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# Ultralytics YOLO 🚀, AGPL-3.0 license
import cv2
from ultralytics.utils.checks import check_imshow
from ultralytics.utils.plotting import Annotator
class AIGym:
"""A class to manage the gym steps of people in a real-time video stream based on their poses."""
def __init__(
self,
kpts_to_check,
line_thickness=2,
view_img=False,
pose_up_angle=145.0,
pose_down_angle=90.0,
pose_type="pullup",
):
"""
Initializes the AIGym class with the specified parameters.
Args:
kpts_to_check (list): Indices of keypoints to check.
line_thickness (int, optional): Thickness of the lines drawn. Defaults to 2.
view_img (bool, optional): Flag to display the image. Defaults to False.
pose_up_angle (float, optional): Angle threshold for the 'up' pose. Defaults to 145.0.
pose_down_angle (float, optional): Angle threshold for the 'down' pose. Defaults to 90.0.
pose_type (str, optional): Type of pose to detect ('pullup', 'pushup', 'abworkout'). Defaults to "pullup".
"""
# Image and line thickness
self.im0 = None
self.tf = line_thickness
# Keypoints and count information
self.keypoints = None
self.poseup_angle = pose_up_angle
self.posedown_angle = pose_down_angle
self.threshold = 0.001
# Store stage, count and angle information
self.angle = None
self.count = None
self.stage = None
self.pose_type = pose_type
self.kpts_to_check = kpts_to_check
# Visual Information
self.view_img = view_img
self.annotator = None
# Check if environment supports imshow
self.env_check = check_imshow(warn=True)
def start_counting(self, im0, results, frame_count):
"""
Function used to count the gym steps.
Args:
im0 (ndarray): Current frame from the video stream.
results (list): Pose estimation data.
frame_count (int): Current frame count.
"""
self.im0 = im0
# Initialize count, angle, and stage lists on the first frame
if frame_count == 1:
self.count = [0] * len(results[0])
self.angle = [0] * len(results[0])
self.stage = ["-" for _ in results[0]]
self.keypoints = results[0].keypoints.data
self.annotator = Annotator(im0, line_width=self.tf)
for ind, k in enumerate(reversed(self.keypoints)):
# Estimate angle and draw specific points based on pose type
if self.pose_type in {"pushup", "pullup", "abworkout", "squat"}:
self.angle[ind] = self.annotator.estimate_pose_angle(
k[int(self.kpts_to_check[0])].cpu(),
k[int(self.kpts_to_check[1])].cpu(),
k[int(self.kpts_to_check[2])].cpu(),
)
self.im0 = self.annotator.draw_specific_points(k, self.kpts_to_check, shape=(640, 640), radius=10)
# Check and update pose stages and counts based on angle
if self.pose_type in {"abworkout", "pullup"}:
if self.angle[ind] > self.poseup_angle:
self.stage[ind] = "down"
if self.angle[ind] < self.posedown_angle and self.stage[ind] == "down":
self.stage[ind] = "up"
self.count[ind] += 1
elif self.pose_type in {"pushup", "squat"}:
if self.angle[ind] > self.poseup_angle:
self.stage[ind] = "up"
if self.angle[ind] < self.posedown_angle and self.stage[ind] == "up":
self.stage[ind] = "down"
self.count[ind] += 1
self.annotator.plot_angle_and_count_and_stage(
angle_text=self.angle[ind],
count_text=self.count[ind],
stage_text=self.stage[ind],
center_kpt=k[int(self.kpts_to_check[1])],
)
# Draw keypoints
self.annotator.kpts(k, shape=(640, 640), radius=1, kpt_line=True)
# Display the image if environment supports it and view_img is True
if self.env_check and self.view_img:
cv2.imshow("Ultralytics YOLOv8 AI GYM", self.im0)
if cv2.waitKey(1) & 0xFF == ord("q"):
return
return self.im0
if __name__ == "__main__":
kpts_to_check = [0, 1, 2] # example keypoints
aigym = AIGym(kpts_to_check)
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