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  1. 00207/img-mean-std-00207003.npy +3 -0
  2. 00207/img-mean-std-00207004.npy +3 -0
  3. 00207/img-mean-std-00207012.npy +3 -0
  4. 00207/img-mean-std-00207015.npy +3 -0
  5. 00207/img-mean-std-00207036.npy +3 -0
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  7. 00207/img-mean-std-00207043.npy +3 -0
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  9. 00207/img-mean-std-00207068.npy +3 -0
  10. 00207/img-mean-std-00207069.npy +3 -0
  11. 00207/img-mean-std-00207071.npy +3 -0
  12. 00207/img-mean-std-00207076.npy +3 -0
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  14. 00207/img-mean-std-00207092.npy +3 -0
  15. 00207/img-mean-std-00207112.npy +3 -0
  16. 00207/img-mean-std-00207115.npy +3 -0
  17. 00207/img-mean-std-00207120.npy +3 -0
  18. 00207/img-mean-std-00207127.npy +3 -0
  19. 00207/img-mean-std-00207129.npy +3 -0
  20. 00207/img-mean-std-00207131.npy +3 -0
  21. 00207/img-mean-std-00207136.npy +3 -0
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  24. 00207/img-mean-std-00207144.npy +3 -0
  25. 00207/img-mean-std-00207152.npy +3 -0
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  27. 00207/img-mean-std-00207160.npy +3 -0
  28. 00207/img-mean-std-00207169.npy +3 -0
  29. 00207/img-mean-std-00207183.npy +3 -0
  30. 00207/img-mean-std-00207184.npy +3 -0
  31. 00207/img-mean-std-00207195.npy +3 -0
  32. 00207/img-mean-std-00207202.npy +3 -0
  33. 00207/img-mean-std-00207205.npy +3 -0
  34. 00207/img-mean-std-00207221.npy +3 -0
  35. 00207/img-mean-std-00207226.npy +3 -0
  36. 00207/img-mean-std-00207230.npy +3 -0
  37. 00207/img-mean-std-00207237.npy +3 -0
  38. 00207/img-mean-std-00207239.npy +3 -0
  39. 00207/img-mean-std-00207242.npy +3 -0
  40. 00207/img-mean-std-00207245.npy +3 -0
  41. 00207/img-mean-std-00207253.npy +3 -0
  42. 00207/img-mean-std-00207254.npy +3 -0
  43. 00207/img-mean-std-00207277.npy +3 -0
  44. 00207/img-mean-std-00207282.npy +3 -0
  45. 00207/img-mean-std-00207285.npy +3 -0
  46. 00207/img-mean-std-00207293.npy +3 -0
  47. 00207/img-mean-std-00207294.npy +3 -0
  48. 00207/img-mean-std-00207302.npy +3 -0
  49. 00207/img-mean-std-00207303.npy +3 -0
  50. 00207/img-mean-std-00207305.npy +3 -0
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