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- import numpy as np
- import os
- AU = ["Person", "Case", "Confidence", "AU01", "AU02", "AU04", "AU05", "AU06", "AU07", "AU09","AU10","AU12","AU14","AU15","AU17","AU20","AU23",
- "AU25","AU26", "AU45"]
- # folder where output csv files of OpenFace are stored
- folder = '/home/valapil/Project/ForkCausal_Adithya/csv_files'
- csv_files = [file for file in os.listdir(folder) if file.endswith('.csv')]
- # load the offset values
- offset = np.load(f'/home/valapil/Project/ForkCausal_Adithya/offset_values.npy')
- length = {}
- same = np.unique(offset[1:, 0])
- for i in same:
- same_rows = offset[offset[:, 0] == i]
- length[i] = max(abs(int(same_rows[0][2]) - int(same_rows[0][1])), abs(int(same_rows[1][2]) - int(same_rows[1][1])))
- for file in csv_files:
- base_name, extension = os.path.splitext(file)
- new_name = base_name.split('.')[0]
- f1 = new_name[:-2]
- f2 = new_name[-1:]
- file_path = os.path.join(folder, file)
- len = length[new_name[:-3] + new_name[-1]]
- start = np.where(offset[1:, 3] == new_name)[0][0]
- start = int(offset[start+1, 1])
- data_all = np.genfromtxt(file_path, delimiter=',', skip_header=1)
- data = data_all[start:len-200, 679:696]
- selected_columns = np.hstack((np.full((data.shape[0], 2), [f1, f2]), data_all[start:len-200, [3]], data))
- AU = np.row_stack((AU, selected_columns))
- # save each offset data here
- np.save(f'/home/valapil/Project/ForkCausal_Adithya/data/{new_name}.npy', data)
- # save all offset data with the particular case and confidence value here
- np.save(f'/home/valapil/Project/ForkCausal_Adithya/processed_data.npy', AU)
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