34 lines
1.4 KiB
Python
34 lines
1.4 KiB
Python
from utils.embedding import DataProcessing as dp
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from floder.config import cfg
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import cv2 as cv
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from utils.filter import filt
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from network.vanalysis_video import vanalysis, raft_init_model
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import argparse
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from utils.detect import opvideo
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parser = argparse.ArgumentParser()
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#parser.add_argument('--model', default='../module/ieemoo-ai-search/model/now/raft-things.pth',help="restore checkpoint")
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parser.add_argument('--model', default='./checkpoint/raft-small.pth',help="restore checkpoint")
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#parser.add_argument('--small', action='store_true', help='use small model')
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parser.add_argument('--small', type=bool, default=True, help='use small model')
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parser.add_argument('--mixed_precision', action='store_true', help='use mixed precision')
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parser.add_argument('--alternate_corr', action='store_true', help='use efficent correlation implementation')
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opt, unknown = parser.parse_known_args()
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backbone = 'mobilevit'
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modelPath = cfg.model_path
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device = 'cuda'
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dps = dp(backbone, modelPath, device)
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flowmodel = raft_init_model(opt)
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opv = opvideo(flowmodel , dps)
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if __name__ == '__main__':
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video1 = './imgs/1.mp4'
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video2 = './imgs/2.mp4'
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video3 = './imgs/3.mp4'
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video4 = './imgs/4.mp4'
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opv.addFeature('test', 0, video1)
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opv.addFeature('test', 1, video2)
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opv.addFeature('test', 2, video3)
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result = opv.opFeature('test', 3, video4)
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print('result>>>>> {}'.format(result))
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