Multimodal_Demo / models /kts_model.py
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import torch
import numpy as np
from models.kts_src.kts_utils import cpd_auto, l2_normalize_np_array
class VideoSegmentor:
def __init__(self, alpha, beta):
self.alpha = alpha
self.beta = beta
def __call__(self, video_features, video_length):
K = l2_normalize_np_array(video_features)
K = np.dot(K, K.T)
clip_num = K.shape[0]
max_seg_num = clip_num // self.alpha
cps, _ = cpd_auto(K, max_seg_num - 1, 0)
seg_num = len(cps) + 1
seg_points = [x * self.beta for x in cps]
seg_points = np.insert(seg_points, 0, 0)
seg_points = np.append(seg_points, video_length)
seg_windows = [[int(seg_points[i]), int(seg_points[i+1])] for i in range(seg_num)]
return seg_windows