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  1. 00160/img-mean-std-00160029.npy +3 -0
  2. 00160/img-mean-std-00160052.npy +3 -0
  3. 00160/img-mean-std-00160083.npy +3 -0
  4. 00160/img-mean-std-00160084.npy +3 -0
  5. 00160/img-mean-std-00160171.npy +3 -0
  6. 00160/img-mean-std-00160176.npy +3 -0
  7. 00160/img-mean-std-00160261.npy +3 -0
  8. 00160/img-mean-std-00160266.npy +3 -0
  9. 00160/img-mean-std-00160339.npy +3 -0
  10. 00160/img-mean-std-00160342.npy +3 -0
  11. 00160/img-mean-std-00160345.npy +3 -0
  12. 00160/img-mean-std-00160393.npy +3 -0
  13. 00160/img-mean-std-00160394.npy +3 -0
  14. 00160/img-mean-std-00160433.npy +3 -0
  15. 00160/img-mean-std-00160434.npy +3 -0
  16. 00160/img-mean-std-00160448.npy +3 -0
  17. 00160/img-mean-std-00160499.npy +3 -0
  18. 00160/img-mean-std-00160510.npy +3 -0
  19. 00160/img-mean-std-00160517.npy +3 -0
  20. 00160/img-mean-std-00160600.npy +3 -0
  21. 00160/img-mean-std-00160607.npy +3 -0
  22. 00160/img-mean-std-00160723.npy +3 -0
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  24. 00160/img-mean-std-00160758.npy +3 -0
  25. 00160/img-mean-std-00160789.npy +3 -0
  26. 00160/img-mean-std-00160841.npy +3 -0
  27. 00160/img-mean-std-00160846.npy +3 -0
  28. 00160/img-mean-std-00160890.npy +3 -0
  29. 00160/img-mean-std-00160897.npy +3 -0
  30. 00160/img-mean-std-00160919.npy +3 -0
  31. 00160/img-mean-std-00160962.npy +3 -0
  32. 00160/img-mean-std-00160965.npy +3 -0
  33. 01242/img-mean-std-01242016.npy +3 -0
  34. 01242/img-mean-std-01242018.npy +3 -0
  35. 01242/img-mean-std-01242063.npy +3 -0
  36. 01242/img-mean-std-01242064.npy +3 -0
  37. 01242/img-mean-std-01242132.npy +3 -0
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  39. 01242/img-mean-std-01242147.npy +3 -0
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  48. 01242/img-mean-std-01242281.npy +3 -0
  49. 01242/img-mean-std-01242286.npy +3 -0
  50. 01242/img-mean-std-01242288.npy +3 -0
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