czming

# columns in the data that you want to visualize (visualize each column's value along the rows, where the row number is the x-axis)
VISUALIZED_COLUMNS = [0, -1, -2, -3, -4]

# show visualization of data, change to only one column (second argument) if only want to visualize current set of data instead of contrasting pre- vs post-filtering
fig, axs = plt.subplots(len(VISUALIZED_COLUMNS), 2)

for i, column in enumerate(VISUALIZED_COLUMNS):
    old_data = data[:, column]
    # plot pre-filtered data
    axs[i, 0].plot(range(len(data)), old_data)

czming

# pick bin dimensions in the vector [aruco_marker[:72], color_bins[72:92], optical_flow_avg[92:94], hand_loc[94:96]]
pick_bins = [i for i in range(24 * 2)]
place_bins = [i for i in range(24 * 2, 36 * 2)]

for i in range(1,41):
    with open(f"htk_inputs_aruco/picklist_{i}.txt") as infile:
        infile = infile.readlines()
        for line in infile:
            line = line.split()
            aruco_markers = line[:72]

czming

import glob

files = glob.glob("*_raw.txt")

for file in files:
    with open(file, "r") as infile:
        phrase = infile.read().strip()
    with open(file.replace("_raw.txt", "_place.lab"), "w") as outfile:
        #prepend sil for HTK formatting
        outfile.write("sil\n")