def sitUpDetect(length):
'''Open folder and process .json into a dict
input: The file path
ouput: The times of push-up
'''
params = dict()
params["model_folder"] = r"E:\Programming\Openpose\openpose\openposePython\models"
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# get video from webcam or video
# start = time.time()
cap_side = cv2.VideoCapture(0)
cap_front = cv2.VideoCapture(1)
# cap2 = cv2.VideoCapture(r'E:\University\科研创新\雏燕计划-体测\体测姿势素材\push-up\push-up-test-1.mp4')
# coorList = []
results = []
tendency = []
tick = []
result = {}
r_waist_angle_list = []
l_waist_angle_list = []
r_s_knee_angle_list = []
l_s_knee_angle_list = []
r_elbowtoneck_dist_list = []
l_elbowtoneck_dist_list = []
total_r_elbowtoneck_dist = 0
total_l_elbowtoneck_dist = 0
cnt = cnt_1 = cnt_2 = 0
sitUp_cnt = 0
start_time = datetime.now()
while True:
# Get images from cam
ret, imageToProcessFront = cap_front.read()
ret, imageToProcessSide = cap_side.read()
cv2.imshow('front', imageToProcessFront)
cv2.imshow('side', imageToProcessSide)
cur_time = datetime.now()
delta_time = (cur_time - start_time).seconds
print('\r倒计时：' + length - delta_time + '秒', end='')
if delta_time == length:
break
if cnt % 2 == 0:
datum1 = op.Datum()
datum2 = op.Datum()
datum1.cvInputData = imageToProcessFront
datum2.cvInputData = imageToProcessSide
opWrapper.emplaceAndPop([datum1])
opWrapper.emplaceAndPop([datum2])
if datum1.poseKeypoints.size != 1 and datum2.poseKeypoints.size != 1:
coor_front = kpp.getKeyPoints(datum1.poseKeypoints[0]) # 记得改参数
coor_side = kpp.getKeyPoints(datum2.poseKeypoints[0])
r_waist_angle = getValue.getWaistAngle(coor_side, 'R')
l_waist_angle = getValue.getWaistAngle(coor_side, 'L')
r_s_knee_angle = getValue.getKneeAngle(coor_side, 'R')
l_s_knee_angle = getValue.getKneeAngle(coor_side, 'L')
r_elbowtoneck_dist = getValue.getElbowToNeckDistance(coor_front, 'R')
l_elbowtoneck_dist = getValue.getElbowToNeckDistance(coor_front, 'L')
if l_waist_angle:
l_waist_angle_list.append(r_waist_angle)
tick.append(l_waist_angle)
# if l_waist_angle:
# l_waist_angle_list.append(l_waist_angle)
if r_s_knee_angle:
r_s_knee_angle_list.append(r_s_knee_angle)
if l_s_knee_angle:
l_s_knee_angle_list.append(l_s_knee_angle)
if r_elbowtoneck_dist:
r_elbowtoneck_dist_list.append(r_elbowtoneck_dist)
cnt_1 += 1
total_r_elbowtoneck_dist += r_elbowtoneck_dist
aver_r_elbowtoneck_dist = total_r_elbowtoneck_dist / cnt_1
if l_elbowtoneck_dist:
l_elbowtoneck_dist_list.append(l_elbowtoneck_dist)
cnt_2 += 1
total_l_elbowtoneck_dist += l_elbowtoneck_dist
aver_l_elbowtoneck_dist = total_l_elbowtoneck_dist / cnt_2
if len(tick) == 5:
tend = analysis.getTendency(tick, 8) # One tick
tick = []
if tend:
tendency.append(tend)
if 3 <= len(tendency):
if tendency[-1] == 'down':
if tendency[-2] == 'upper': # a period and tendency[-3] == 'upper'
sitUp_cnt += 1
result['Num'] = cnt
standard = analysis.sitUpPeriodJudge(
r_waist_angle_list, l_waist_angle_list,
r_s_knee_angle_list, l_s_knee_angle_list,
r_elbowtoneck_dist_list,
l_elbowtoneck_dist_list,
aver_r_elbowtoneck_dist,
aver_l_elbowtoneck_dist)
result['IsRWaistStandard'], result[
'IsLWaistStandard'], result[
'IsRKneeAngle'], result[
'IsLKneeAngle'], result[
'IsRElbowtoNeckStandard'], result[
'IsLElbowtoNeckStandard'], total = standard
# result['Flag'] = i
r_waist_angle_list = l_waist_angle_list = []
r_s_knee_angle_list = l_s_knee_angle_list = []
r_elbowtoneck_dist_list = l_elbowtoneck_dist_list = [] # 序列置空
cnt_1 = cnt_2 = 0
results.append(result)
print(result)
db.ret(delta_time, total, sitUp_cnt, 'sitUp', results, True)
result = {}
cnt += 1
cv2.imshow("OpenPose 1.5.1 - Tutorial Python API", datum1.cvOutputData)
cv2.imshow("OpenPose 1.5.1 - Tutorial Python API - front", datum2.cvOutputData)
if cv2.waitKey(1) == ord('q'):
break
db.ret(None, None, None, None, None, False)
def pullUpDetect(length):
# Process
cnt = 0
results = []
tendency = []
result = {}
r_elbow_angle_list = []
l_elbow_angle_list = []
eye_distance_list = []
tick = []
pullUpCnt = 0
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# get video from webcam or video
start = time.time()
cap = cv2.VideoCapture(0)
cap_t = cv2.VideoCapture(1)
# cap2 = cv2.VideoCapture(r'E:\University\科研创新\雏燕计划-体测\体测姿势素材\push-up\push-up-test-1.mp4')
coorList = []
start_time = datetime.now()
while True:
# Get images from cam
ret, imageToProcess = cap.read()
ret, imageToTest = cap_t.read()
cv2.imshow('video', imageToProcess)
cv2.imshow('2', imageToTest)
cur_time = datetime.now()
delta_time = (cur_time - start_time).seconds
print('\r倒计时：' + length - delta_time + '秒', end='')
if delta_time == length:
break
if cnt % 2 == 0:
datum = op.Datum()
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
if datum.poseKeypoints.size != 1:
coor = kpp.getKeyPoints(datum.poseKeypoints[0])
if coor:
r_elbow_angle = getValue.getElbowAngle(coor, 'R')
l_elbow_angle = getValue.getElbowAngle(coor, 'L')
eye_distance = getValue.getEyeWristDistance(coor)
if l_elbow_angle:
l_elbow_angle_list.append(l_elbow_angle)
if eye_distance:
eye_distance_list.append(eye_distance)
if r_elbow_angle:
r_elbow_angle_list.append(r_elbow_angle)
tick.append(r_elbow_angle)
if len(tick) == 5:
tend = analysis.getTendency(tick, 8) # One tick
tick = []
if tend:
tendency.append(tend)
if 3 <= len(tendency):
if tendency[-1] == 'down' or tendency[
-1] == 'stable':
if tendency[-2] == 'upper' and tendency[
-3] == 'upper': # a period
pullUpCnt += 1
result['Num'] = pullUpCnt
standard = analysis.pullUpPeriodJudge(
r_elbow_angle_list,
l_elbow_angle_list,
eye_distance_list)
result['IsRElbowStandard'], result[
'IsLElbowStandard'], result[
'IsHeightStandard'], total = standard
r_elbow_angle_list = l_elbow_angle_list = eye_distance_list = []
results.append(result)
print(result)
result = {}
db.ret(delta_time, total, pullUpCnt,
'pullUp', results, True)
cv2.imshow("OpenPose 1.5.1 - Tutorial Python API",
datum.cvOutputData)
if cv2.waitKey(1) == ord('q'):
break
cnt += 1
db.ret(None, None, None, None, None, False)
cnt = 0
while True:
# Get images from cam
ret, imageToProcess = cap2.read()
# frame = cv2.flip(frame, 1)
# cv2.imshow('frame', fr5ame)
# print(frame)
# print("type:", type(frame))
if cnt % 2 == 0:
datum = op.Datum()
datum.cvInputData = imageToProcess
opWrapper.emplaceAndPop([datum])
# print(type(datum.poseKeypoints), 'Shape', datum.poseKeypoints.shape)
print("Body keypoints: \n")
# print(datum.poseKeypoints.size)
if datum.poseKeypoints.size != 1:
coor = kpp.getKeyPoints(datum.poseKeypoints[0])
print(coor)
cv2.imshow("OpenPose 1.5.1 - Tutorial Python API", datum.cvOutputData)
if cv2.waitKey(1) == ord('q'):
break
cnt += 1
end = time.time()
print("OpenPose demo successfully finished. Total time: " + str(end - start) + " seconds")
# except Exception as e:
# print(e)
# sys.exit(-1)
def pushUpDetect(length):
# Process
cnt = 0
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# get video from webcam or video
start = time.time()
cap_side = cv2.VideoCapture(0)
cap_front = cv2.VideoCapture(1)
# cap2 = cv2.VideoCapture(r'E:\University\科研创新\雏燕计划-体测\体测姿势素材\push-up\push-up-test-1.mp4')
coorList = []
results = []
tendency = []
result = {}
r_elbow_angle_list = []
l_elbow_angle_list = []
l_knee_angle_list = []
hip_angle_list = []
hip_distance_list = []
tick = []
pushUpCnt = 0
start_time = datetime.now()
while True:
# Get images from cam
ret, imageToProcessFront = cap_front.read()
ret, imageToProcessSide = cap_side.read()
cv2.imshow('front', imageToProcessFront)
cv2.imshow('side', imageToProcessSide)
cnt = 0
cur_time = datetime.now()
delta_time = (cur_time - start_time).seconds
print('\r倒计时：' + length - delta_time + '秒', end='')
if delta_time == length:
break
if cnt % 2 == 0:
datum_front = op.Datum()
datum_side = op.Datum()
datum_front.cvInputData = imageToProcessFront
datum_side.cvInputData = imageToProcessSide
opWrapper.emplaceAndPop([datum_front])
opWrapper.emplaceAndPop([datum_side])
# print("Body keypoints:")
if datum_front.poseKeypoints.size != 1 and datum_side.poseKeypoints.size != 1:
coor_front = kpp.getKeyPoints(
datum_front.poseKeypoints[0]) # 记得改参数
coor_side = kpp.getKeyPoints(datum_side.poseKeypoints[0])
r_elbow_angle = getValue.getElbowAngle(coor_front, 'R')
l_elbow_angle = getValue.getElbowAngle(coor_front, 'L')
l_knee_angle = getValue.getKneeAngle(coor_side, 'L')
hip_angle = getValue.getHipAngle(coor_side, 'L')
hip_distance = getValue.getHipDistance(coor_side, 'L')
if r_elbow_angle:
r_elbow_angle_list.append(r_elbow_angle)
tick.append(r_elbow_angle)
if hip_angle:
hip_angle_list.append(hip_angle)
if l_knee_angle:
l_knee_angle_list.append(l_knee_angle)
if l_elbow_angle:
l_elbow_angle_list.append(l_elbow_angle)
if hip_distance:
hip_distance_list.append(hip_distance)
if len(tick) == 5:
tend = analysis.getTendency(tick, 20) # One tick
print(tend)
tick = []
if tend:
tendency.append(tend)
if 3 <= len(tendency):
if tendency[-1] == 'down' or tendency[
-1] == 'stable':
if tendency[
-2] == 'upper': # a period and tendency[-3] == 'upper'
pushUpCnt += 1
result['Num'] = pushUpCnt
standard = analysis.pushUpPeriodJudgeTwoSides(
r_elbow_angle_list,
l_elbow_angle_list, hip_angle_list,
l_knee_angle_list,
hip_distance_list)
result['IsRElbowStandard'], result[
'IsLElbowStandard'], result[
'IsHipAngleStandard'], result[
'IsRKneeStandard'], result[
'IsHipDistanceStandard'], total = standard
r_elbow_angle_list = []
l_elbow_angle_list = []
l_knee_angle_list = []
hip_angle_list = []
hip_distance_list = []
pushUpCnt += 1
results.append(result)
print(result)
result = {}
db.ret(delta_time, total, pushUpCnt,
'pushUp', results, True)
cnt += 1
cv2.imshow("front", datum_front.cvOutputData)
cv2.imshow("side", datum_side.cvOutputData)
if cv2.waitKey(1) == ord('q'):
break
db.ret(None, None, None, None, None, False)