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import numpy as np
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def non_max_suppression(proposals, overlapThresh=0.3):
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if len(proposals) == 0:
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return []
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pick = []
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sorted_proposal = sorted(proposals, key=lambda proposal:proposal['score'], reverse=True)
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idx=0
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total_proposal= len(sorted_proposal)
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while idx < total_proposal:
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proposal = sorted_proposal[idx]
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st = proposal['segment'][0]
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ed = proposal['segment'][1]
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label = proposal['label']
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delete_item = []
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for j in range(idx+1, total_proposal):
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target_proposal = sorted_proposal[j]
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target_st = target_proposal['segment'][0]
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target_ed = target_proposal['segment'][1]
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target_label = target_proposal['label']
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if(label == target_label):
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sst = np.minimum(st, target_st)
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led = np.maximum(ed, target_ed)
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lst = np.maximum(st, target_st)
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sed = np.minimum(ed, target_ed)
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iou = (sed-lst) / max(led-sst,1)
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if(iou > overlapThresh):
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delete_item.append(target_proposal)
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for item in delete_item:
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sorted_proposal.remove(item)
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total_proposal=len(sorted_proposal)
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idx+=1
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return sorted_proposal
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def check_overlap_proposal(proposal_list, new_proposal, overlapThresh=0.3):
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for proposal in proposal_list:
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st = proposal['segment'][0]
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ed = proposal['segment'][1]
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label = proposal['label']
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new_st = new_proposal['segment'][0]
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new_ed = new_proposal['segment'][1]
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new_label = new_proposal['label']
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if(label == new_label):
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sst = np.minimum(st, new_st)
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led = np.maximum(ed, new_ed)
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lst = np.maximum(st, new_st)
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sed = np.minimum(ed, new_ed)
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iou = (sed-lst) / max(led-sst,1)
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if(iou > overlapThresh):
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return proposal
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return None
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