29 lines
1.4 KiB
Python
Executable File
29 lines
1.4 KiB
Python
Executable File
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import numpy as np
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def thumos_postprocessing(ground_truth, prediction, smooth=False, switch=False):
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"""
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We follow (Shou et al., 2017) and adopt their perframe postprocessing method on THUMOS'14 datset.
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Source: https://bitbucket.org/columbiadvmm/cdc/src/master/THUMOS14/eval/PreFrameLabeling/compute_framelevel_mAP.m
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"""
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# Simple temporal smoothing via NMS of 5-frames window
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if smooth:
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prob = np.copy(prediction)
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prob1 = prob.reshape(1, prob.shape[0], prob.shape[1])
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prob2 = np.append(prob[0, :].reshape(1, -1), prob[0: -1, :], axis=0).reshape(1, prob.shape[0], prob.shape[1])
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prob3 = np.append(prob[1:, :], prob[-1, :].reshape(1, -1), axis=0).reshape(1, prob.shape[0], prob.shape[1])
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prob4 = np.append(prob[0: 2, :], prob[0: -2, :], axis=0).reshape(1, prob.shape[0], prob.shape[1])
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prob5 = np.append(prob[2:, :], prob[-2:, :], axis=0).reshape(1, prob.shape[0], prob.shape[1])
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probsmooth = np.squeeze(np.max(np.concatenate((prob1, prob2, prob3, prob4, prob5), axis=0), axis=0))
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prediction = np.copy(probsmooth)
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# Assign cliff diving (5) as diving (8)
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if switch:
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switch_index = np.where(prediction[:, 5] > prediction[:, 8])[0]
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prediction[switch_index, 8] = prediction[switch_index, 5]
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# Remove ambiguous (21)
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valid_index = np.where(ground_truth[:, 21] != 1)[0]
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return ground_truth[valid_index], prediction[valid_index] |