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Update PP-Radar.md to reflect on norm steps.
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PP-Radar.md

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@@ -447,6 +447,11 @@ points = np.fromfile(str(lidar_file), dtype=np.float32).reshape(-1, number_of_ch
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means = [0, 0, 0, 0, 0, 0, 0] # 'x', 'y', 'z', 'rcs', 'v_r', 'v_r_comp', 'time'
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stds = [1, 1, 1, 1, 1, 1, 1] # 'x', 'y', 'z', 'rcs', 'v_r', 'v_r_comp', 'time'
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#in practice, you should use either train, or train+val values to calculate mean and stds. Note that x, y, z, and time are not normed, but you can experiment with that.
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#means = [0, 0, 0, mean_RCS (~ -13.0), mean_v_r (~-3.0), mean_vr_comp (~ -0.1), 0] # 'x', 'y', 'z', 'rcs', 'v_r', 'v_r_comp', 'time'
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#stds = [1, 1, 1, std_RCS (~14.0), std_v_r (~8.0), std_v_r_comp (~6.0), 0] # 'x', 'y', 'z', 'rcs', 'v_r', 'v_r_comp', 'time'
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#we then norm the channels
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points = (points - means)/stds
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