lm
in
enumerate(results.pose_landmarks.landmark):
-
h, w, c = img.shape
-
print(
id, lm)
-
cx, cy =
int(lm.x * w),
int(lm.y * h)
-
cv2.circle(img, (cx, cy),
5, (
255,
0,
0), cv2.FILLED)
-
#######################################################################################
-
cTime = time.time()
-
fps =
1 / (cTime - pTime)
-
pTime = cTime
-
cv2.putText(img,
str(
int(fps)), (
70,
50), cv2.FONT_HERSHEY_PLAIN,
3,
-
(
255,
0,
0),
3)
-
-
cv2.imshow(
"Image", img)
-
k=cv2.waitKey(
1)
-
if k==
27:
-
break
PoseModule.py
-
import cv2
-
import mediapipe
as mp
-
import time
-
-
class
poseDetector():
-
-
def
__init__(
self, mode=False, upBody=False, smooth=True,
-
detectionCon=0.5, trackCon=0.5):
-
-
self.mode = mode
-
self.upBody = upBody
-
self.smooth = smooth
-
self.detectionCon = detectionCon
-
self.trackCon=trackCon
-
-
self.mpDraw = mp.solutions.drawing_utils
-
self.mpPose = mp.solutions.pose
-
self.pose = self.mpPose.Pose(self.mode, self.upBody, self.smooth)
-
-
def
findPose(
self, img, draw=True):
-
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-
self.results = self.pose.process(imgRGB)
-
if self.results.pose_landmarks:
-
if draw:
-
self.mpDraw.draw_landmarks(img, self.results.pose_landmarks,
-
self.mpPose.POSE_CONNECTIONS)
-
return img
-
-
def
findPosition(
self, img, draw=True):
-
self.lmList = []
-
if self.results.pose_landmarks:
-
for
id, lm
in
enumerate(self.results.pose_landmarks.landmark):
-
h, w, c = img.shape
-
# print(id, lm)
-
cx, cy =
int(lm.x * w),
int(lm.y * h)
-
self.lmList.append([
id, cx, cy])
-
if draw:
-
cv2.circle(img, (cx, cy),
5, (
255,
0,
0), cv2.FILLED)
-
return self.lmList
-
-
def
main():
-
cap = cv2.VideoCapture(
'Pose_videos/02.mp4')
-
pTime =
0
-
detector = poseDetector()
-
while
True:
-
success, img = cap.read()
-
img = detector.findPose(img)
-
lmList = detector.findPosition(img, draw=
False)
-
if
len(lmList) !=
0:
-
print(lmList[
14])
-
cv2.circle(img, (lmList[
14][
1], lmList[
14][
2]),
15, (
0,
0,
255), cv2.FILLED)
-
-
cTime = time.time()
-
fps =
1 / (cTime - pTime)
-
pTime = cTime
-
-
cv2.putText(img,
str(
int(fps)), (
70,
50), cv2.FONT_HERSHEY_PLAIN,
3,
-
(
255,
0,
0),
3)
-
-
cv2.imshow(
"Image", img)
-
k=cv2.waitKey(
1)
-
if k==
27:
-
break
-
-
if __name__ ==
"__main__":
-
main()
此模块参照与cvzone中的cvzone.PoseModule模块，大家以后也要学习一下这种制作模块的思想，对大家做项目时是很有帮助的。
Example.py
-
import cv2
-
import time
-
import PoseModule
as pm
-
-
cap = cv2.VideoCapture(
'Pose_videos/02.mp4')
-
pTime =
0
-
detector = pm.poseDetector()
-
while
True:
-
success, img = cap.read()
-
img = detector.findPose(img)
-
lmList = detector.findPosition(img, draw=
False)
-
if
len(lmList) !=
0:
-
print(lmList[
14])
-
cv2.circle(img, (lmList[
14][
1], lmList[
14][
2]),
15, (
0,
0,
255), cv2.FILLED)
-
-
cTime = time.time()
-
fps =
1 / (cTime - pTime)
-
pTime = cTime
-
-
cv2.putText(img,
str(
int(fps)), (
70,
50), cv2.FONT_HERSHEY_PLAIN,
3,
-
(
255,
0,
0),
3)
-
-
cv2.imshow(
"Image", img)
-
k = cv2.waitKey(
1)
-
if k ==
27:
-
break
可以看到，在以后做项目时就可以从模块当中copy代码，实现会变得更加的方便。
人体姿态图
此为人体姿态各点的对应图，如果你想要检测某一点的信息，则需要查看此图。
（此图来源于Pose | mediapipe）
4、项目资源
GitHub:18 Human Posture Recognition
5、项目总结
本次项目是按照mediapipe提供的人体姿态估计的功能实现的项目，非常的基础和简单，后面如果我有更好的点子会继续更新这部分内容。
转载：https://blog.csdn.net/m0_62919535/article/details/128425482
查看评论