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import numpy as np |
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import math |
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from models.pose_estimator.pose_estimator_model_setup import get_pose_estimation |
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def applyFeetApartError(filepath, pose_pred=None, diver_detector=None, pose_model=None): |
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if pose_pred is None and filepath != "": |
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diver_box, pose_pred = get_pose_estimation(filepath, diver_detector=diver_detector, pose_model=pose_model) |
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if pose_pred is not None: |
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pose_pred = np.array(pose_pred)[0] |
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average_knee = [np.mean((pose_pred[4][0], pose_pred[1][0])), np.mean((pose_pred[4][1], pose_pred[1][1]))] |
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vector1 = [pose_pred[5][0] - average_knee[0], pose_pred[5][1] - average_knee[1]] |
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vector2 = [pose_pred[0][0] - average_knee[0], pose_pred[0][1] - average_knee[1]] |
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unit_vector_1 = vector1 / np.linalg.norm(vector1) |
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unit_vector_2 = vector2 / np.linalg.norm(vector2) |
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dot_product = np.dot(unit_vector_1, unit_vector_2) |
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angle = math.degrees(np.arccos(dot_product)) |
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return angle |
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else: |
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return None |
