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import sys
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sys.path.append('./Evaluation')
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from eval_detection_gentime import ANETdetection
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import matplotlib.pyplot as plt
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import numpy as np
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def run_evaluation_detection(opt, ground_truth_filename, prediction_filename,
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tiou_thresholds=np.linspace(0.5, 0.95, 10),
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subset='validation', verbose=True):
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anet_detection = ANETdetection(opt, ground_truth_filename, prediction_filename,
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subset=subset, tiou_thresholds=tiou_thresholds,
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verbose=verbose, check_status=False)
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anet_detection.evaluate()
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ap = anet_detection.ap
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mAP = anet_detection.mAP
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tdiff = anet_detection.tdiff
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return (mAP, ap, tdiff)
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def evaluation_detection(opt, verbose=True):
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mAP, AP, tdiff = run_evaluation_detection(
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opt,
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opt["video_anno"].format(opt["split"]),
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opt["result_file"].format(opt['exp']),
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tiou_thresholds=np.linspace(0.1, 0.50, 5),
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subset=opt['inference_subset'], verbose=verbose)
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if verbose:
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print('mAP')
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print(mAP)
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print('AEDT')
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print(tdiff)
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return mAP
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