Pose Estimation script V1

Modules/PoseEstimation/pose_estimator.py

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+from ultralytics import YOLO
+import numpy as np
+
+id_joints_dict = {0: 'nose',
+        1: 'left_eye',
+        2: 'right_eye',
+        3: 'left_ear',
+        4: 'right_ear',
+        5: 'left_shoulder',
+        6: 'right_shoulder',
+        7: 'left_elbow',
+        8: 'right_elbow',
+        9: 'left_wrist',
+        10: 'right_wrist',
+        11: 'left_hip',
+        12: 'right_hip',
+        13: 'left_knee',
+        14: 'right_knee',
+        15: 'left_ankle',
+        16: 'right_ankle'}
+joints_id_dict = {v: k for k, v in id_joints_dict.items()}
+
+model = YOLO('yolov8n-pose.pt')
+
+def get_keypoints_from_keypoints(model, video_path):
+
+    keypoints = []
+    results = model(video_path, save=True, show_conf=False, show_boxes=False)
+    for frame in results:
+        keypoints.append(frame.keypoints.xy)
+
+    return keypoints
+
+keypoints = get_keypoints_from_keypoints(model, '../../data/pose/squat.mp4')
+
+def calculate_angle(a, b, c):
+
+    """
+    Calculates the angle between three joints.
+
+    Args:
+        a (tuple): coordinates of the first joint
+        b (tuple): coordinates of the second joint
+        c (tuple): coordinates of the third joint
+
+    Returns:
+        angle (float): angle between the three joints
+    """
+    
+    ba = np.array(a) - np.array(b)
+    bc = np.array(c) - np.array(b)
+
+    cosine_angle = np.dot(ba, bc) / (np.linalg.norm(ba) * np.linalg.norm(bc))
+    angle = np.arccos(cosine_angle)
+
+    return np.degrees(angle)
+
+def compute_left_knee_angle(pose):
+
+    """
+    Computes the knee angle.
+
+    Args:
+        pose (dict): pose dictionary
+
+    Returns:
+        knee_angle (float): knee angle
+    """
+
+    left_hip = pose[0][joints_id_dict['left_hip']]
+    left_knee = pose[0][joints_id_dict['left_knee']]
+    left_ankle = pose[0][joints_id_dict['left_ankle']]
+
+    knee_angle = calculate_angle(left_hip, left_knee, left_ankle)
+
+    return knee_angle
+
+def compute_right_knee_angle(pose):
+
+    """
+    Computes the knee angle.
+
+    Args:
+        pose (dict): pose dictionary
+
+    Returns:
+        knee_angle (float): knee angle
+    """
+
+    right_hip = pose[0][joints_id_dict['right_hip']]
+    right_knee = pose[0][joints_id_dict['right_knee']]
+    right_ankle = pose[0][joints_id_dict['right_ankle']]
+
+    knee_angle = calculate_angle(right_hip, right_knee, right_ankle)
+
+    return knee_angle
+
+def moving_average(data, window_size):
+
+    """
+    Computes the moving average of a list.
+
+    Args:
+        data (list): list of values
+        window_size (int): size of the window
+
+    Returns:
+        avg (list): list of moving average values
+    """
+
+    avg = []
+    for i in range(len(data) - window_size + 1):
+        avg.append(sum(data[i:i + window_size]) / window_size)
+
+    return avg
+

config.py

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+# Pose estimation
+
+pose_mode_size = 'm'