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PoseEstimationModule.py
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PoseEstimationModule.py
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import cv2
import time
import mediapipe as mp
class poseDetector( ):
def __init__(self, mode=False, complexity=1, smooth=True, segmentation=False, smooth_segmentation=True,
detectionCon=0.5, trackCon=0.5):
self.mode = mode
self.complexity = complexity
self.segmentation = segmentation
self.smooth_segmentation = smooth_segmentation
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.complexity, self.smooth, self.segmentation,
self.smooth_segmentation, self.detectionCon, self.trackCon)
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):
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)
lmList.append([id, cx, cy])
if draw:
cv2.circle(img, (cx, cy), 5, (255, 255, 0), cv2.FILLED)
return lmList
def main():
cap = cv2.VideoCapture("videos/poseVideo3.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)
cv2.waitKey(1)
if __name__ == "__main__":
main( )