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  1. 00207/img-mean-std-00207002.npy +3 -0
  2. 00207/img-mean-std-00207005.npy +3 -0
  3. 00207/img-mean-std-00207033.npy +3 -0
  4. 00207/img-mean-std-00207034.npy +3 -0
  5. 00207/img-mean-std-00207037.npy +3 -0
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  7. 00207/img-mean-std-00207041.npy +3 -0
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  9. 00207/img-mean-std-00207045.npy +3 -0
  10. 00207/img-mean-std-00207048.npy +3 -0
  11. 00207/img-mean-std-00207070.npy +3 -0
  12. 00207/img-mean-std-00207077.npy +3 -0
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  14. 00207/img-mean-std-00207093.npy +3 -0
  15. 00207/img-mean-std-00207094.npy +3 -0
  16. 00207/img-mean-std-00207099.npy +3 -0
  17. 00207/img-mean-std-00207110.npy +3 -0
  18. 00207/img-mean-std-00207113.npy +3 -0
  19. 00207/img-mean-std-00207114.npy +3 -0
  20. 00207/img-mean-std-00207119.npy +3 -0
  21. 00207/img-mean-std-00207121.npy +3 -0
  22. 00207/img-mean-std-00207126.npy +3 -0
  23. 00207/img-mean-std-00207128.npy +3 -0
  24. 00207/img-mean-std-00207153.npy +3 -0
  25. 00207/img-mean-std-00207154.npy +3 -0
  26. 00207/img-mean-std-00207161.npy +3 -0
  27. 00207/img-mean-std-00207166.npy +3 -0
  28. 00207/img-mean-std-00207179.npy +3 -0
  29. 00207/img-mean-std-00207182.npy +3 -0
  30. 00207/img-mean-std-00207185.npy +3 -0
  31. 00207/img-mean-std-00207200.npy +3 -0
  32. 00207/img-mean-std-00207203.npy +3 -0
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  34. 00207/img-mean-std-00207207.npy +3 -0
  35. 00207/img-mean-std-00207209.npy +3 -0
  36. 00207/img-mean-std-00207212.npy +3 -0
  37. 00207/img-mean-std-00207231.npy +3 -0
  38. 00207/img-mean-std-00207236.npy +3 -0
  39. 00207/img-mean-std-00207238.npy +3 -0
  40. 00207/img-mean-std-00207243.npy +3 -0
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  42. 00207/img-mean-std-00207271.npy +3 -0
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  44. 00207/img-mean-std-00207292.npy +3 -0
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  46. 00207/img-mean-std-00207312.npy +3 -0
  47. 00207/img-mean-std-00207315.npy +3 -0
  48. 00207/img-mean-std-00207320.npy +3 -0
  49. 00207/img-mean-std-00207323.npy +3 -0
  50. 00207/img-mean-std-00207324.npy +3 -0
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