def run(self):
global height, width
self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
self.cap.set(3, 480)
self.cap.set(4, 640)
self.cap.set(5, 7)
self.fourcc = cv2.VideoWriter_fourcc(*'XVID')
self.out = cv2.VideoWriter('Wideo/Przysiady.avi', self.fourcc, 3,
(640, 480))
while True:
ret, frame = self.cap.read()
if ret:
allPerson = estimator.inference(frame,
resize_to_default=(w > 0
and h > 0),
upsample_size=4.0)
frame = TfPoseEstimator.draw_humans(frame,
allPerson,
imgcopy=False)
height, width = frame.shape[0], frame.shape[1]
if len(allPerson) > 0:
# dystans
foot_distance = int(
euclidianDistance(findPoint(allPerson, 10),
findPoint(allPerson, 13)))
knee_distance = int(
euclidianDistance(findPoint(allPerson, 9),
findPoint(allPerson, 12)))
shoulders_distance = int(
euclidianDistance(findPoint(allPerson, 2),
findPoint(allPerson, 5)))
# katy
angleKneeR = angleCount(findPoint(allPerson, 11),
findPoint(allPerson, 12),
findPoint(allPerson, 13))
angleKneeL = angleCount(findPoint(allPerson, 8),
findPoint(allPerson, 9),
findPoint(allPerson, 10))
angleNeckR = angleCount(findPoint(allPerson, 8),
findPoint(allPerson, 1),
findPoint(allPerson, 0))
angleNeckL = angleCount(findPoint(allPerson, 11),
findPoint(allPerson, 1),
findPoint(allPerson, 0))
if angleNeckR < 120:
cv2.putText(frame,
"Patrz przed siebie!", (20, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if shoulders_distance <= 0.55 * foot_distance:
cv2.putText(frame,
"Stopy za szeroko!", (20, 55),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if shoulders_distance >= 1.3 * foot_distance:
cv2.putText(frame,
"Rozszerz stopy!", (20, 80),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if knee_distance <= 0.7 * foot_distance:
cv2.putText(frame,
"Kolana zbyt wasko!", (20, 105),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if knee_distance >= 1.35 * foot_distance:
cv2.putText(frame,
"Kolana za szeroko!", (20, 130),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if squats(angleKneeR, angleKneeL, angleNeckR, angleNeckL) and (
knee_distance >= 0.7 * foot_distance) and (
foot_distance <= 1.35 * knee_distance) \
and (shoulders_distance >= 0.55 * foot_distance) and (
shoulders_distance <= 1.3 * foot_distance):
frame = TfPoseEstimator.draw_humans2(frame,
allPerson,
imgcopy=False)
if squatsDone(angleKneeR, angleKneeL):
frame = TfPoseEstimator.draw_humans3(frame,
allPerson,
imgcopy=False)
if squatDoneScore(angleKneeR, angleKneeL):
frame = TfPoseEstimator.draw_humans4(
frame, allPerson, imgcopy=False)
cv2.putText(frame,
"Powrot do gory!", (20, 80),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
else:
cv2.putText(frame,
"Brak uzytkownika na obrazie!", (20, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
qImg4 = QImage(frame.data, width, height, QImage.Format_BGR888)
self.changePixmap.emit(qImg4)
self.out.write(frame)
def run(self):
global height, width
self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
self.cap.set(3, 480)
self.cap.set(4, 640)
self.cap.set(5, 7)
self.fourcc = cv2.VideoWriter_fourcc(*'XVID')
self.out = cv2.VideoWriter('Wideo/Pompki.avi', self.fourcc, 3,
(640, 480))
while True:
ret, frame = self.cap.read()
if ret:
allPerson = estimator.inference(frame,
resize_to_default=(w > 0
and h > 0),
upsample_size=4.0)
frame = TfPoseEstimator.draw_humans(frame,
allPerson,
imgcopy=False)
height, width = frame.shape[0], frame.shape[1]
if len(allPerson) > 0:
# katy
angleAnkleR = angleCount(findPoint(allPerson, 4),
findPoint(allPerson, 3),
findPoint(allPerson, 2))
angleAnkleL = angleCount(findPoint(allPerson, 7),
findPoint(allPerson, 6),
findPoint(allPerson, 5))
angleKneeR = angleCount(findPoint(allPerson, 8),
findPoint(allPerson, 9),
findPoint(allPerson, 10))
angleKneeL = angleCount(findPoint(allPerson, 11),
findPoint(allPerson, 12),
findPoint(allPerson, 13))
angleHipR = angleCount(findPoint(allPerson, 1),
findPoint(allPerson, 8),
findPoint(allPerson, 9))
angleHipL = angleCount(findPoint(allPerson, 1),
findPoint(allPerson, 11),
findPoint(allPerson, 12))
angleNeckR = angleCount(findPoint(allPerson, 8),
findPoint(allPerson, 1),
findPoint(allPerson, 0))
angleNeckL = angleCount(findPoint(allPerson, 11),
findPoint(allPerson, 1),
findPoint(allPerson, 0))
if angleKneeR < 145:
cv2.putText(frame,
"Nie zginaj kolan!", (20, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if angleHipR < 145:
cv2.putText(frame,
"Biodra nizej!", (20, 55),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if angleNeckR < 150:
cv2.putText(frame,
"Patrz przed siebie!", (20, 80),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if pushUps(angleAnkleR, angleAnkleL, angleKneeR,
angleKneeL, angleHipR, angleHipL, angleNeckR,
angleNeckL):
frame = TfPoseEstimator.draw_humans2(frame,
allPerson,
imgcopy=False)
if pushUpsDone(angleAnkleR, angleAnkleL):
frame = TfPoseEstimator.draw_humans3(frame,
allPerson,
imgcopy=False)
if pushUpsDoneScore(angleAnkleR, angleAnkleL):
frame = TfPoseEstimator.draw_humans4(
frame, allPerson, imgcopy=False)
cv2.putText(frame,
"Powrot do gory!", (20, 105),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
else:
cv2.putText(frame,
"Brak uzytkownika na obrazie!", (20, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
qImg2 = QImage(frame.data, width, height, QImage.Format_BGR888)
self.changePixmap.emit(qImg2)
self.out.write(frame)
def run(self):
global height, width
self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
self.cap.set(3, 480)
self.cap.set(4, 640)
self.cap.set(5, 7)
self.fourcc = cv2.VideoWriter_fourcc(*'XVID')
self.out = cv2.VideoWriter('Wideo/Plank.avi', self.fourcc, 3,
(640, 480))
while True:
ret, frame = self.cap.read()
if ret:
allPerson = estimator.inference(frame,
resize_to_default=(w > 0
and h > 0),
upsample_size=4.0)
frame = TfPoseEstimator.draw_humans(frame,
allPerson,
imgcopy=False)
height, width = frame.shape[0], frame.shape[1]
if len(allPerson) > 0:
# dystans
foot_distance = int(
euclidianDistance(findPoint(allPerson, 10),
findPoint(allPerson, 13)))
ankle_distance = int(
euclidianDistance(findPoint(allPerson, 3),
findPoint(allPerson, 6)))
# katy
angleAnkleR = angleCount(findPoint(allPerson, 7),
findPoint(allPerson, 6),
findPoint(allPerson, 5))
angleAnkleL = angleCount(findPoint(allPerson, 4),
findPoint(allPerson, 3),
findPoint(allPerson, 2))
angleKneeR = angleCount(findPoint(allPerson, 8),
findPoint(allPerson, 9),
findPoint(allPerson, 10))
angleKneeL = angleCount(findPoint(allPerson, 11),
findPoint(allPerson, 12),
findPoint(allPerson, 13))
angleHipR = angleCount(findPoint(allPerson, 1),
findPoint(allPerson, 8),
findPoint(allPerson, 9))
angleHipL = angleCount(findPoint(allPerson, 1),
findPoint(allPerson, 11),
findPoint(allPerson, 12))
angleNeckR = angleCount(findPoint(allPerson, 0),
findPoint(allPerson, 1),
findPoint(allPerson, 8))
angleNeckL = angleCount(findPoint(allPerson, 0),
findPoint(allPerson, 1),
findPoint(allPerson, 11))
if angleAnkleR < 80:
cv2.putText(frame,
"Trzymaj kat prosty w lokciach!", (20, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if angleKneeR < 125:
cv2.putText(frame,
"Nie zginaj kolan!", (20, 55),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if angleHipR < 115:
cv2.putText(frame,
"Biodra nizej!", (20, 80),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if angleNeckR < 130:
cv2.putText(frame,
"Patrz przed siebie!", (20, 105),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if foot_distance > ankle_distance:
cv2.putText(frame,
"Stopy za szeroko!", (20, 105),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if plank(angleAnkleR, angleAnkleL, angleKneeR, angleKneeL,
angleHipR, angleHipL, angleNeckR,
angleNeckL) and foot_distance < ankle_distance:
frame = TfPoseEstimator.draw_humans2(frame,
allPerson,
imgcopy=False)
if plankDone(angleAnkleR, angleAnkleL):
frame = TfPoseEstimator.draw_humans3(frame,
allPerson,
imgcopy=False)
cv2.putText(frame,
"Tak trzymaj!", (20, 130),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
else:
cv2.putText(frame,
"Brak uzytkownika na obrazie!", (20, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
qImg3 = QImage(frame.data, width, height, QImage.Format_BGR888)
self.changePixmap.emit(qImg3)
self.out.write(frame)
def run(self):
global counter, start_time
global height, width
self.cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
self.cap.set(3, 480)
self.cap.set(4, 640)
self.cap.set(5, 7)
self.fourcc = cv2.VideoWriter_fourcc(*'XVID')
self.out = cv2.VideoWriter('Wideo/Wykroki.avi', self.fourcc, 3,
(640, 480))
while True:
ret, frame = self.cap.read()
if ret:
allPerson = estimator.inference(frame,
resize_to_default=(w > 0
and h > 0),
upsample_size=4.0)
frame = TfPoseEstimator.draw_humans(frame,
allPerson,
imgcopy=False)
height, width = frame.shape[0], frame.shape[1]
if len(allPerson) > 0:
# katy
angleKneeR = angleCount(findPoint(allPerson, 10),
findPoint(allPerson, 9),
findPoint(allPerson, 8))
angleKneeL = angleCount(findPoint(allPerson, 13),
findPoint(allPerson, 12),
findPoint(allPerson, 11))
angleNeckR = angleCount(findPoint(allPerson, 8),
findPoint(allPerson, 1),
findPoint(allPerson, 0))
angleNeckL = angleCount(findPoint(allPerson, 11),
findPoint(allPerson, 1),
findPoint(allPerson, 0))
# dystans
wrist_hipR = int(
euclidianDistance(findPoint(allPerson, 4),
findPoint(allPerson, 8)))
wrist_hipL = int(
euclidianDistance(findPoint(allPerson, 7),
findPoint(allPerson, 11)))
wrist_noseR = int(
euclidianDistance(findPoint(allPerson, 4),
findPoint(allPerson, 0)))
wrist_noseL = int(
euclidianDistance(findPoint(allPerson, 7),
findPoint(allPerson, 0)))
if angleKneeR < 80:
cv2.putText(frame,
"Zachowaj kat prosty w kolanie!", (20, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if angleNeckR < 110 or angleNeckL > 150:
cv2.putText(frame,
"Patrz przed siebie!", (20, 55),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if wrist_hipR > wrist_noseR:
cv2.putText(frame,
"Trzymaj rece przy ciele!", (20, 80),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
if lungesStart(angleKneeR, angleKneeL, angleNeckR,
angleNeckL) and (wrist_hipL < wrist_noseL or
wrist_hipR < wrist_noseR):
frame = TfPoseEstimator.draw_humans2(frame,
allPerson,
imgcopy=False)
if lungesDone(angleKneeR, angleKneeL):
frame = TfPoseEstimator.draw_humans3(frame,
allPerson,
imgcopy=False)
if lungesDoneScore(angleKneeR, angleKneeL):
frame = TfPoseEstimator.draw_humans4(
frame, allPerson, imgcopy=False)
cv2.putText(frame,
"Powrot do gory!", (20, 105),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
else:
cv2.putText(frame,
"Brak uzytkownika na obrazie!", (20, 30),
cv2.FONT_HERSHEY_SIMPLEX,
1,
color=(255, 255, 255),
thickness=2,
lineType=cv2.LINE_8)
qImg1 = QImage(frame.data, width, height, QImage.Format_BGR888)
self.changePixmap.emit(qImg1)
self.out.write(frame)
