data_dirs = {
    't_data': [('./data/Translation/Y1/', 'trans_1'),
               ('./data/Translation/Y2/', 'trans_2'),
               ('./data/Translation/Y3/', 'trans_3'),
               ('./data/Translation/Y4/', 'trans_4')],
    'p_data': [('./data/Pitch/d1_-40/', 'pitch_1'),
               ('./data/Pitch/d2_-37/', 'pitch_2'),
               ('./data/Pitch/d3_-34/', 'pitch_3'),
               ('./data/Pitch/d4_-31/', 'pitch_4')],
    'y_data': [('./data/Yaw/d1_44/', 'yaw_1'), ('./data/Yaw/d2_41/', 'yaw_2'),
               ('./data/Yaw/d3_38/', 'yaw_3'), ('./data/Yaw/d4_35/', 'yaw_4')],
    'v_data': [('./data/RV_Data2/', 'vid')]
}

if frame_1 == 0 and (data_file != 'V' and data_file != 'v'):
    data_set_1 = dat.Dataset(data_dirs[which_data][frame_1])
    frame_text = "Translation Image"

    if frame_2 != 0:
        data_set_2 = dat.Dataset(data_dirs[which_data][frame_2])
        for i in range(len(data_set_1.data)):
            #while True:
            frame_1 = data_set_1.next_entry()
            frame_2 = data_set_2.next_entry()
            # if data_file == 'P' or data_file == 'p'
            frame_1.amplitude[frame_1.amplitude == 65533] = 0
            frame_2.amplitude[frame_2.amplitude == 65533] = 0
            frame_1.amplitude = gaussian_filter(frame_1.amplitude,
                                                sigma=sigma_val)
            frame_1.x = gaussian_filter(frame_1.x, sigma=sigma_val)
            frame_1.y = gaussian_filter(frame_1.y, sigma=sigma_val)
示例#2
0
    'trans': [('./data/Translation/Y1/', 'trans_1'),
              ('./data/Translation/Y2/', 'trans_2'),
              ('./data/Translation/Y3/', 'trans_3'),
              ('./data/Translation/Y4/', 'trans_4')],
    'pitch': [('./data/Pitch/d1_-40/', 'pitch_1'),
              ('./data/Pitch/d2_-37/', 'pitch_2'),
              ('./data/Pitch/d3_-34/', 'pitch_3'),
              ('./data/Pitch/d4_-31/', 'pitch_4')],
    'yaw': [('./data/Yaw/d1_44/', 'yaw_1'), ('./data/Yaw/d2_41/', 'yaw_2'),
            ('./data/Yaw/d3_38/', 'yaw_3'), ('./data/Yaw/d4_35/', 'yaw_4')],
    'video': [('./data/RV_Data2/', 'vid')]
}

if T >= 0 or P >= 0 or Y >= 0:
    if T >= 0:
        data_set = data.Dataset(data_dirs['trans'][T])
        frame_text = "Translation Image"
    elif P >= 0:
        data_set = data.Dataset(data_dirs['pitch'][P])
        frame_text = "Pitch Image"
    elif Y >= 0:
        data_set = data.Dataset(data_dirs['yaw'][Y])
        frame_text = "Yaw Image"

    # ####image display
    img = np.zeros_like(data_set.data[0].amplitude)
    img = np.float32(img)
    if avg == 1:
        frame_text += ": averaged"
        i = 0
        for frame in data_set.data:
    # print("Previous threshold value: ", ransac_thresh)
    # ransac_thresh = float(input("Enter threshold value: "))

    all_pitch = []
    all_yaw = []
    all_roll = []
    all_x = []
    all_y = []
    all_z = []

    data_dirs = {'v_data': [('./data/RV_Data2/', 'vid')]}

    if data_file == 'V' or data_file == 'v':
        frame_text = "Video Run"

    data_set_1 = data.Dataset(data_dirs[which_data][loc_1])
    for frame_1 in data_set_1.data:
        frame_1.x = -1 * frame_1.x
        temp_y1 = frame_1.y
        frame_1.y = frame_1.z
        frame_1.z = temp_y1

        frame_1.amplitude[frame_1.amplitude > 250] = 0  # adjust maximum
        frame_1.amplitude[frame_1.amplitude == 0] = np.max(frame_1.amplitude)

        frame_1.amplitude = gaussian_filter(frame_1.amplitude, sigma=sigma_val)  # start gaussian filter
        frame_1.x = gaussian_filter(frame_1.x, sigma=sigma_val)
        frame_1.y = gaussian_filter(frame_1.y, sigma=sigma_val)
        frame_1.z = gaussian_filter(frame_1.z, sigma=sigma_val)

    # print("Dataset Length: ", len(data_set_1.data))