def evaluate_side_bicepcurl(self, frames: List[pose.PoseData]):
side = detect_perspective(frames)
# Angles to calculate
upper_arm_lower_arm_angles = []
upper_arm_torso_angles = []
for frame in frames:
if (side == pose.Side.right):
upper_arm = pose.Part(frame.relbow, frame.rshoulder)
lower_arm = pose.Part(frame.relbow, frame.rwrist)
torso = pose.Part(frame.rhip, frame.neck)
else:
upper_arm = pose.Part(frame.lelbow, frame.lshoulder)
lower_arm = pose.Part(frame.lelbow, frame.lwrist)
torso = pose.Part(frame.lhip, frame.neck)
upper_arm_lower_arm_angle = upper_arm.calculate_angle(lower_arm)
upper_arm_torso_angle = upper_arm.calculate_angle(torso)
upper_arm_lower_arm_angles.append(upper_arm_lower_arm_angle)
upper_arm_torso_angles.append(upper_arm_torso_angle)
# use thresholds learned from analysis
upper_arm_torso_range = np.max(upper_arm_torso_angles) - np.min(
upper_arm_torso_angles)
upper_arm_lower_arm_min = np.min(upper_arm_lower_arm_angles)
# print('Upper arm and torso angle range: {}'.format(upperarm_torso_range))
# print('Upper arm and forearm minimum angle: {}'.format(upperarm_forearm_min))
correct = True
feedback = ''
if upper_arm_torso_range > 35.0:
correct = False
feedback += 'Significant rotation in upper arm while curling\n'
if upper_arm_lower_arm_min > 45.0:
correct = False
feedback += 'Curling not performed all the way to the top\n'
if correct:
feedback += 'Correctly performed\n'
# print('-'*30)
# print('Exercise correct: '+str(correct))
# print(feedback)
return (correct, feedback)
def evaluate_frame(self, frame: pose.PoseData):
self.frames.append(frame)
# @TODO we need to calculate this only once
side = detect_perspective([frame])
upper_arm_lower_arm_angle, upper_arm_torso_angle = self.evaluate_angle_per_frame(
frame, side)
################# Reps counter and feedback logic ###########################
# rep is still proceeding in downward direction
if (not self.down_exited and
upper_arm_lower_arm_angle < self.start_angle - self.threshold):
self.frames_elapsed = 0
self.down_exited = True
if (self.down_exited):
self.frames_elapsed += 1
# for feedback purpose
if (self.start_angle - self.threshold <= upper_arm_lower_arm_angle <=
self.start_angle + self.threshold):
# @TODO need to check it later, hardcoded value
if (self.down_exited and self.frames_elapsed > 20):
# 1 rep completed
# print(upper_arm_lower_arm_angle)
self.correct, feedback = self.evaluate_side_bicepcurl(
self.frames)
if (self.correct):
self.reps += 1
else:
self.reps_incorrect += 1
self.feedbacks.append(feedback)
# Ahoy new reps begin
self.frames = []
print(feedback)
print(self.reps)
print(self.reps_incorrect)
self.initial_frame = self.frame_index
self.down_exited = False
self.frames_elapsed = 0
def on_file_change(*args):
global video, side, active_file, cap, initial_frame, start_angle, end_angle, threshold, down, down_exited, frame_index
global reps, reps_incorrect, frames_elapsed, feedback, frame_index
active_file = variable.get()
video = parser.parse_file(root_dir + '/' + active_file, False)
cap.release()
cap = cv2.VideoCapture(f'demo/video/{active_file.split(".")[0]}.mp4')
if (cap.isOpened() == False):
print("Error")
initial_frame = 0 # start of each reps
start_angle = 160 # intial position defined
end_angle = 40 # final position of arm
threshold = 10
down = False # to check whether the arm is in down region
down_exited = False # to check whether arm exited down region
reps = 0 # to count the number of reps in exercise
reps_incorrect = 0 # to counf the incorrect reps
frames_elapsed = 0
feedback = ""
frame_index = 0
side = parser.detect_perspective(video)
root.title(active_file)
print(active_file)
def evaluate_side_shoulderpress(frames: List[pose.PoseData]):
side = detect_perspective(frames)
upperarm_forearm_angles = []
upperarm_torso_angles = []
back_vectors = []
elbow_neck_x = []
for frame in frames:
# IGnore all the 0 confidence frames
if (side == pose.Side.right):
if (frame.relbow.confidence == 0 or frame.rshoulder.confidence == 0
or frame.rwrist.confidence == 0
or frame.rhip.confidence == 0
or frame.neck.confidence == 0):
continue
else:
if (frame.lelbow.confidence == 0 or frame.lshoulder.confidence == 0
or frame.lwrist.confidence == 0
or frame.lhip.confidence == 0
or frame.neck.confidence == 0):
continue
if (side == pose.Side.right):
upperarm = pose.Part(frame.relbow, frame.rshoulder)
forearm = pose.Part(frame.relbow, frame.rwrist)
torso = pose.Part(frame.rhip, frame.neck) # Or back
# elbow_neck = pose.Part(frame.neck, frame.relbow)
back_vectors.append(
np.array(
[frame.neck.x - frame.rhip.x,
frame.neck.y - frame.rhip.y]))
elbow_neck_x.append(frame.relbow.x - frame.neck.x)
else:
upperarm = pose.Part(frame.lelbow, frame.lshoulder)
forearm = pose.Part(frame.lelbow, frame.lwrist)
torso = pose.Part(frame.lhip, frame.neck)
# elbow_neck = pose.Part(frame.lelbow, frame.neck)
back_vectors.append(
np.array(
[frame.neck.x - frame.lhip.x,
frame.neck.y - frame.lhip.y]))
elbow_neck_x.append(frame.neck.x - frame.lelbow.x)
angle1 = upperarm.calculate_angle(forearm)
angle2 = upperarm.calculate_angle(torso)
upperarm_forearm_angles.append(angle1)
upperarm_torso_angles.append(angle2)
##### Angle cleanup ############
upperarm_forearm_angles = np.array(upperarm_forearm_angles)
upperarm_forearm_angles = upperarm_forearm_angles[np.logical_not(
np.isnan(upperarm_forearm_angles))]
upperarm_torso_angles = np.array(upperarm_torso_angles)
upperarm_torso_angles = upperarm_torso_angles[np.logical_not(
np.isnan(upperarm_torso_angles))]
back_vectors = np.array(back_vectors)
### Calculation of required parameters #################
max_upperarm_forearm_angle = np.max(upperarm_forearm_angles)
back_vector_range = np.max(back_vectors, axis=0) - \
np.min(back_vectors, axis=0)
elbow_x = np.min(elbow_neck_x) # Only x axis
print(elbow_x)
correct = True
feedback = ""
if (max_upperarm_forearm_angle < 175):
correct = False
feedback += "Not lifted upto the top. \n"
if (back_vector_range[0] > 0.16):
correct = False
feedback += "Back shows significant movement. \n"
if (elbow_x < -0.12):
correct = False
feedback += "Shoulders are not steady/parallel. \n"
return (correct, feedback)
down = False # to check whether the arm is in down region
down_exited = False # to check whether arm exited down region
reps = 0 # to count the number of reps in exercise
reps_incorrect = 0 # to counf the incorrect reps
frames_elapsed = 0
feedback = ""
frame_index = 0
cv_default_font = cv2.FONT_HERSHEY_PLAIN
font_size = 1
video = []
while (True):
keypoint, img = wrapper.calculate_frame()
frame = parse_single_frame(keypoint[0])
video.append(frame)
side = detect_perspective([frame])
output = evaluate_angle_per_frame(frame, side)
angle1 = output["a1"]
angle2 = output["a2"]
################# Reps counter and feedback logic ###########################
if (not down_exited and angle1 < start_angle - threshold):
frames_elapsed = 0
down_exited = True
if (down_exited):
frames_elapsed += 1
if (start_angle - threshold <= angle1 <= start_angle + threshold):
if (down_exited and frames_elapsed > 20):
# 1 rep completed
print(angle1)
# cv.imwrite("frame%d.jpg" % i, image)
break
if k == ord('c'):
is_video_good = not is_video_good
index = 0
if k == ord('n'):
video_index += 1
index = 0
if k == ord('p'):
video_index -= 1
index = 0
# Main logic
if is_video_good:
video_index = abs(video_index % len(good_videos))
video = good_videos[video_index]
side = detect_perspective(video)
current_type = "Good"
else:
video_index = abs(video_index % len(bad_videos))
video = bad_videos[video_index]
side = detect_perspective(video)
current_type = "Bad"
frame = video[index]
# Angle
if (side == pose.Side.right):
upperarm = pose.Part(frame.relbow, frame.rshoulder)
forearm = pose.Part(frame.relbow, frame.rwrist)
torso = pose.Part(frame.rhip, frame.neck)
else:
def visualize_vid(path):
# Create a black image
#img = np.zeros((600, 1200, 3), np.uint8)
# Draw a diagonal blue line with thickness of 5 px
# cv.line(img, (0, 0), (511, 511), (255, 0, 0), 5)
# cv.circle(img, (447, 63), 63, (0, 0, 255), -1)
video = parse_file(path, False)
side = detect_perspective(video)
index = 0
cap = cv.VideoCapture('videos/bicep_6.mp4')
if(cap.isOpened()==False):
print("Error")
i = 0 # to count the frame
initial_frame = i #start of each reps
start_angle = 160 #intial position defined
end_angle = 40 # final position of arm
threshold = 10
down = False #to check whether the arm is in down region
up = False #to check whether the arm is in upward region
down_exited = False # to check whether arm exited down region
reps = 0 # to count the number of reps in exercise
reps_incorrect = 0 # to counf the incorrect reps
start = False
angles = []
frames_elapsed = 0
while(cap.isOpened()):
ret, image = cap.read()
frame = video[i]
# User input
k = cv.waitKey(1) & 0xFF
if k == 27:
break
if ret==False:
break
if(k == 'p'):
cv.waitKey(0)
# Angle
if (side == pose.Side.right):
upperarm = pose.Part(frame.relbow, frame.rshoulder)
forearm = pose.Part(frame.relbow, frame.rwrist)
torso = pose.Part(frame.rhip, frame.neck)
else:
upperarm = pose.Part(frame.lelbow, frame.lshoulder)
forearm = pose.Part(frame.lelbow, frame.lwrist)
torso = pose.Part(frame.lhip, frame.neck)
angle1 = upperarm.calculate_angle(forearm)
angle2 = upperarm.calculate_angle(torso)
angles.append(angle1)
#Reps counter
if (not down_exited and angle1 < start_angle-threshold):
print(i)
frames_elapsed = 0
down_exited = True
if (down_exited):
frames_elapsed += 1
if (start_angle-threshold <= angle1 <= start_angle+threshold):
if (down_exited and frames_elapsed > 20):
print(angle1)
# cv.imwrite("frame%d.jpg" % i, image)
correct, feedback = evaluate_side_bicepcurl(video[initial_frame:i])
if (correct):
reps += 1
else:
reps_incorrect += 1
# print(initial_frame,i)
# print(feedback)
initial_frame = i
down_exited = False
frames_elapsed = 0
# #Lower region
# if (start_angle-threshold <= angle1 <= start_angle+threshold):
# down = True
# if (down and down_exited):
# # reps += 1
# down = False
# down_exited = False
# start = True
# correct, feedback = evaluate_side_bicepcurl(video[initial_frame:i])
# if (correct):
# reps += 1
# else:
# reps_incorrect += 1
# # print(initial_frame,i)
# initial_frame = i
# # print(reps,feedback)
# # if (down and up):
# # reps += 1
# # final_frame = i
# # down = False
# # up = False
# # feedback = evaluate_bicepcurl (video[initial_frame:final_frame])
# # print(feedback)
# # initial_frame = i
# # #Upper region
# # if (end_angle-threshold <= angle1 <= end_angle+threshold):
# # up = True
# #Downward region exit
# if (down and angle1<start_angle-threshold):
# down_exited = True
# if (start and down and angle1<start_angle-threshold):
# # print(i)
# print(initial_frame, i)
# start = False
# index_min = np.argmin(angles[initial_frame:i])+initial_frame
# print(initial_frame, index_min)
# initial_frame = index_min
# Drawing
cv.putText(image, f"{path} {index}", (250, 20), cv.FONT_HERSHEY_PLAIN,
2, (255, 255, 255), 1)
cv.putText(image, f"Angle upperarm forearm: {angle1}", (10, 50), cv.FONT_HERSHEY_PLAIN,
2, (255, 255, 255), 1)
cv.putText(image, f"Angle upperarm torso: {angle2}", (10, 80), cv.FONT_HERSHEY_PLAIN,
2, (255, 255, 255), 1)
cv.putText(image, f"Reps: {reps}", (10, 110), cv.FONT_HERSHEY_PLAIN,
2, (0, 255, 0), 1)
cv.putText(image, f"Reps incorrect: {reps_incorrect}", (10, 140), cv.FONT_HERSHEY_PLAIN,
2, (0, 0, 255), 1)
for name, joint in frame:
x = int(joint.x)
y = int(joint.y)
cv.circle(image, (x, y), 5, (0, 0, 255), -1)
# cv.putText(image, name, (x, y-10), cv.FONT_HERSHEY_SIMPLEX,
# 0.6, (36, 255, 12), 2)
# Update
# time.sleep(0.04)
i = i+1
cv.imshow('Testing', image)
cv.destroyAllWindows()