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import argparse
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import os
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import os.path as osp
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import mmengine
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import numpy as np
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from mmaction.evaluation import ActivityNetLocalization
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args = None
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def cuhk17_top1():
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"""Assign label for each proposal with the cuhk17 result, which is the #2
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entry in http://activity-net.org/challenges/2017/evaluation.html."""
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if not osp.exists('cuhk_anet17_pred.json'):
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os.system('wget https://download.openmmlab.com/'
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'mmaction/localization/cuhk_anet17_pred.json')
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proposal = mmengine.load(args.proposal)
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results = proposal['results']
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cuhk_pred = mmengine.load('cuhk_anet17_pred.json')['results']
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def get_topk(preds, k):
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preds.sort(key=lambda x: x['score'])
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return preds[-k:]
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for k, v in results.items():
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action_pred = cuhk_pred[k]
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top1 = get_topk(action_pred, 1)
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top1_label = top1[0]['label']
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new_value = []
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for item in v:
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x = dict(label=top1_label)
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x.update(item)
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new_value.append(x)
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results[k] = new_value
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proposal['results'] = results
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mmengine.dump(proposal, args.det_output)
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cls_funcs = {'cuhk17_top1': cuhk17_top1}
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def parse_args():
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parser = argparse.ArgumentParser(description='Report detection mAP for'
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'ActivityNet proposal file')
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parser.add_argument('--proposal', type=str, help='proposal file')
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parser.add_argument(
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'--gt',
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type=str,
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default='data/ActivityNet/'
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'anet_anno_val.json',
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help='groundtruth file')
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parser.add_argument(
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'--cls',
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type=str,
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default='cuhk17_top1',
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choices=['cuhk17_top1'],
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help='the way to assign label for each '
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'proposal')
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parser.add_argument(
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'--det-output',
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type=str,
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default='det_result.json',
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help='the path to store detection results')
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args = parser.parse_args()
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return args
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def main():
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global args, cls_funcs
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args = parse_args()
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func = cls_funcs[args.cls]
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func()
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anet_detection = ActivityNetLocalization(
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args.gt,
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args.det_output,
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tiou_thresholds=np.linspace(0.5, 0.95, 10),
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verbose=True)
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mAP, average_mAP = anet_detection.evaluate()
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print('[RESULTS] Performance on ActivityNet detection task.\n'
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f'mAP: {mAP}\nAverage-mAP: {average_mAP}')
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if __name__ == '__main__':
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main()
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