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  1. 00173/img-mean-std-00173000.npy +3 -0
  2. 00173/img-mean-std-00173009.npy +3 -0
  3. 00173/img-mean-std-00173023.npy +3 -0
  4. 00173/img-mean-std-00173032.npy +3 -0
  5. 00173/img-mean-std-00173035.npy +3 -0
  6. 00173/img-mean-std-00173040.npy +3 -0
  7. 00173/img-mean-std-00173047.npy +3 -0
  8. 00173/img-mean-std-00173049.npy +3 -0
  9. 00173/img-mean-std-00173058.npy +3 -0
  10. 00173/img-mean-std-00173072.npy +3 -0
  11. 00173/img-mean-std-00173075.npy +3 -0
  12. 00173/img-mean-std-00173080.npy +3 -0
  13. 00173/img-mean-std-00173089.npy +3 -0
  14. 00173/img-mean-std-00173091.npy +3 -0
  15. 00173/img-mean-std-00173096.npy +3 -0
  16. 00173/img-mean-std-00173098.npy +3 -0
  17. 00173/img-mean-std-00173100.npy +3 -0
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  19. 00173/img-mean-std-00173109.npy +3 -0
  20. 00173/img-mean-std-00173111.npy +3 -0
  21. 00173/img-mean-std-00173116.npy +3 -0
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  24. 00173/img-mean-std-00173156.npy +3 -0
  25. 00173/img-mean-std-00173158.npy +3 -0
  26. 00173/img-mean-std-00173163.npy +3 -0
  27. 00173/img-mean-std-00173164.npy +3 -0
  28. 00173/img-mean-std-00173175.npy +3 -0
  29. 00173/img-mean-std-00173180.npy +3 -0
  30. 00173/img-mean-std-00173187.npy +3 -0
  31. 00173/img-mean-std-00173201.npy +3 -0
  32. 00173/img-mean-std-00173206.npy +3 -0
  33. 00173/img-mean-std-00173208.npy +3 -0
  34. 00173/img-mean-std-00173210.npy +3 -0
  35. 00173/img-mean-std-00173217.npy +3 -0
  36. 00173/img-mean-std-00173241.npy +3 -0
  37. 00173/img-mean-std-00173246.npy +3 -0
  38. 00173/img-mean-std-00173273.npy +3 -0
  39. 00173/img-mean-std-00173274.npy +3 -0
  40. 00173/img-mean-std-00173290.npy +3 -0
  41. 00173/img-mean-std-00173297.npy +3 -0
  42. 00173/img-mean-std-00173317.npy +3 -0
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  47. 00173/img-mean-std-00173334.npy +3 -0
  48. 00173/img-mean-std-00173341.npy +3 -0
  49. 00173/img-mean-std-00173346.npy +3 -0
  50. 00173/img-mean-std-00173348.npy +3 -0
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